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Sample records for reconstruction algorithm based

  1. Research on compressive sensing reconstruction algorithm based on total variation model

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    Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

    2017-12-01

    Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

  2. A Superresolution Image Reconstruction Algorithm Based on Landweber in Electrical Capacitance Tomography

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    Chen Deyun

    2013-01-01

    Full Text Available According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm.

  3. Reconstruction algorithm in compressed sensing based on maximum a posteriori estimation

    International Nuclear Information System (INIS)

    Takeda, Koujin; Kabashima, Yoshiyuki

    2013-01-01

    We propose a systematic method for constructing a sparse data reconstruction algorithm in compressed sensing at a relatively low computational cost for general observation matrix. It is known that the cost of ℓ 1 -norm minimization using a standard linear programming algorithm is O(N 3 ). We show that this cost can be reduced to O(N 2 ) by applying the approach of posterior maximization. Furthermore, in principle, the algorithm from our approach is expected to achieve the widest successful reconstruction region, which is evaluated from theoretical argument. We also discuss the relation between the belief propagation-based reconstruction algorithm introduced in preceding works and our approach

  4. A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video

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    Zhang Liangpei

    2007-01-01

    Full Text Available Super-resolution (SR reconstruction technique is capable of producing a high-resolution image from a sequence of low-resolution images. In this paper, we study an efficient SR algorithm for digital video. To effectively deal with the intractable problems in SR video reconstruction, such as inevitable motion estimation errors, noise, blurring, missing regions, and compression artifacts, the total variation (TV regularization is employed in the reconstruction model. We use the fixed-point iteration method and preconditioning techniques to efficiently solve the associated nonlinear Euler-Lagrange equations of the corresponding variational problem in SR. The proposed algorithm has been tested in several cases of motion and degradation. It is also compared with the Laplacian regularization-based SR algorithm and other TV-based SR algorithms. Experimental results are presented to illustrate the effectiveness of the proposed algorithm.

  5. Time Reversal Reconstruction Algorithm Based on PSO Optimized SVM Interpolation for Photoacoustic Imaging

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    Mingjian Sun

    2015-01-01

    Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.

  6. Imaging reconstruction based on improved wavelet denoising combined with parallel-beam filtered back-projection algorithm

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    Ren, Zhong; Liu, Guodong; Huang, Zhen

    2012-11-01

    The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.

  7. Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

    International Nuclear Information System (INIS)

    Tang Jie; Nett, Brian E; Chen Guanghong

    2009-01-01

    Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.

  8. A compressed sensing based reconstruction algorithm for synchrotron source propagation-based X-ray phase contrast computed tomography

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    Melli, Seyed Ali, E-mail: sem649@mail.usask.ca [Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK (Canada); Wahid, Khan A. [Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK (Canada); Babyn, Paul [Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK (Canada); Montgomery, James [College of Medicine, University of Saskatchewan, Saskatoon, SK (Canada); Snead, Elisabeth [Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK (Canada); El-Gayed, Ali [College of Medicine, University of Saskatchewan, Saskatoon, SK (Canada); Pettitt, Murray; Wolkowski, Bailey [College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK (Canada); Wesolowski, Michal [Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK (Canada)

    2016-01-11

    Synchrotron source propagation-based X-ray phase contrast computed tomography is increasingly used in pre-clinical imaging. However, it typically requires a large number of projections, and subsequently a large radiation dose, to produce high quality images. To improve the applicability of this imaging technique, reconstruction algorithms that can reduce the radiation dose and acquisition time without degrading image quality are needed. The proposed research focused on using a novel combination of Douglas–Rachford splitting and randomized Kaczmarz algorithms to solve large-scale total variation based optimization in a compressed sensing framework to reconstruct 2D images from a reduced number of projections. Visual assessment and quantitative performance evaluations of a synthetic abdomen phantom and real reconstructed image of an ex-vivo slice of canine prostate tissue demonstrate that the proposed algorithm is competitive in reconstruction process compared with other well-known algorithms. An additional potential benefit of reducing the number of projections would be reduction of time for motion artifact to occur if the sample moves during image acquisition. Use of this reconstruction algorithm to reduce the required number of projections in synchrotron source propagation-based X-ray phase contrast computed tomography is an effective form of dose reduction that may pave the way for imaging of in-vivo samples.

  9. Spectral CT metal artifact reduction with an optimization-based reconstruction algorithm

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    Gilat Schmidt, Taly; Barber, Rina F.; Sidky, Emil Y.

    2017-03-01

    Metal objects cause artifacts in computed tomography (CT) images. This work investigated the feasibility of a spectral CT method to reduce metal artifacts. Spectral CT acquisition combined with optimization-based reconstruction is proposed to reduce artifacts by modeling the physical effects that cause metal artifacts and by providing the flexibility to selectively remove corrupted spectral measurements in the spectral-sinogram space. The proposed Constrained `One-Step' Spectral CT Image Reconstruction (cOSSCIR) algorithm directly estimates the basis material maps while enforcing convex constraints. The incorporation of constraints on the reconstructed basis material maps is expected to mitigate undersampling effects that occur when corrupted data is excluded from reconstruction. The feasibility of the cOSSCIR algorithm to reduce metal artifacts was investigated through simulations of a pelvis phantom. The cOSSCIR algorithm was investigated with and without the use of a third basis material representing metal. The effects of excluding data corrupted by metal were also investigated. The results demonstrated that the proposed cOSSCIR algorithm reduced metal artifacts and improved CT number accuracy. For example, CT number error in a bright shading artifact region was reduced from 403 HU in the reference filtered backprojection reconstruction to 33 HU using the proposed algorithm in simulation. In the dark shading regions, the error was reduced from 1141 HU to 25 HU. Of the investigated approaches, decomposing the data into three basis material maps and excluding the corrupted data demonstrated the greatest reduction in metal artifacts.

  10. Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

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    Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

    2016-01-01

    To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (palgorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (palgorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

  11. Level-set-based reconstruction algorithm for EIT lung images: first clinical results.

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    Rahmati, Peyman; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz; Adler, Andy

    2012-05-01

    We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.

  12. Level-set-based reconstruction algorithm for EIT lung images: first clinical results

    International Nuclear Information System (INIS)

    Rahmati, Peyman; Adler, Andy; Soleimani, Manuchehr; Pulletz, Sven; Frerichs, Inéz

    2012-01-01

    We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure–volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM. (paper)

  13. An accelerated threshold-based back-projection algorithm for Compton camera image reconstruction

    International Nuclear Information System (INIS)

    Mundy, Daniel W.; Herman, Michael G.

    2011-01-01

    Purpose: Compton camera imaging (CCI) systems are currently under investigation for radiotherapy dose reconstruction and verification. The ability of such a system to provide real-time images during dose delivery will be limited by the computational speed of the image reconstruction algorithm. In this work, the authors present a fast and simple method by which to generate an initial back-projected image from acquired CCI data, suitable for use in a filtered back-projection algorithm or as a starting point for iterative reconstruction algorithms, and compare its performance to the current state of the art. Methods: Each detector event in a CCI system describes a conical surface that includes the true point of origin of the detected photon. Numerical image reconstruction algorithms require, as a first step, the back-projection of each of these conical surfaces into an image space. The algorithm presented here first generates a solution matrix for each slice of the image space by solving the intersection of the conical surface with the image plane. Each element of the solution matrix is proportional to the distance of the corresponding voxel from the true intersection curve. A threshold function was developed to extract those pixels sufficiently close to the true intersection to generate a binary intersection curve. This process is repeated for each image plane for each CCI detector event, resulting in a three-dimensional back-projection image. The performance of this algorithm was tested against a marching algorithm known for speed and accuracy. Results: The threshold-based algorithm was found to be approximately four times faster than the current state of the art with minimal deficit to image quality, arising from the fact that a generically applicable threshold function cannot provide perfect results in all situations. The algorithm fails to extract a complete intersection curve in image slices near the detector surface for detector event cones having axes nearly

  14. Reconstruction of a digital core containing clay minerals based on a clustering algorithm.

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    He, Yanlong; Pu, Chunsheng; Jing, Cheng; Gu, Xiaoyu; Chen, Qingdong; Liu, Hongzhi; Khan, Nasir; Dong, Qiaoling

    2017-10-01

    It is difficult to obtain a core sample and information for digital core reconstruction of mature sandstone reservoirs around the world, especially for an unconsolidated sandstone reservoir. Meanwhile, reconstruction and division of clay minerals play a vital role in the reconstruction of the digital cores, although the two-dimensional data-based reconstruction methods are specifically applicable as the microstructure reservoir simulation methods for the sandstone reservoir. However, reconstruction of clay minerals is still challenging from a research viewpoint for the better reconstruction of various clay minerals in the digital cores. In the present work, the content of clay minerals was considered on the basis of two-dimensional information about the reservoir. After application of the hybrid method, and compared with the model reconstructed by the process-based method, the digital core containing clay clusters without the labels of the clusters' number, size, and texture were the output. The statistics and geometry of the reconstruction model were similar to the reference model. In addition, the Hoshen-Kopelman algorithm was used to label various connected unclassified clay clusters in the initial model and then the number and size of clay clusters were recorded. At the same time, the K-means clustering algorithm was applied to divide the labeled, large connecting clusters into smaller clusters on the basis of difference in the clusters' characteristics. According to the clay minerals' characteristics, such as types, textures, and distributions, the digital core containing clay minerals was reconstructed by means of the clustering algorithm and the clay clusters' structure judgment. The distributions and textures of the clay minerals of the digital core were reasonable. The clustering algorithm improved the digital core reconstruction and provided an alternative method for the simulation of different clay minerals in the digital cores.

  15. Reconstruction of a digital core containing clay minerals based on a clustering algorithm

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    He, Yanlong; Pu, Chunsheng; Jing, Cheng; Gu, Xiaoyu; Chen, Qingdong; Liu, Hongzhi; Khan, Nasir; Dong, Qiaoling

    2017-10-01

    It is difficult to obtain a core sample and information for digital core reconstruction of mature sandstone reservoirs around the world, especially for an unconsolidated sandstone reservoir. Meanwhile, reconstruction and division of clay minerals play a vital role in the reconstruction of the digital cores, although the two-dimensional data-based reconstruction methods are specifically applicable as the microstructure reservoir simulation methods for the sandstone reservoir. However, reconstruction of clay minerals is still challenging from a research viewpoint for the better reconstruction of various clay minerals in the digital cores. In the present work, the content of clay minerals was considered on the basis of two-dimensional information about the reservoir. After application of the hybrid method, and compared with the model reconstructed by the process-based method, the digital core containing clay clusters without the labels of the clusters' number, size, and texture were the output. The statistics and geometry of the reconstruction model were similar to the reference model. In addition, the Hoshen-Kopelman algorithm was used to label various connected unclassified clay clusters in the initial model and then the number and size of clay clusters were recorded. At the same time, the K -means clustering algorithm was applied to divide the labeled, large connecting clusters into smaller clusters on the basis of difference in the clusters' characteristics. According to the clay minerals' characteristics, such as types, textures, and distributions, the digital core containing clay minerals was reconstructed by means of the clustering algorithm and the clay clusters' structure judgment. The distributions and textures of the clay minerals of the digital core were reasonable. The clustering algorithm improved the digital core reconstruction and provided an alternative method for the simulation of different clay minerals in the digital cores.

  16. A fast sparse reconstruction algorithm for electrical tomography

    International Nuclear Information System (INIS)

    Zhao, Jia; Xu, Yanbin; Tan, Chao; Dong, Feng

    2014-01-01

    Electrical tomography (ET) has been widely investigated due to its advantages of being non-radiative, low-cost and high-speed. However, the image reconstruction of ET is a nonlinear and ill-posed inverse problem and the imaging results are easily affected by measurement noise. A sparse reconstruction algorithm based on L 1 regularization is robust to noise and consequently provides a high quality of reconstructed images. In this paper, a sparse reconstruction by separable approximation algorithm (SpaRSA) is extended to solve the ET inverse problem. The algorithm is competitive with the fastest state-of-the-art algorithms in solving the standard L 2 −L 1 problem. However, it is computationally expensive when the dimension of the matrix is large. To further improve the calculation speed of solving inverse problems, a projection method based on the Krylov subspace is employed and combined with the SpaRSA algorithm. The proposed algorithm is tested with image reconstruction of electrical resistance tomography (ERT). Both simulation and experimental results demonstrate that the proposed method can reduce the computational time and improve the noise robustness for the image reconstruction. (paper)

  17. Multichannel algorithm for fast 3D reconstruction

    International Nuclear Information System (INIS)

    Rodet, Thomas; Grangeat, Pierre; Desbat, Laurent

    2002-01-01

    Some recent medical imaging applications such as functional imaging (PET and SPECT) or interventional imaging (CT fluoroscopy) involve increasing amounts of data. In order to reduce the image reconstruction time, we develop a new fast 3D reconstruction algorithm based on a divide and conquer approach. The proposed multichannel algorithm performs an indirect frequential subband decomposition of the image f to be reconstructed (f=Σf j ) through the filtering of the projections Rf. The subband images f j are reconstructed on a downsampled grid without information suppression. In order to reduce the computation time, we do not backproject the null filtered projections and we downsample the number of projections according to the Shannon conditions associated with the subband image. Our algorithm is based on filtering and backprojection operators. Using the same algorithms for these basic operators, our approach is three and a half times faster than a classical FBP algorithm for a 2D image 512x512 and six times faster for a 3D image 32x512x512. (author)

  18. A Spectral Reconstruction Algorithm of Miniature Spectrometer Based on Sparse Optimization and Dictionary Learning.

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    Zhang, Shang; Dong, Yuhan; Fu, Hongyan; Huang, Shao-Lun; Zhang, Lin

    2018-02-22

    The miniaturization of spectrometer can broaden the application area of spectrometry, which has huge academic and industrial value. Among various miniaturization approaches, filter-based miniaturization is a promising implementation by utilizing broadband filters with distinct transmission functions. Mathematically, filter-based spectral reconstruction can be modeled as solving a system of linear equations. In this paper, we propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning. To verify the feasibility of the reconstruction algorithm, we design and implement a simple prototype of a filter-based miniature spectrometer. The experimental results demonstrate that sparse optimization is well applicable to spectral reconstruction whether the spectra are directly sparse or not. As for the non-directly sparse spectra, their sparsity can be enhanced by dictionary learning. In conclusion, the proposed approach has a bright application prospect in fabricating a practical miniature spectrometer.

  19. A reconstruction algorithm for coherent scatter computed tomography based on filtered back-projection

    International Nuclear Information System (INIS)

    Stevendaal, U. van; Schlomka, J.-P.; Harding, A.; Grass, M.

    2003-01-01

    Coherent scatter computed tomography (CSCT) is a reconstructive x-ray imaging technique that yields the spatially resolved coherent-scatter form factor of the investigated object. Reconstruction from coherently scattered x-rays is commonly done using algebraic reconstruction techniques (ART). In this paper, we propose an alternative approach based on filtered back-projection. For the first time, a three-dimensional (3D) filtered back-projection technique using curved 3D back-projection lines is applied to two-dimensional coherent scatter projection data. The proposed algorithm is tested with simulated projection data as well as with projection data acquired with a demonstrator setup similar to a multi-line CT scanner geometry. While yielding comparable image quality as ART reconstruction, the modified 3D filtered back-projection algorithm is about two orders of magnitude faster. In contrast to iterative reconstruction schemes, it has the advantage that subfield-of-view reconstruction becomes feasible. This allows a selective reconstruction of the coherent-scatter form factor for a region of interest. The proposed modified 3D filtered back-projection algorithm is a powerful reconstruction technique to be implemented in a CSCT scanning system. This method gives coherent scatter CT the potential of becoming a competitive modality for medical imaging or nondestructive testing

  20. A Spectral Reconstruction Algorithm of Miniature Spectrometer Based on Sparse Optimization and Dictionary Learning

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    Zhang, Shang; Fu, Hongyan; Huang, Shao-Lun; Zhang, Lin

    2018-01-01

    The miniaturization of spectrometer can broaden the application area of spectrometry, which has huge academic and industrial value. Among various miniaturization approaches, filter-based miniaturization is a promising implementation by utilizing broadband filters with distinct transmission functions. Mathematically, filter-based spectral reconstruction can be modeled as solving a system of linear equations. In this paper, we propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning. To verify the feasibility of the reconstruction algorithm, we design and implement a simple prototype of a filter-based miniature spectrometer. The experimental results demonstrate that sparse optimization is well applicable to spectral reconstruction whether the spectra are directly sparse or not. As for the non-directly sparse spectra, their sparsity can be enhanced by dictionary learning. In conclusion, the proposed approach has a bright application prospect in fabricating a practical miniature spectrometer. PMID:29470406

  1. A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

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    Hamidreza Mousavi

    2017-01-01

    Full Text Available Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN. In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

  2. A new iterative algorithm to reconstruct the refractive index.

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    Liu, Y J; Zhu, P P; Chen, B; Wang, J Y; Yuan, Q X; Huang, W X; Shu, H; Li, E R; Liu, X S; Zhang, K; Ming, H; Wu, Z Y

    2007-06-21

    The latest developments in x-ray imaging are associated with techniques based on the phase contrast. However, the image reconstruction procedures demand significant improvements of the traditional methods, and/or new algorithms have to be introduced to take advantage of the high contrast and sensitivity of the new experimental techniques. In this letter, an improved iterative reconstruction algorithm based on the maximum likelihood expectation maximization technique is presented and discussed in order to reconstruct the distribution of the refractive index from data collected by an analyzer-based imaging setup. The technique considered probes the partial derivative of the refractive index with respect to an axis lying in the meridional plane and perpendicular to the propagation direction. Computer simulations confirm the reliability of the proposed algorithm. In addition, the comparison between an analytical reconstruction algorithm and the iterative method has been also discussed together with the convergent characteristic of this latter algorithm. Finally, we will show how the proposed algorithm may be applied to reconstruct the distribution of the refractive index of an epoxy cylinder containing small air bubbles of about 300 micro of diameter.

  3. Selected event reconstruction algorithms for the CBM experiment at FAIR

    International Nuclear Information System (INIS)

    Lebedev, Semen; Höhne, Claudia; Lebedev, Andrey; Ososkov, Gennady

    2014-01-01

    Development of fast and efficient event reconstruction algorithms is an important and challenging task in the Compressed Baryonic Matter (CBM) experiment at the future FAIR facility. The event reconstruction algorithms have to process terabytes of input data produced in particle collisions. In this contribution, several event reconstruction algorithms are presented. Optimization of the algorithms in the following CBM detectors are discussed: Ring Imaging Cherenkov (RICH) detector, Transition Radiation Detectors (TRD) and Muon Chamber (MUCH). The ring reconstruction algorithm in the RICH is discussed. In TRD and MUCH track reconstruction algorithms are based on track following and Kalman Filter methods. All algorithms were significantly optimized to achieve maximum speed up and minimum memory consumption. Obtained results showed that a significant speed up factor for all algorithms was achieved and the reconstruction efficiency stays at high level.

  4. Cone-beam and fan-beam image reconstruction algorithms based on spherical and circular harmonics

    International Nuclear Information System (INIS)

    Zeng, Gengsheng L; Gullberg, Grant T

    2004-01-01

    A cone-beam image reconstruction algorithm using spherical harmonic expansions is proposed. The reconstruction algorithm is in the form of a summation of inner products of two discrete arrays of spherical harmonic expansion coefficients at each cone-beam point of acquisition. This form is different from the common filtered backprojection algorithm and the direct Fourier reconstruction algorithm. There is no re-sampling of the data, and spherical harmonic expansions are used instead of Fourier expansions. As a special case, a new fan-beam image reconstruction algorithm is also derived in terms of a circular harmonic expansion. Computer simulation results for both cone-beam and fan-beam algorithms are presented for circular planar orbit acquisitions. The algorithms give accurate reconstructions; however, the implementation of the cone-beam reconstruction algorithm is computationally intensive. A relatively efficient algorithm is proposed for reconstructing the central slice of the image when a circular scanning orbit is used

  5. A novel algorithm of super-resolution image reconstruction based on multi-class dictionaries for natural scene

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    Wu, Wei; Zhao, Dewei; Zhang, Huan

    2015-12-01

    Super-resolution image reconstruction is an effective method to improve the image quality. It has important research significance in the field of image processing. However, the choice of the dictionary directly affects the efficiency of image reconstruction. A sparse representation theory is introduced into the problem of the nearest neighbor selection. Based on the sparse representation of super-resolution image reconstruction method, a super-resolution image reconstruction algorithm based on multi-class dictionary is analyzed. This method avoids the redundancy problem of only training a hyper complete dictionary, and makes the sub-dictionary more representatives, and then replaces the traditional Euclidean distance computing method to improve the quality of the whole image reconstruction. In addition, the ill-posed problem is introduced into non-local self-similarity regularization. Experimental results show that the algorithm is much better results than state-of-the-art algorithm in terms of both PSNR and visual perception.

  6. Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

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    Elahi, Sana; kaleem, Muhammad; Omer, Hammad

    2018-01-01

    Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

  7. Advanced reconstruction algorithms for electron tomography: From comparison to combination

    Energy Technology Data Exchange (ETDEWEB)

    Goris, B. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Roelandts, T. [Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Batenburg, K.J. [Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Centrum Wiskunde and Informatica, Science Park 123, NL-1098XG Amsterdam (Netherlands); Heidari Mezerji, H. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Bals, S., E-mail: sara.bals@ua.ac.be [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium)

    2013-04-15

    In this work, the simultaneous iterative reconstruction technique (SIRT), the total variation minimization (TVM) reconstruction technique and the discrete algebraic reconstruction technique (DART) for electron tomography are compared and the advantages and disadvantages are discussed. Furthermore, we describe how the result of a three dimensional (3D) reconstruction based on TVM can provide objective information that is needed as the input for a DART reconstruction. This approach results in a tomographic reconstruction of which the segmentation is carried out in an objective manner. - Highlights: ► A comparative study between different reconstruction algorithms for tomography is performed. ► Reconstruction algorithms that uses prior knowledge about the specimen have a superior result. ► One reconstruction algorithm can provide the prior knowledge for a second algorithm.

  8. Duality reconstruction algorithm for use in electrical impedance tomography

    International Nuclear Information System (INIS)

    Abdullah, M.Z.; Dickin, F.J.

    1996-01-01

    A duality reconstruction algorithm for solving the inverse problem in electrical impedance tomography (EIT) is described. In this method, an algorithm based on the Geselowitz compensation (GC) theorem is used first to reconstruct an approximate version of the image. It is then fed as a first guessed data to the modified Newton-Raphson (MNR) algorithm which iteratively correct the image until a final acceptable solution is reached. The implementation of the GC and MNR based algorithms using the finite element method will be discussed. Reconstructed images produced by the algorithm will also be presented. Consideration is also given to the most computationally intensive aspects of the algorithm, namely the inversion of the large and sparse matrices. The methods taken to approximately compute the inverse ot those matrices will be outlined. (author)

  9. High performance graphics processor based computed tomography reconstruction algorithms for nuclear and other large scale applications.

    Energy Technology Data Exchange (ETDEWEB)

    Jimenez, Edward S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Orr, Laurel J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Thompson, Kyle R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2013-09-01

    The goal of this work is to develop a fast computed tomography (CT) reconstruction algorithm based on graphics processing units (GPU) that achieves significant improvement over traditional central processing unit (CPU) based implementations. The main challenge in developing a CT algorithm that is capable of handling very large datasets is parallelizing the algorithm in such a way that data transfer does not hinder performance of the reconstruction algorithm. General Purpose Graphics Processing (GPGPU) is a new technology that the Science and Technology (S&T) community is starting to adopt in many fields where CPU-based computing is the norm. GPGPU programming requires a new approach to algorithm development that utilizes massively multi-threaded environments. Multi-threaded algorithms in general are difficult to optimize since performance bottlenecks occur that are non-existent in single-threaded algorithms such as memory latencies. If an efficient GPU-based CT reconstruction algorithm can be developed; computational times could be improved by a factor of 20. Additionally, cost benefits will be realized as commodity graphics hardware could potentially replace expensive supercomputers and high-end workstations. This project will take advantage of the CUDA programming environment and attempt to parallelize the task in such a way that multiple slices of the reconstruction volume are computed simultaneously. This work will also take advantage of the GPU memory by utilizing asynchronous memory transfers, GPU texture memory, and (when possible) pinned host memory so that the memory transfer bottleneck inherent to GPGPU is amortized. Additionally, this work will take advantage of GPU-specific hardware (i.e. fast texture memory, pixel-pipelines, hardware interpolators, and varying memory hierarchy) that will allow for additional performance improvements.

  10. A combination-weighted Feldkamp-based reconstruction algorithm for cone-beam CT

    International Nuclear Information System (INIS)

    Mori, Shinichiro; Endo, Masahiro; Komatsu, Shuhei; Kandatsu, Susumu; Yashiro, Tomoyasu; Baba, Masayuki

    2006-01-01

    The combination-weighted Feldkamp algorithm (CW-FDK) was developed and tested in a phantom in order to reduce cone-beam artefacts and enhance cranio-caudal reconstruction coverage in an attempt to improve image quality when utilizing cone-beam computed tomography (CBCT). Using a 256-slice cone-beam CT (256CBCT), image quality (CT-number uniformity and geometrical accuracy) was quantitatively evaluated in phantom and clinical studies, and the results were compared to those obtained with the original Feldkamp algorithm. A clinical study was done in lung cancer patients under breath holding and free breathing. Image quality for the original Feldkamp algorithm is degraded at the edge of the scan region due to the missing volume, commensurate with the cranio-caudal distance between the reconstruction and central planes. The CW-FDK extended the reconstruction coverage to equal the scan coverage and improved reconstruction accuracy, unaffected by the cranio-caudal distance. The extended reconstruction coverage with good image quality provided by the CW-FDK will be clinically investigated for improving diagnostic and radiotherapy applications. In addition, this algorithm can also be adapted for use in relatively wide cone-angle CBCT such as with a flat-panel detector CBCT

  11. A combinational fast algorithm for image reconstruction

    International Nuclear Information System (INIS)

    Wu Zhongquan

    1987-01-01

    A combinational fast algorithm has been developed in order to increase the speed of reconstruction. First, an interpolation method based on B-spline functions is used in image reconstruction. Next, the influence of the boundary conditions assumed here on the interpolation of filtered projections and on the image reconstruction is discussed. It is shown that this boundary condition has almost no influence on the image in the central region of the image space, because the error of interpolation rapidly decreases by a factor of ten in shifting two pixels from the edge toward the center. In addition, a fast algorithm for computing the detecting angle has been used with the mentioned interpolation algorithm, and the cost for detecting angle computaton is reduced by a factor of two. The implementation results show that in the same subjective and objective fidelity, the computational cost for the interpolation using this algorithm is about one-twelfth of the conventional algorithm

  12. Versatility of the CFR algorithm for limited angle reconstruction

    International Nuclear Information System (INIS)

    Fujieda, I.; Heiskanen, K.; Perez-Mendez, V.

    1990-01-01

    The constrained Fourier reconstruction (CFR) algorithm and the iterative reconstruction-reprojection (IRR) algorithm are evaluated based on their accuracy for three types of limited angle reconstruction problems. The cFR algorithm performs better for problems such as Xray CT imaging of a nuclear reactor core with one large data gap due to structural blocking of the source and detector pair. For gated heart imaging by Xray CT, radioisotope distribution imaging by PET or SPECT, using a polygonal array of gamma cameras with insensitive gaps between camera boundaries, the IRR algorithm has a slight advantage over the CFR algorithm but the difference is not significant

  13. Missing texture reconstruction method based on error reduction algorithm using Fourier transform magnitude estimation scheme.

    Science.gov (United States)

    Ogawa, Takahiro; Haseyama, Miki

    2013-03-01

    A missing texture reconstruction method based on an error reduction (ER) algorithm, including a novel estimation scheme of Fourier transform magnitudes is presented in this brief. In our method, Fourier transform magnitude is estimated for a target patch including missing areas, and the missing intensities are estimated by retrieving its phase based on the ER algorithm. Specifically, by monitoring errors converged in the ER algorithm, known patches whose Fourier transform magnitudes are similar to that of the target patch are selected from the target image. In the second approach, the Fourier transform magnitude of the target patch is estimated from those of the selected known patches and their corresponding errors. Consequently, by using the ER algorithm, we can estimate both the Fourier transform magnitudes and phases to reconstruct the missing areas.

  14. Study on the effects of sample selection on spectral reflectance reconstruction based on the algorithm of compressive sensing

    International Nuclear Information System (INIS)

    Zhang, Leihong; Liang, Dong

    2016-01-01

    In order to solve the problem that reconstruction efficiency and precision is not high, in this paper different samples are selected to reconstruct spectral reflectance, and a new kind of spectral reflectance reconstruction method based on the algorithm of compressive sensing is provided. Four different color numbers of matte color cards such as the ColorChecker Color Rendition Chart and Color Checker SG, the copperplate paper spot color card of Panton, and the Munsell colors card are chosen as training samples, the spectral image is reconstructed respectively by the algorithm of compressive sensing and pseudo-inverse and Wiener, and the results are compared. These methods of spectral reconstruction are evaluated by root mean square error and color difference accuracy. The experiments show that the cumulative contribution rate and color difference of the Munsell colors card are better than those of the other three numbers of color cards in the same conditions of reconstruction, and the accuracy of the spectral reconstruction will be affected by the training sample of different numbers of color cards. The key technology of reconstruction means that the uniformity and representation of the training sample selection has important significance upon reconstruction. In this paper, the influence of the sample selection on the spectral image reconstruction is studied. The precision of the spectral reconstruction based on the algorithm of compressive sensing is higher than that of the traditional algorithm of spectral reconstruction. By the MATLAB simulation results, it can be seen that the spectral reconstruction precision and efficiency are affected by the different color numbers of the training sample. (paper)

  15. Algorithm for three dimension reconstruction of magnetic resonance tomographs and X-ray images based on Fast Fourier Transform

    International Nuclear Information System (INIS)

    Bueno, Josiane M.; Traina, Agma Juci M.; Cruvinel, Paulo E.

    1995-01-01

    This work presents an algorithm for three-dimensional digital image reconstruction. Such algorithms based on the combination of both a Fast Fourier Transform method with Hamming Window and the use of a tri-linear interpolation function. The algorithm allows not only the generation of three-dimensional spatial spin distribution maps for Magnetic Resonance Tomography data but also X and Y-rays linear attenuation coefficient maps for CT scanners. Results demonstrates the usefulness of the algorithm in three-dimensional image reconstruction by doing first two-dimensional reconstruction and rather after interpolation. The algorithm was developed in C++ language, and there are two available versions: one under the DOS environment, and the other under the UNIX/Sun environment. (author)

  16. A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT

    Science.gov (United States)

    Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo

    2016-11-01

    Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.

  17. A reconstruction algorithm for electrical impedance tomography based on sparsity regularization

    KAUST Repository

    Jin, Bangti

    2011-08-24

    This paper develops a novel sparse reconstruction algorithm for the electrical impedance tomography problem of determining a conductivity parameter from boundary measurements. The sparsity of the \\'inhomogeneity\\' with respect to a certain basis is a priori assumed. The proposed approach is motivated by a Tikhonov functional incorporating a sparsity-promoting ℓ 1-penalty term, and it allows us to obtain quantitative results when the assumption is valid. A novel iterative algorithm of soft shrinkage type was proposed. Numerical results for several two-dimensional problems with both single and multiple convex and nonconvex inclusions were presented to illustrate the features of the proposed algorithm and were compared with one conventional approach based on smoothness regularization. © 2011 John Wiley & Sons, Ltd.

  18. DART: a practical reconstruction algorithm for discrete tomography.

    Science.gov (United States)

    Batenburg, Kees Joost; Sijbers, Jan

    2011-09-01

    In this paper, we present an iterative reconstruction algorithm for discrete tomography, called discrete algebraic reconstruction technique (DART). DART can be applied if the scanned object is known to consist of only a few different compositions, each corresponding to a constant gray value in the reconstruction. Prior knowledge of the gray values for each of the compositions is exploited to steer the current reconstruction towards a reconstruction that contains only these gray values. Based on experiments with both simulated CT data and experimental μCT data, it is shown that DART is capable of computing more accurate reconstructions from a small number of projection images, or from a small angular range, than alternative methods. It is also shown that DART can deal effectively with noisy projection data and that the algorithm is robust with respect to errors in the estimation of the gray values.

  19. A fast 4D cone beam CT reconstruction method based on the OSC-TV algorithm.

    Science.gov (United States)

    Mascolo-Fortin, Julia; Matenine, Dmitri; Archambault, Louis; Després, Philippe

    2018-01-01

    Four-dimensional cone beam computed tomography allows for temporally resolved imaging with useful applications in radiotherapy, but raises particular challenges in terms of image quality and computation time. The purpose of this work is to develop a fast and accurate 4D algorithm by adapting a GPU-accelerated ordered subsets convex algorithm (OSC), combined with the total variation minimization regularization technique (TV). Different initialization schemes were studied to adapt the OSC-TV algorithm to 4D reconstruction: each respiratory phase was initialized either with a 3D reconstruction or a blank image. Reconstruction algorithms were tested on a dynamic numerical phantom and on a clinical dataset. 4D iterations were implemented for a cluster of 8 GPUs. All developed methods allowed for an adequate visualization of the respiratory movement and compared favorably to the McKinnon-Bates and adaptive steepest descent projection onto convex sets algorithms, while the 4D reconstructions initialized from a prior 3D reconstruction led to better overall image quality. The most suitable adaptation of OSC-TV to 4D CBCT was found to be a combination of a prior FDK reconstruction and a 4D OSC-TV reconstruction with a reconstruction time of 4.5 minutes. This relatively short reconstruction time could facilitate a clinical use.

  20. Iterative concurrent reconstruction algorithms for emission computed tomography

    International Nuclear Information System (INIS)

    Brown, J.K.; Hasegawa, B.H.; Lang, T.F.

    1994-01-01

    Direct reconstruction techniques, such as those based on filtered backprojection, are typically used for emission computed tomography (ECT), even though it has been argued that iterative reconstruction methods may produce better clinical images. The major disadvantage of iterative reconstruction algorithms, and a significant reason for their lack of clinical acceptance, is their computational burden. We outline a new class of ''concurrent'' iterative reconstruction techniques for ECT in which the reconstruction process is reorganized such that a significant fraction of the computational processing occurs concurrently with the acquisition of ECT projection data. These new algorithms use the 10-30 min required for acquisition of a typical SPECT scan to iteratively process the available projection data, significantly reducing the requirements for post-acquisition processing. These algorithms are tested on SPECT projection data from a Hoffman brain phantom acquired with a 2 x 10 5 counts in 64 views each having 64 projections. The SPECT images are reconstructed as 64 x 64 tomograms, starting with six angular views. Other angular views are added to the reconstruction process sequentially, in a manner that reflects their availability for a typical acquisition protocol. The results suggest that if T s of concurrent processing are used, the reconstruction processing time required after completion of the data acquisition can be reduced by at least 1/3 T s. (Author)

  1. Development of a new prior knowledge based image reconstruction algorithm for the cone-beam-CT in radiation therapy

    International Nuclear Information System (INIS)

    Vaegler, Sven

    2016-01-01

    The treatment of cancer in radiation therapy is achievable today by techniques that enable highly conformal dose distributions and steep dose gradients. In order to avoid mistreatment, these irradiation techniques have necessitated enhanced patient localization techniques. With an integrated x-ray tube at modern linear accelerators kV-projections can be acquired over a sufficiently large angular space and can be reconstructed to a volumetric image data set from the current situation of the patient prior to irradiation. The so-called Cone-Beam-CT (CBCT) allows a precise verification of patient positioning as well as adaptive radiotherapy. The benefits of an improved patient positioning due to a daily performed CBCT's is contrary to an increased and not negligible radiation exposure of the patient. In order to decrease the radiation exposure, substantial research effort is focused on various dose reduction strategies. Prominent strategies are the decrease of the charge per projection, the reduction of the number of projections as well as the reduction of the acquisition space. Unfortunately, these acquisition schemes lead to images with degraded quality with the widely used Feldkamp-Davis-Kress image reconstruction algorithm. More sophisticated image reconstruction techniques can deal with these dose-reduction strategies without degrading the image quality. A frequently investigated method is the image reconstruction by minimizing the total variation (TV), which is also known as Compressed Sensing (CS). A Compressed Sensing-based reconstruction framework that includes prior images into the reconstruction algorithm is the Prior-Image-Constrained- Compressed-Sensing algorithm (PICCS). The images reconstructed by PICCS outperform the reconstruction results of the conventional Feldkamp-Davis-Kress algorithm (FDK) based method if only a small number of projections are available. However, a drawback of PICCS is that major deviations between prior image data sets and the

  2. Neural network algorithm for image reconstruction using the grid friendly projections

    International Nuclear Information System (INIS)

    Cierniak, R.

    2011-01-01

    Full text: The presented paper describes a development of original approach to the reconstruction problem using a recurrent neural network. Particularly, the 'grid-friendly' angles of performed projections are selected according to the discrete Radon transform (DRT) concept to decrease the number of projections required. The methodology of our approach is consistent with analytical reconstruction algorithms. Reconstruction problem is reformulated in our approach to optimization problem. This problem is solved in present concept using method based on the maximum likelihood methodology. The reconstruction algorithm proposed in this work is consequently adapted for more practical discrete fan beam projections. Computer simulation results show that the neural network reconstruction algorithm designed to work in this way improves obtained results and outperforms conventional methods in reconstructed image quality. (author)

  3. A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

    Energy Technology Data Exchange (ETDEWEB)

    Felix, Simon; Bolzern, Roman; Battaglia, Marina, E-mail: simon.felix@fhnw.ch, E-mail: roman.bolzern@fhnw.ch, E-mail: marina.battaglia@fhnw.ch [University of Applied Sciences and Arts Northwestern Switzerland FHNW, 5210 Windisch (Switzerland)

    2017-11-01

    One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS-CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS-CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

  4. A Compressed Sensing-based Image Reconstruction Algorithm for Solar Flare X-Ray Observations

    Science.gov (United States)

    Felix, Simon; Bolzern, Roman; Battaglia, Marina

    2017-11-01

    One way of imaging X-ray emission from solar flares is to measure Fourier components of the spatial X-ray source distribution. We present a new compressed sensing-based algorithm named VIS_CS, which reconstructs the spatial distribution from such Fourier components. We demonstrate the application of the algorithm on synthetic and observed solar flare X-ray data from the Reuven Ramaty High Energy Solar Spectroscopic Imager satellite and compare its performance with existing algorithms. VIS_CS produces competitive results with accurate photometry and morphology, without requiring any algorithm- and X-ray-source-specific parameter tuning. Its robustness and performance make this algorithm ideally suited for the generation of quicklook images or large image cubes without user intervention, such as for imaging spectroscopy analysis.

  5. First results of genetic algorithm application in ML image reconstruction in emission tomography

    International Nuclear Information System (INIS)

    Smolik, W.

    1999-01-01

    This paper concerns application of genetic algorithm in maximum likelihood image reconstruction in emission tomography. The example of genetic algorithm for image reconstruction is presented. The genetic algorithm was based on the typical genetic scheme modified due to the nature of solved problem. The convergence of algorithm was examined. The different adaption functions, selection and crossover methods were verified. The algorithm was tested on simulated SPECT data. The obtained results of image reconstruction are discussed. (author)

  6. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation

    International Nuclear Information System (INIS)

    Zhao, Zhanqi; Möller, Knut; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich

    2014-01-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton–Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR C ) and (4) GREIT with individual thorax geometry (GR T ). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal–Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms. (paper)

  7. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2014-06-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

  8. Ant-Based Phylogenetic Reconstruction (ABPR: A new distance algorithm for phylogenetic estimation based on ant colony optimization

    Directory of Open Access Journals (Sweden)

    Karla Vittori

    2008-12-01

    Full Text Available We propose a new distance algorithm for phylogenetic estimation based on Ant Colony Optimization (ACO, named Ant-Based Phylogenetic Reconstruction (ABPR. ABPR joins two taxa iteratively based on evolutionary distance among sequences, while also accounting for the quality of the phylogenetic tree built according to the total length of the tree. Similar to optimization algorithms for phylogenetic estimation, the algorithm allows exploration of a larger set of nearly optimal solutions. We applied the algorithm to four empirical data sets of mitochondrial DNA ranging from 12 to 186 sequences, and from 898 to 16,608 base pairs, and covering taxonomic levels from populations to orders. We show that ABPR performs better than the commonly used Neighbor-Joining algorithm, except when sequences are too closely related (e.g., population-level sequences. The phylogenetic relationships recovered at and above species level by ABPR agree with conventional views. However, like other algorithms of phylogenetic estimation, the proposed algorithm failed to recover expected relationships when distances are too similar or when rates of evolution are very variable, leading to the problem of long-branch attraction. ABPR, as well as other ACO-based algorithms, is emerging as a fast and accurate alternative method of phylogenetic estimation for large data sets.

  9. A wavelet-based regularized reconstruction algorithm for SENSE parallel MRI with applications to neuroimaging

    International Nuclear Information System (INIS)

    Chaari, L.; Pesquet, J.Ch.; Chaari, L.; Ciuciu, Ph.; Benazza-Benyahia, A.

    2011-01-01

    To reduce scanning time and/or improve spatial/temporal resolution in some Magnetic Resonance Imaging (MRI) applications, parallel MRI acquisition techniques with multiple coils acquisition have emerged since the early 1990's as powerful imaging methods that allow a faster acquisition process. In these techniques, the full FOV image has to be reconstructed from the resulting acquired under sampled k-space data. To this end, several reconstruction techniques have been proposed such as the widely-used Sensitivity Encoding (SENSE) method. However, the reconstructed image generally presents artifacts when perturbations occur in both the measured data and the estimated coil sensitivity profiles. In this paper, we aim at achieving accurate image reconstruction under degraded experimental conditions (low magnetic field and high reduction factor), in which neither the SENSE method nor the Tikhonov regularization in the image domain give convincing results. To this end, we present a novel method for SENSE-based reconstruction which proceeds with regularization in the complex wavelet domain by promoting sparsity. The proposed approach relies on a fast algorithm that enables the minimization of regularized non-differentiable criteria including more general penalties than a classical l 1 term. To further enhance the reconstructed image quality, local convex constraints are added to the regularization process. In vivo human brain experiments carried out on Gradient-Echo (GRE) anatomical and Echo Planar Imaging (EPI) functional MRI data at 1.5 T indicate that our algorithm provides reconstructed images with reduced artifacts for high reduction factors. (authors)

  10. Algorithms for reconstructing images for industrial applications

    International Nuclear Information System (INIS)

    Lopes, R.T.; Crispim, V.R.

    1986-01-01

    Several algorithms for reconstructing objects from their projections are being studied in our Laboratory, for industrial applications. Such algorithms are useful locating the position and shape of different composition of materials in the object. A Comparative study of two algorithms is made. The two investigated algorithsm are: The MART (Multiplicative - Algebraic Reconstruction Technique) and the Convolution Method. The comparison are carried out from the point view of the quality of the image reconstructed, number of views and cost. (Author) [pt

  11. Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm

    International Nuclear Information System (INIS)

    Zhou Xiaolin; Yun Mingkai; Cao Xuexiang; Liu Shuangquan; Wang Lu; Huang Xianchao; Wei Long

    2014-01-01

    Single-photon emission computerized tomography and positron emission tomography are essential medical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different acquisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose. (authors)

  12. UV Reconstruction Algorithm And Diurnal Cycle Variability

    Science.gov (United States)

    Curylo, Aleksander; Litynska, Zenobia; Krzyscin, Janusz; Bogdanska, Barbara

    2009-03-01

    UV reconstruction is a method of estimation of surface UV with the use of available actinometrical and aerological measurements. UV reconstruction is necessary for the study of long-term UV change. A typical series of UV measurements is not longer than 15 years, which is too short for trend estimation. The essential problem in the reconstruction algorithm is the good parameterization of clouds. In our previous algorithm we used an empirical relation between Cloud Modification Factor (CMF) in global radiation and CMF in UV. The CMF is defined as the ratio between measured and modelled irradiances. Clear sky irradiance was calculated with a solar radiative transfer model. In the proposed algorithm, the time variability of global radiation during the diurnal cycle is used as an additional source of information. For elaborating an improved reconstruction algorithm relevant data from Legionowo [52.4 N, 21.0 E, 96 m a.s.l], Poland were collected with the following instruments: NILU-UV multi channel radiometer, Kipp&Zonen pyranometer, radiosonde profiles of ozone, humidity and temperature. The proposed algorithm has been used for reconstruction of UV at four Polish sites: Mikolajki, Kolobrzeg, Warszawa-Bielany and Zakopane since the early 1960s. Krzyscin's reconstruction of total ozone has been used in the calculations.

  13. Wind reconstruction algorithm for Viking Lander 1

    Science.gov (United States)

    Kynkäänniemi, Tuomas; Kemppinen, Osku; Harri, Ari-Matti; Schmidt, Walter

    2017-06-01

    The wind measurement sensors of Viking Lander 1 (VL1) were only fully operational for the first 45 sols of the mission. We have developed an algorithm for reconstructing the wind measurement data after the wind measurement sensor failures. The algorithm for wind reconstruction enables the processing of wind data during the complete VL1 mission. The heater element of the quadrant sensor, which provided auxiliary measurement for wind direction, failed during the 45th sol of the VL1 mission. Additionally, one of the wind sensors of VL1 broke down during sol 378. Regardless of the failures, it was still possible to reconstruct the wind measurement data, because the failed components of the sensors did not prevent the determination of the wind direction and speed, as some of the components of the wind measurement setup remained intact for the complete mission. This article concentrates on presenting the wind reconstruction algorithm and methods for validating the operation of the algorithm. The algorithm enables the reconstruction of wind measurements for the complete VL1 mission. The amount of available sols is extended from 350 to 2245 sols.

  14. Wind reconstruction algorithm for Viking Lander 1

    Directory of Open Access Journals (Sweden)

    T. Kynkäänniemi

    2017-06-01

    Full Text Available The wind measurement sensors of Viking Lander 1 (VL1 were only fully operational for the first 45 sols of the mission. We have developed an algorithm for reconstructing the wind measurement data after the wind measurement sensor failures. The algorithm for wind reconstruction enables the processing of wind data during the complete VL1 mission. The heater element of the quadrant sensor, which provided auxiliary measurement for wind direction, failed during the 45th sol of the VL1 mission. Additionally, one of the wind sensors of VL1 broke down during sol 378. Regardless of the failures, it was still possible to reconstruct the wind measurement data, because the failed components of the sensors did not prevent the determination of the wind direction and speed, as some of the components of the wind measurement setup remained intact for the complete mission. This article concentrates on presenting the wind reconstruction algorithm and methods for validating the operation of the algorithm. The algorithm enables the reconstruction of wind measurements for the complete VL1 mission. The amount of available sols is extended from 350 to 2245 sols.

  15. Fast half-sibling population reconstruction: theory and algorithms.

    Science.gov (United States)

    Dexter, Daniel; Brown, Daniel G

    2013-07-12

    Kinship inference is the task of identifying genealogically related individuals. Kinship information is important for determining mating structures, notably in endangered populations. Although many solutions exist for reconstructing full sibling relationships, few exist for half-siblings. We consider the problem of determining whether a proposed half-sibling population reconstruction is valid under Mendelian inheritance assumptions. We show that this problem is NP-complete and provide a 0/1 integer program that identifies the minimum number of individuals that must be removed from a population in order for the reconstruction to become valid. We also present SibJoin, a heuristic-based clustering approach based on Mendelian genetics, which is strikingly fast. The software is available at http://github.com/ddexter/SibJoin.git+. Our SibJoin algorithm is reasonably accurate and thousands of times faster than existing algorithms. The heuristic is used to infer a half-sibling structure for a population which was, until recently, too large to evaluate.

  16. Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: comparison of filtered back projection, adaptive statistical iterative reconstruction and model-based iterative reconstruction

    International Nuclear Information System (INIS)

    Choo, Ji Yung; Goo, Jin Mo; Park, Chang Min; Park, Sang Joon; Lee, Chang Hyun; Shim, Mi-Suk

    2014-01-01

    To evaluate filtered back projection (FBP) and two iterative reconstruction (IR) algorithms and their effects on the quantitative analysis of lung parenchyma and airway measurements on computed tomography (CT) images. Low-dose chest CT obtained in 281 adult patients were reconstructed using three algorithms: FBP, adaptive statistical IR (ASIR) and model-based IR (MBIR). Measurements of each dataset were compared: total lung volume, emphysema index (EI), airway measurements of the lumen and wall area as well as average wall thickness. Accuracy of airway measurements of each algorithm was also evaluated using an airway phantom. EI using a threshold of -950 HU was significantly different among the three algorithms in decreasing order of FBP (2.30 %), ASIR (1.49 %) and MBIR (1.20 %) (P < 0.01). Wall thickness was also significantly different among the three algorithms with FBP (2.09 mm) demonstrating thicker walls than ASIR (2.00 mm) and MBIR (1.88 mm) (P < 0.01). Airway phantom analysis revealed that MBIR showed the most accurate value for airway measurements. The three algorithms presented different EIs and wall thicknesses, decreasing in the order of FBP, ASIR and MBIR. Thus, care should be taken in selecting the appropriate IR algorithm on quantitative analysis of the lung. (orig.)

  17. Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: comparison of filtered back projection, adaptive statistical iterative reconstruction and model-based iterative reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Choo, Ji Yung [Seoul National University Medical Research Center, Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul (Korea, Republic of); Korea University Ansan Hospital, Ansan-si, Department of Radiology, Gyeonggi-do (Korea, Republic of); Goo, Jin Mo; Park, Chang Min; Park, Sang Joon [Seoul National University Medical Research Center, Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul (Korea, Republic of); Seoul National University, Cancer Research Institute, Seoul (Korea, Republic of); Lee, Chang Hyun; Shim, Mi-Suk [Seoul National University Medical Research Center, Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul (Korea, Republic of)

    2014-04-15

    To evaluate filtered back projection (FBP) and two iterative reconstruction (IR) algorithms and their effects on the quantitative analysis of lung parenchyma and airway measurements on computed tomography (CT) images. Low-dose chest CT obtained in 281 adult patients were reconstructed using three algorithms: FBP, adaptive statistical IR (ASIR) and model-based IR (MBIR). Measurements of each dataset were compared: total lung volume, emphysema index (EI), airway measurements of the lumen and wall area as well as average wall thickness. Accuracy of airway measurements of each algorithm was also evaluated using an airway phantom. EI using a threshold of -950 HU was significantly different among the three algorithms in decreasing order of FBP (2.30 %), ASIR (1.49 %) and MBIR (1.20 %) (P < 0.01). Wall thickness was also significantly different among the three algorithms with FBP (2.09 mm) demonstrating thicker walls than ASIR (2.00 mm) and MBIR (1.88 mm) (P < 0.01). Airway phantom analysis revealed that MBIR showed the most accurate value for airway measurements. The three algorithms presented different EIs and wall thicknesses, decreasing in the order of FBP, ASIR and MBIR. Thus, care should be taken in selecting the appropriate IR algorithm on quantitative analysis of the lung. (orig.)

  18. Parametric boundary reconstruction algorithm for industrial CT metrology application.

    Science.gov (United States)

    Yin, Zhye; Khare, Kedar; De Man, Bruno

    2009-01-01

    High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly

  19. Parallel CT image reconstruction based on GPUs

    International Nuclear Information System (INIS)

    Flores, Liubov A.; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2014-01-01

    In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data. - Highlights: • We developed GPU-based iterative algorithm to reconstruct images. • Iterative algorithms are capable to reconstruct images from under sampled set of projections. • The computer cost of the implementation of the developed algorithm is low. • The efficiency of the algorithm increases for the large scale problems

  20. Optimization, evaluation, and comparison of standard algorithms for image reconstruction with the VIP-PET.

    Science.gov (United States)

    Mikhaylova, E; Kolstein, M; De Lorenzo, G; Chmeissani, M

    2014-07-01

    A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm 3 ) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [3] simulation including the expected CdTe and electronic specifics.

  1. Volume reconstruction optimization for tomo-PIV algorithms applied to experimental data

    Science.gov (United States)

    Martins, Fabio J. W. A.; Foucaut, Jean-Marc; Thomas, Lionel; Azevedo, Luis F. A.; Stanislas, Michel

    2015-08-01

    Tomographic PIV is a three-component volumetric velocity measurement technique based on the tomographic reconstruction of a particle distribution imaged by multiple camera views. In essence, the performance and accuracy of this technique is highly dependent on the parametric adjustment and the reconstruction algorithm used. Although synthetic data have been widely employed to optimize experiments, the resulting reconstructed volumes might not have optimal quality. The purpose of the present study is to offer quality indicators that can be applied to data samples in order to improve the quality of velocity results obtained by the tomo-PIV technique. The methodology proposed can potentially lead to significantly reduction in the time required to optimize a tomo-PIV reconstruction, also leading to better quality velocity results. Tomo-PIV data provided by a six-camera turbulent boundary-layer experiment were used to optimize the reconstruction algorithms according to this methodology. Velocity statistics measurements obtained by optimized BIMART, SMART and MART algorithms were compared with hot-wire anemometer data and velocity measurement uncertainties were computed. Results indicated that BIMART and SMART algorithms produced reconstructed volumes with equivalent quality as the standard MART with the benefit of reduced computational time.

  2. Volume reconstruction optimization for tomo-PIV algorithms applied to experimental data

    International Nuclear Information System (INIS)

    Martins, Fabio J W A; Foucaut, Jean-Marc; Stanislas, Michel; Thomas, Lionel; Azevedo, Luis F A

    2015-01-01

    Tomographic PIV is a three-component volumetric velocity measurement technique based on the tomographic reconstruction of a particle distribution imaged by multiple camera views. In essence, the performance and accuracy of this technique is highly dependent on the parametric adjustment and the reconstruction algorithm used. Although synthetic data have been widely employed to optimize experiments, the resulting reconstructed volumes might not have optimal quality. The purpose of the present study is to offer quality indicators that can be applied to data samples in order to improve the quality of velocity results obtained by the tomo-PIV technique. The methodology proposed can potentially lead to significantly reduction in the time required to optimize a tomo-PIV reconstruction, also leading to better quality velocity results. Tomo-PIV data provided by a six-camera turbulent boundary-layer experiment were used to optimize the reconstruction algorithms according to this methodology. Velocity statistics measurements obtained by optimized BIMART, SMART and MART algorithms were compared with hot-wire anemometer data and velocity measurement uncertainties were computed. Results indicated that BIMART and SMART algorithms produced reconstructed volumes with equivalent quality as the standard MART with the benefit of reduced computational time. (paper)

  3. A sparsity-based iterative algorithm for reconstruction of micro-CT images from highly undersampled projection datasets obtained with a synchrotron X-ray source

    Science.gov (United States)

    Melli, S. Ali; Wahid, Khan A.; Babyn, Paul; Cooper, David M. L.; Gopi, Varun P.

    2016-12-01

    Synchrotron X-ray Micro Computed Tomography (Micro-CT) is an imaging technique which is increasingly used for non-invasive in vivo preclinical imaging. However, it often requires a large number of projections from many different angles to reconstruct high-quality images leading to significantly high radiation doses and long scan times. To utilize this imaging technique further for in vivo imaging, we need to design reconstruction algorithms that reduce the radiation dose and scan time without reduction of reconstructed image quality. This research is focused on using a combination of gradient-based Douglas-Rachford splitting and discrete wavelet packet shrinkage image denoising methods to design an algorithm for reconstruction of large-scale reduced-view synchrotron Micro-CT images with acceptable quality metrics. These quality metrics are computed by comparing the reconstructed images with a high-dose reference image reconstructed from 1800 equally spaced projections spanning 180°. Visual and quantitative-based performance assessment of a synthetic head phantom and a femoral cortical bone sample imaged in the biomedical imaging and therapy bending magnet beamline at the Canadian Light Source demonstrates that the proposed algorithm is superior to the existing reconstruction algorithms. Using the proposed reconstruction algorithm to reduce the number of projections in synchrotron Micro-CT is an effective way to reduce the overall radiation dose and scan time which improves in vivo imaging protocols.

  4. Inverse Monte Carlo: a unified reconstruction algorithm for SPECT

    International Nuclear Information System (INIS)

    Floyd, C.E.; Coleman, R.E.; Jaszczak, R.J.

    1985-01-01

    Inverse Monte Carlo (IMOC) is presented as a unified reconstruction algorithm for Emission Computed Tomography (ECT) providing simultaneous compensation for scatter, attenuation, and the variation of collimator resolution with depth. The technique of inverse Monte Carlo is used to find an inverse solution to the photon transport equation (an integral equation for photon flux from a specified source) for a parameterized source and specific boundary conditions. The system of linear equations so formed is solved to yield the source activity distribution for a set of acquired projections. For the studies presented here, the equations are solved using the EM (Maximum Likelihood) algorithm although other solution algorithms, such as Least Squares, could be employed. While the present results specifically consider the reconstruction of camera-based Single Photon Emission Computed Tomographic (SPECT) images, the technique is equally valid for Positron Emission Tomography (PET) if a Monte Carlo model of such a system is used. As a preliminary evaluation, experimentally acquired SPECT phantom studies for imaging Tc-99m (140 keV) are presented which demonstrate the quantitative compensation for scatter and attenuation for a two dimensional (single slice) reconstruction. The algorithm may be expanded in a straight forward manner to full three dimensional reconstruction including compensation for out of plane scatter

  5. Research on Image Reconstruction Algorithms for Tuber Electrical Resistance Tomography System

    Directory of Open Access Journals (Sweden)

    Jiang Zili

    2016-01-01

    Full Text Available The application of electrical resistance tomography (ERT technology has been expanded to the field of agriculture, and the concept of TERT (Tuber Electrical Resistance Tomography is proposed. On the basis of the research on the forward and the inverse problems of the TERT system, a hybrid algorithm based on genetic algorithm is proposed, which can be used in TERT system to monitor the growth status of the plant tubers. The image reconstruction of TERT system is different from the conventional ERT system for two phase-flow measurement. Imaging of TERT needs more precision measurement and the conventional ERT cares more about the image reconstruction speed. A variety of algorithms are analyzed and optimized for the purpose of making them suitable for TERT system. For example: linear back projection, modified Newton-Raphson and genetic algorithm. Experimental results showed that the novel hybrid algorithm is superior to other algorithm and it can effectively improve the image reconstruction quality.

  6. A New Track Reconstruction Algorithm suitable for Parallel Processing based on Hit Triplets and Broken Lines

    Directory of Open Access Journals (Sweden)

    Schöning André

    2016-01-01

    Full Text Available Track reconstruction in high track multiplicity environments at current and future high rate particle physics experiments is a big challenge and very time consuming. The search for track seeds and the fitting of track candidates are usually the most time consuming steps in the track reconstruction. Here, a new and fast track reconstruction method based on hit triplets is proposed which exploits a three-dimensional fit model including multiple scattering and hit uncertainties from the very start, including the search for track seeds. The hit triplet based reconstruction method assumes a homogeneous magnetic field which allows to give an analytical solutions for the triplet fit result. This method is highly parallelizable, needs fewer operations than other standard track reconstruction methods and is therefore ideal for the implementation on parallel computing architectures. The proposed track reconstruction algorithm has been studied in the context of the Mu3e-experiment and a typical LHC experiment.

  7. FPGA Hardware Acceleration of a Phylogenetic Tree Reconstruction with Maximum Parsimony Algorithm

    OpenAIRE

    BLOCK, Henry; MARUYAMA, Tsutomu

    2017-01-01

    In this paper, we present an FPGA hardware implementation for a phylogenetic tree reconstruction with a maximum parsimony algorithm. We base our approach on a particular stochastic local search algorithm that uses the Progressive Neighborhood and the Indirect Calculation of Tree Lengths method. This method is widely used for the acceleration of the phylogenetic tree reconstruction algorithm in software. In our implementation, we define a tree structure and accelerate the search by parallel an...

  8. A low-count reconstruction algorithm for Compton-based prompt gamma imaging

    Science.gov (United States)

    Huang, Hsuan-Ming; Liu, Chih-Chieh; Jan, Meei-Ling; Lee, Ming-Wei

    2018-04-01

    The Compton camera is an imaging device which has been proposed to detect prompt gammas (PGs) produced by proton–nuclear interactions within tissue during proton beam irradiation. Compton-based PG imaging has been developed to verify proton ranges because PG rays, particularly characteristic ones, have strong correlations with the distribution of the proton dose. However, accurate image reconstruction from characteristic PGs is challenging because the detector efficiency and resolution are generally low. Our previous study showed that point spread functions can be incorporated into the reconstruction process to improve image resolution. In this study, we proposed a low-count reconstruction algorithm to improve the image quality of a characteristic PG emission by pooling information from other characteristic PG emissions. PGs were simulated from a proton beam irradiated on a water phantom, and a two-stage Compton camera was used for PG detection. The results show that the image quality of the reconstructed characteristic PG emission is improved with our proposed method in contrast to the standard reconstruction method using events from only one characteristic PG emission. For the 4.44 MeV PG rays, both methods can be used to predict the positions of the peak and the distal falloff with a mean accuracy of 2 mm. Moreover, only the proposed method can improve the estimated positions of the peak and the distal falloff of 5.25 MeV PG rays, and a mean accuracy of 2 mm can be reached.

  9. Quantitative tomography simulations and reconstruction algorithms

    International Nuclear Information System (INIS)

    Martz, H.E.; Aufderheide, M.B.; Goodman, D.; Schach von Wittenau, A.; Logan, C.; Hall, J.; Jackson, J.; Slone, D.

    2000-01-01

    X-ray, neutron and proton transmission radiography and computed tomography (CT) are important diagnostic tools that are at the heart of LLNL's effort to meet the goals of the DOE's Advanced Radiography Campaign. This campaign seeks to improve radiographic simulation and analysis so that radiography can be a useful quantitative diagnostic tool for stockpile stewardship. Current radiographic accuracy does not allow satisfactory separation of experimental effects from the true features of an object's tomographically reconstructed image. This can lead to difficult and sometimes incorrect interpretation of the results. By improving our ability to simulate the whole radiographic and CT system, it will be possible to examine the contribution of system components to various experimental effects, with the goal of removing or reducing them. In this project, we are merging this simulation capability with a maximum-likelihood (constrained-conjugate-gradient-CCG) reconstruction technique yielding a physics-based, forward-model image-reconstruction code. In addition, we seek to improve the accuracy of computed tomography from transmission radiographs by studying what physics is needed in the forward model. During FY 2000, an improved version of the LLNL ray-tracing code called HADES has been coupled with a recently developed LLNL CT algorithm known as CCG. The problem of image reconstruction is expressed as a large matrix equation relating a model for the object being reconstructed to its projections (radiographs). Using a constrained-conjugate-gradient search algorithm, a maximum likelihood solution is sought. This search continues until the difference between the input measured radiographs or projections and the simulated or calculated projections is satisfactorily small

  10. Preconditioned alternating projection algorithms for maximum a posteriori ECT reconstruction

    International Nuclear Information System (INIS)

    Krol, Andrzej; Li, Si; Shen, Lixin; Xu, Yuesheng

    2012-01-01

    We propose a preconditioned alternating projection algorithm (PAPA) for solving the maximum a posteriori (MAP) emission computed tomography (ECT) reconstruction problem. Specifically, we formulate the reconstruction problem as a constrained convex optimization problem with the total variation (TV) regularization. We then characterize the solution of the constrained convex optimization problem and show that it satisfies a system of fixed-point equations defined in terms of two proximity operators raised from the convex functions that define the TV-norm and the constraint involved in the problem. The characterization (of the solution) via the proximity operators that define two projection operators naturally leads to an alternating projection algorithm for finding the solution. For efficient numerical computation, we introduce to the alternating projection algorithm a preconditioning matrix (the EM-preconditioner) for the dense system matrix involved in the optimization problem. We prove theoretically convergence of the PAPA. In numerical experiments, performance of our algorithms, with an appropriately selected preconditioning matrix, is compared with performance of the conventional MAP expectation-maximization (MAP-EM) algorithm with TV regularizer (EM-TV) and that of the recently developed nested EM-TV algorithm for ECT reconstruction. Based on the numerical experiments performed in this work, we observe that the alternating projection algorithm with the EM-preconditioner outperforms significantly the EM-TV in all aspects including the convergence speed, the noise in the reconstructed images and the image quality. It also outperforms the nested EM-TV in the convergence speed while providing comparable image quality. (paper)

  11. A very fast implementation of 2D iterative reconstruction algorithms

    DEFF Research Database (Denmark)

    Toft, Peter Aundal; Jensen, Peter James

    1996-01-01

    that iterative reconstruction algorithms can be implemented and run almost as fast as direct reconstruction algorithms. The method has been implemented in a software package that is available for free, providing reconstruction algorithms using ART, EM, and the Least Squares Conjugate Gradient Method...

  12. Angle Statistics Reconstruction: a robust reconstruction algorithm for Muon Scattering Tomography

    Science.gov (United States)

    Stapleton, M.; Burns, J.; Quillin, S.; Steer, C.

    2014-11-01

    Muon Scattering Tomography (MST) is a technique for using the scattering of cosmic ray muons to probe the contents of enclosed volumes. As a muon passes through material it undergoes multiple Coulomb scattering, where the amount of scattering is dependent on the density and atomic number of the material as well as the path length. Hence, MST has been proposed as a means of imaging dense materials, for instance to detect special nuclear material in cargo containers. Algorithms are required to generate an accurate reconstruction of the material density inside the volume from the muon scattering information and some have already been proposed, most notably the Point of Closest Approach (PoCA) and Maximum Likelihood/Expectation Maximisation (MLEM) algorithms. However, whilst PoCA-based algorithms are easy to implement, they perform rather poorly in practice. Conversely, MLEM is a complicated algorithm to implement and computationally intensive and there is currently no published, fast and easily-implementable algorithm that performs well in practice. In this paper, we first provide a detailed analysis of the source of inaccuracy in PoCA-based algorithms. We then motivate an alternative method, based on ideas first laid out by Morris et al, presenting and fully specifying an algorithm that performs well against simulations of realistic scenarios. We argue this new algorithm should be adopted by developers of Muon Scattering Tomography as an alternative to PoCA.

  13. Optimization of reconstruction algorithms using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Hanson, K.M.

    1989-01-01

    A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by a iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a nonnegativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. 11 refs., 6 figs., 2 tabs

  14. Optimization of reconstruction algorithms using Monte Carlo simulation

    International Nuclear Information System (INIS)

    Hanson, K.M.

    1989-01-01

    A method for optimizing reconstruction algorithms is presented that is based on how well a specified task can be performed using the reconstructed images. Task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, reconstruction, and performance of the stated task based on the final image. The use of this method is demonstrated through the optimization of the Algebraic Reconstruction Technique (ART), which reconstructs images from their projections by an iterative procedure. The optimization is accomplished by varying the relaxation factor employed in the updating procedure. In some of the imaging situations studied, it is found that the optimization of constrained ART, in which a non-negativity constraint is invoked, can vastly increase the detectability of objects. There is little improvement attained for unconstrained ART. The general method presented may be applied to the problem of designing neutron-diffraction spectrometers. (author)

  15. Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA).

    Science.gov (United States)

    Muckley, Matthew J; Noll, Douglas C; Fessler, Jeffrey A

    2015-02-01

    Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms.

  16. Interval-based reconstruction for uncertainty quantification in PET

    Science.gov (United States)

    Kucharczak, Florentin; Loquin, Kevin; Buvat, Irène; Strauss, Olivier; Mariano-Goulart, Denis

    2018-02-01

    A new directed interval-based tomographic reconstruction algorithm, called non-additive interval based expectation maximization (NIBEM) is presented. It uses non-additive modeling of the forward operator that provides intervals instead of single-valued projections. The detailed approach is an extension of the maximum likelihood—expectation maximization algorithm based on intervals. The main motivation for this extension is that the resulting intervals have appealing properties for estimating the statistical uncertainty associated with the reconstructed activity values. After reviewing previously published theoretical concepts related to interval-based projectors, this paper describes the NIBEM algorithm and gives examples that highlight the properties and advantages of this interval valued reconstruction.

  17. Linear array implementation of the EM algorithm for PET image reconstruction

    International Nuclear Information System (INIS)

    Rajan, K.; Patnaik, L.M.; Ramakrishna, J.

    1995-01-01

    The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution back projection algorithms. However, the PET image reconstruction based on the EM algorithm is computationally burdensome for today's single processor systems. In addition, a large memory is required for the storage of the image, projection data, and the probability matrix. Since the computations are easily divided into tasks executable in parallel, multiprocessor configurations are the ideal choice for fast execution of the EM algorithms. In tis study, the authors attempt to overcome these two problems by parallelizing the EM algorithm on a multiprocessor systems. The parallel EM algorithm on a linear array topology using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PE's) has been implemented. The performance of the EM algorithm on a 386/387 machine, IBM 6000 RISC workstation, and on the linear array system is discussed and compared. The results show that the computational speed performance of a linear array using 8 DSP chips as PE's executing the EM image reconstruction algorithm is about 15.5 times better than that of the IBM 6000 RISC workstation. The novelty of the scheme is its simplicity. The linear array topology is expandable with a larger number of PE's. The architecture is not dependant on the DSP chip chosen, and the substitution of the latest DSP chip is straightforward and could yield better speed performance

  18. Incomplete projection reconstruction of computed tomography based on the modified discrete algebraic reconstruction technique

    Science.gov (United States)

    Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Gao, Zongzhao; Yang, YaFei

    2018-02-01

    Based on the discrete algebraic reconstruction technique (DART), this study aims to address and test a new improved algorithm applied to incomplete projection data to generate a high quality reconstruction image by reducing the artifacts and noise in computed tomography. For the incomplete projections, an augmented Lagrangian based on compressed sensing is first used in the initial reconstruction for segmentation of the DART to get higher contrast graphics for boundary and non-boundary pixels. Then, the block matching 3D filtering operator was used to suppress the noise and to improve the gray distribution of the reconstructed image. Finally, simulation studies on the polychromatic spectrum were performed to test the performance of the new algorithm. Study results show a significant improvement in the signal-to-noise ratios (SNRs) and average gradients (AGs) of the images reconstructed from incomplete data. The SNRs and AGs of the new images reconstructed by DART-ALBM were on average 30%-40% and 10% higher than the images reconstructed by DART algorithms. Since the improved DART-ALBM algorithm has a better robustness to limited-view reconstruction, which not only makes the edge of the image clear but also makes the gray distribution of non-boundary pixels better, it has the potential to improve image quality from incomplete projections or sparse projections.

  19. A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT

    International Nuclear Information System (INIS)

    Cho, Seungryong; Xia, Dan; Pellizzari, Charles A.; Pan Xiaochuan

    2010-01-01

    Purpose: Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation. Methods: The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack-Noo-formula-based filteredbackprojection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step. Results: The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts. Conclusions: They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories.

  20. A new algorithm for 3D reconstruction from support functions

    DEFF Research Database (Denmark)

    Gardner, Richard; Kiderlen, Markus

    2009-01-01

    We introduce a new algorithm for reconstructing an unknown shape from a finite number of noisy measurements of its support function. The algorithm, based on a least squares procedure, is very easy to program in standard software such as Matlab and allows, for the first time, good 3D reconstructio...

  1. Multifractal signal reconstruction based on singularity power spectrum

    International Nuclear Information System (INIS)

    Xiong, Gang; Yu, Wenxian; Xia, Wenxiang; Zhang, Shuning

    2016-01-01

    Highlights: • We propose a novel multifractal reconstruction method based on singularity power spectrum analysis (MFR-SPS). • The proposed MFR-SPS method has better power characteristic than the algorithm in Fraclab. • Further, the SPS-ISE algorithm performs better than the SPS-MFS algorithm. • Based on the proposed MFR-SPS method, we can restructure singularity white fractal noise (SWFN) and linear singularity modulation (LSM) multifractal signal, in equivalent sense, similar with the linear frequency modulation(LFM) signal and WGN in the Fourier domain. - Abstract: Fractal reconstruction (FR) and multifractal reconstruction (MFR) can be considered as the inverse problem of singularity spectrum analysis, and it is challenging to reconstruct fractal signal in accord with multifractal spectrum (MFS). Due to the multiple solutions of fractal reconstruction, the traditional methods of FR/MFR, such as FBM based method, wavelet based method, random wavelet series, fail to reconstruct fractal signal deterministically, and besides, those methods neglect the power spectral distribution in the singular domain. In this paper, we propose a novel MFR method based singularity power spectrum (SPS). Supposing the consistent uniform covering of multifractal measurement, we control the traditional power law of each scale of wavelet coefficients based on the instantaneous singularity exponents (ISE) or MFS, simultaneously control the singularity power law based on the SPS, and deduce the principle and algorithm of MFR based on SPS. Reconstruction simulation and error analysis of estimated ISE, MFS and SPS show the effectiveness and the improvement of the proposed methods compared to those obtained by the Fraclab package.

  2. Efficient operator splitting algorithm for joint sparsity-regularized SPIRiT-based parallel MR imaging reconstruction.

    Science.gov (United States)

    Duan, Jizhong; Liu, Yu; Jing, Peiguang

    2018-02-01

    Self-consistent parallel imaging (SPIRiT) is an auto-calibrating model for the reconstruction of parallel magnetic resonance imaging, which can be formulated as a regularized SPIRiT problem. The Projection Over Convex Sets (POCS) method was used to solve the formulated regularized SPIRiT problem. However, the quality of the reconstructed image still needs to be improved. Though methods such as NonLinear Conjugate Gradients (NLCG) can achieve higher spatial resolution, these methods always demand very complex computation and converge slowly. In this paper, we propose a new algorithm to solve the formulated Cartesian SPIRiT problem with the JTV and JL1 regularization terms. The proposed algorithm uses the operator splitting (OS) technique to decompose the problem into a gradient problem and a denoising problem with two regularization terms, which is solved by our proposed split Bregman based denoising algorithm, and adopts the Barzilai and Borwein method to update step size. Simulation experiments on two in vivo data sets demonstrate that the proposed algorithm is 1.3 times faster than ADMM for datasets with 8 channels. Especially, our proposal is 2 times faster than ADMM for the dataset with 32 channels. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. A practical exact maximum compatibility algorithm for reconstruction of recent evolutionary history

    OpenAIRE

    Cherry, Joshua L.

    2017-01-01

    Background Maximum compatibility is a method of phylogenetic reconstruction that is seldom applied to molecular sequences. It may be ideal for certain applications, such as reconstructing phylogenies of closely-related bacteria on the basis of whole-genome sequencing. Results Here I present an algorithm that rapidly computes phylogenies according to a compatibility criterion. Although based on solutions to the maximum clique problem, this algorithm deals properly with ambiguities in the data....

  4. Low dose reconstruction algorithm for differential phase contrast imaging.

    Science.gov (United States)

    Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni

    2011-01-01

    Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.

  5. Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET.

    Science.gov (United States)

    Rapisarda, E; Bettinardi, V; Thielemans, K; Gilardi, M C

    2010-07-21

    The interest in positron emission tomography (PET) and particularly in hybrid integrated PET/CT systems has significantly increased in the last few years due to the improved quality of the obtained images. Nevertheless, one of the most important limits of the PET imaging technique is still its poor spatial resolution due to several physical factors originating both at the emission (e.g. positron range, photon non-collinearity) and at detection levels (e.g. scatter inside the scintillating crystals, finite dimensions of the crystals and depth of interaction). To improve the spatial resolution of the images, a possible way consists of measuring the point spread function (PSF) of the system and then accounting for it inside the reconstruction algorithm. In this work, the system response of the GE Discovery STE operating in 3D mode has been characterized by acquiring (22)Na point sources in different positions of the scanner field of view. An image-based model of the PSF was then obtained by fitting asymmetric two-dimensional Gaussians on the (22)Na images reconstructed with small pixel sizes. The PSF was then incorporated, at the image level, in a three-dimensional ordered subset maximum likelihood expectation maximization (OS-MLEM) reconstruction algorithm. A qualitative and quantitative validation of the algorithm accounting for the PSF has been performed on phantom and clinical data, showing improved spatial resolution, higher contrast and lower noise compared with the corresponding images obtained using the standard OS-MLEM algorithm.

  6. Comparison of phase unwrapping algorithms for topography reconstruction based on digital speckle pattern interferometry

    Science.gov (United States)

    Li, Yuanbo; Cui, Xiaoqian; Wang, Hongbei; Zhao, Mengge; Ding, Hongbin

    2017-10-01

    Digital speckle pattern interferometry (DSPI) can diagnose the topography evolution in real-time, continuous and non-destructive, and has been considered as a most promising technique for Plasma-Facing Components (PFCs) topography diagnostic under the complicated environment of tokamak. It is important for the study of digital speckle pattern interferometry to enhance speckle patterns and obtain the real topography of the ablated crater. In this paper, two kinds of numerical model based on flood-fill algorithm has been developed to obtain the real profile by unwrapping from the wrapped phase in speckle interference pattern, which can be calculated through four intensity images by means of 4-step phase-shifting technique. During the process of phase unwrapping by means of flood-fill algorithm, since the existence of noise pollution, and other inevitable factors will lead to poor quality of the reconstruction results, this will have an impact on the authenticity of the restored topography. The calculation of the quality parameters was introduced to obtain the quality-map from the wrapped phase map, this work presents two different methods to calculate the quality parameters. Then quality parameters are used to guide the path of flood-fill algorithm, and the pixels with good quality parameters are given priority calculation, so that the quality of speckle interference pattern reconstruction results are improved. According to the comparison between the flood-fill algorithm which is suitable for speckle pattern interferometry and the quality-guided flood-fill algorithm (with two different calculation approaches), the errors which caused by noise pollution and the discontinuous of the strips were successfully reduced.

  7. Microstructure Reconstruction of Sheet Molding Composite Using a Random Chips Packing Algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Tianyu; Xu, Hongyi; Chen, Wei

    2017-04-06

    Fiber-reinforced polymer composites are strong candidates for structural materials to replace steel and light alloys in lightweight vehicle design because of their low density and relatively high strength. In the integrated computational materials engineering (ICME) development of carbon fiber composites, microstructure reconstruction algorithms are needed to generate material microstructure representative volume element (RVE) based on the material processing information. The microstructure RVE reconstruction enables the material property prediction by finite element analysis (FEA)This paper presents an algorithm to reconstruct the microstructure of a chopped carbon fiber/epoxy laminate material system produced by compression molding, normally known as sheet molding compounds (SMC). The algorithm takes the result from material’s manufacturing process as inputs, such as the orientation tensor of fibers, the chopped fiber sheet geometry, and the fiber volume fraction. The chopped fiber sheets are treated as deformable rectangle chips and a random packing algorithm is developed to pack these chips into a square plate. The RVE is built in a layer-by-layer fashion until the desired number of lamina is reached, then a fine tuning process is applied to finalize the reconstruction. Compared to the previous methods, this new approach has the ability to model bended fibers by allowing limited amount of overlaps of rectangle chips. Furthermore, the method does not need SMC microstructure images, for which the image-based characterization techniques have not been mature enough, as inputs. Case studies are performed and the results show that the statistics of the reconstructed microstructures generated by the algorithm matches well with the target input parameters from processing.

  8. Comparison of the effects of model-based iterative reconstruction and filtered back projection algorithms on software measurements in pulmonary subsolid nodules.

    Science.gov (United States)

    Cohen, Julien G; Kim, Hyungjin; Park, Su Bin; van Ginneken, Bram; Ferretti, Gilbert R; Lee, Chang Hyun; Goo, Jin Mo; Park, Chang Min

    2017-08-01

    To evaluate the differences between filtered back projection (FBP) and model-based iterative reconstruction (MBIR) algorithms on semi-automatic measurements in subsolid nodules (SSNs). Unenhanced CT scans of 73 SSNs obtained using the same protocol and reconstructed with both FBP and MBIR algorithms were evaluated by two radiologists. Diameter, mean attenuation, mass and volume of whole nodules and their solid components were measured. Intra- and interobserver variability and differences between FBP and MBIR were then evaluated using Bland-Altman method and Wilcoxon tests. Longest diameter, volume and mass of nodules and those of their solid components were significantly higher using MBIR (p algorithms with respect to the diameter, volume and mass of nodules and their solid components. There were no significant differences in intra- or interobserver variability between FBP and MBIR (p > 0.05). Semi-automatic measurements of SSNs significantly differed between FBP and MBIR; however, the differences were within the range of measurement variability. • Intra- and interobserver reproducibility of measurements did not differ between FBP and MBIR. • Differences in SSNs' semi-automatic measurement induced by reconstruction algorithms were not clinically significant. • Semi-automatic measurement may be conducted regardless of reconstruction algorithm. • SSNs' semi-automated classification agreement (pure vs. part-solid) did not significantly differ between algorithms.

  9. An improved cone-beam filtered backprojection reconstruction algorithm based on x-ray angular correction and multiresolution analysis

    International Nuclear Information System (INIS)

    Sun, Y.; Hou, Y.; Yan, Y.

    2004-01-01

    With the extensive application of industrial computed tomography in the field of non-destructive testing, how to improve the quality of the reconstructed image is receiving more and more concern. It is well known that in the existing cone-beam filtered backprojection reconstruction algorithms the cone angle is controlled within a narrow range. The reason of this limitation is the incompleteness of projection data when the cone angle increases. Thus the size of the tested workpiece is limited. Considering the characteristic of X-ray cone angle, an improved cone-beam filtered back-projection reconstruction algorithm taking account of angular correction is proposed in this paper. The aim of our algorithm is to correct the cone-angle effect resulted from the incompleteness of projection data in the conventional algorithm. The basis of the correction is the angular relationship among X-ray source, tested workpiece and the detector. Thus the cone angle is not strictly limited and this algorithm may be used to detect larger workpiece. Further more, adaptive wavelet filter is used to make multiresolution analysis, which can modify the wavelet decomposition series adaptively according to the demand for resolution of local reconstructed area. Therefore the computation and the time of reconstruction can be reduced, and the quality of the reconstructed image can also be improved. (author)

  10. Parameter selection in limited data cone-beam CT reconstruction using edge-preserving total variation algorithms

    Science.gov (United States)

    Lohvithee, Manasavee; Biguri, Ander; Soleimani, Manuchehr

    2017-12-01

    There are a number of powerful total variation (TV) regularization methods that have great promise in limited data cone-beam CT reconstruction with an enhancement of image quality. These promising TV methods require careful selection of the image reconstruction parameters, for which there are no well-established criteria. This paper presents a comprehensive evaluation of parameter selection in a number of major TV-based reconstruction algorithms. An appropriate way of selecting the values for each individual parameter has been suggested. Finally, a new adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm is presented, which implements the edge-preserving function for CBCT reconstruction with limited data. The proposed algorithm shows significant robustness compared to three other existing algorithms: ASD-POCS, AwASD-POCS and PCSD. The proposed AwPCSD algorithm is able to preserve the edges of the reconstructed images better with fewer sensitive parameters to tune.

  11. Optimization of image quality and acquisition time for lab-based X-ray microtomography using an iterative reconstruction algorithm

    Science.gov (United States)

    Lin, Qingyang; Andrew, Matthew; Thompson, William; Blunt, Martin J.; Bijeljic, Branko

    2018-05-01

    Non-invasive laboratory-based X-ray microtomography has been widely applied in many industrial and research disciplines. However, the main barrier to the use of laboratory systems compared to a synchrotron beamline is its much longer image acquisition time (hours per scan compared to seconds to minutes at a synchrotron), which results in limited application for dynamic in situ processes. Therefore, the majority of existing laboratory X-ray microtomography is limited to static imaging; relatively fast imaging (tens of minutes per scan) can only be achieved by sacrificing imaging quality, e.g. reducing exposure time or number of projections. To alleviate this barrier, we introduce an optimized implementation of a well-known iterative reconstruction algorithm that allows users to reconstruct tomographic images with reasonable image quality, but requires lower X-ray signal counts and fewer projections than conventional methods. Quantitative analysis and comparison between the iterative and the conventional filtered back-projection reconstruction algorithm was performed using a sandstone rock sample with and without liquid phases in the pore space. Overall, by implementing the iterative reconstruction algorithm, the required image acquisition time for samples such as this, with sparse object structure, can be reduced by a factor of up to 4 without measurable loss of sharpness or signal to noise ratio.

  12. Optimising Aesthetic Reconstruction of Scalp Soft Tissue by an Algorithm Based on Defect Size and Location.

    Science.gov (United States)

    Ooi, Adrian Sh; Kanapathy, Muholan; Ong, Yee Siang; Tan, Kok Chai; Tan, Bien Keem

    2015-11-01

    Scalp soft tissue defects are common and result from a variety of causes. Reconstructive methods should maximise cosmetic outcomes by maintaining hair-bearing tissue and aesthetic hairlines. This article outlines an algorithm based on a diverse clinical case series to optimise scalp soft tissue coverage. A retrospective analysis of scalp soft tissue reconstruction cases performed at the Singapore General Hospital between January 2004 and December 2013 was conducted. Forty-one patients were included in this study. The majority of defects aesthetic outcome while minimising complications and repeat procedures.

  13. Iterative reconstruction of transcriptional regulatory networks: an algorithmic approach.

    Directory of Open Access Journals (Sweden)

    Christian L Barrett

    2006-05-01

    Full Text Available The number of complete, publicly available genome sequences is now greater than 200, and this number is expected to rapidly grow in the near future as metagenomic and environmental sequencing efforts escalate and the cost of sequencing drops. In order to make use of this data for understanding particular organisms and for discerning general principles about how organisms function, it will be necessary to reconstruct their various biochemical reaction networks. Principal among these will be transcriptional regulatory networks. Given the physical and logical complexity of these networks, the various sources of (often noisy data that can be utilized for their elucidation, the monetary costs involved, and the huge number of potential experiments approximately 10(12 that can be performed, experiment design algorithms will be necessary for synthesizing the various computational and experimental data to maximize the efficiency of regulatory network reconstruction. This paper presents an algorithm for experimental design to systematically and efficiently reconstruct transcriptional regulatory networks. It is meant to be applied iteratively in conjunction with an experimental laboratory component. The algorithm is presented here in the context of reconstructing transcriptional regulation for metabolism in Escherichia coli, and, through a retrospective analysis with previously performed experiments, we show that the produced experiment designs conform to how a human would design experiments. The algorithm is able to utilize probability estimates based on a wide range of computational and experimental sources to suggest experiments with the highest potential of discovering the greatest amount of new regulatory knowledge.

  14. Level-set reconstruction algorithm for ultrafast limited-angle X-ray computed tomography of two-phase flows.

    Science.gov (United States)

    Bieberle, M; Hampel, U

    2015-06-13

    Tomographic image reconstruction is based on recovering an object distribution from its projections, which have been acquired from all angular views around the object. If the angular range is limited to less than 180° of parallel projections, typical reconstruction artefacts arise when using standard algorithms. To compensate for this, specialized algorithms using a priori information about the object need to be applied. The application behind this work is ultrafast limited-angle X-ray computed tomography of two-phase flows. Here, only a binary distribution of the two phases needs to be reconstructed, which reduces the complexity of the inverse problem. To solve it, a new reconstruction algorithm (LSR) based on the level-set method is proposed. It includes one force function term accounting for matching the projection data and one incorporating a curvature-dependent smoothing of the phase boundary. The algorithm has been validated using simulated as well as measured projections of known structures, and its performance has been compared to the algebraic reconstruction technique and a binary derivative of it. The validation as well as the application of the level-set reconstruction on a dynamic two-phase flow demonstrated its applicability and its advantages over other reconstruction algorithms. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  15. Comparison study of reconstruction algorithms for prototype digital breast tomosynthesis using various breast phantoms.

    Science.gov (United States)

    Kim, Ye-seul; Park, Hye-suk; Lee, Haeng-Hwa; Choi, Young-Wook; Choi, Jae-Gu; Kim, Hak Hee; Kim, Hee-Joung

    2016-02-01

    Digital breast tomosynthesis (DBT) is a recently developed system for three-dimensional imaging that offers the potential to reduce the false positives of mammography by preventing tissue overlap. Many qualitative evaluations of digital breast tomosynthesis were previously performed by using a phantom with an unrealistic model and with heterogeneous background and noise, which is not representative of real breasts. The purpose of the present work was to compare reconstruction algorithms for DBT by using various breast phantoms; validation was also performed by using patient images. DBT was performed by using a prototype unit that was optimized for very low exposures and rapid readout. Three algorithms were compared: a back-projection (BP) algorithm, a filtered BP (FBP) algorithm, and an iterative expectation maximization (EM) algorithm. To compare the algorithms, three types of breast phantoms (homogeneous background phantom, heterogeneous background phantom, and anthropomorphic breast phantom) were evaluated, and clinical images were also reconstructed by using the different reconstruction algorithms. The in-plane image quality was evaluated based on the line profile and the contrast-to-noise ratio (CNR), and out-of-plane artifacts were evaluated by means of the artifact spread function (ASF). Parenchymal texture features of contrast and homogeneity were computed based on reconstructed images of an anthropomorphic breast phantom. The clinical images were studied to validate the effect of reconstruction algorithms. The results showed that the CNRs of masses reconstructed by using the EM algorithm were slightly higher than those obtained by using the BP algorithm, whereas the FBP algorithm yielded much lower CNR due to its high fluctuations of background noise. The FBP algorithm provides the best conspicuity for larger calcifications by enhancing their contrast and sharpness more than the other algorithms; however, in the case of small-size and low

  16. Parallelization of the model-based iterative reconstruction algorithm DIRA

    International Nuclear Information System (INIS)

    Oertenberg, A.; Sandborg, M.; Alm Carlsson, G.; Malusek, A.; Magnusson, M.

    2016-01-01

    New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelization of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelization of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelized using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelization of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelization with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained. (authors)

  17. Image-reconstruction algorithms for positron-emission tomography systems

    International Nuclear Information System (INIS)

    Cheng, S.N.C.

    1982-01-01

    The positional uncertainty in the time-of-flight measurement of a positron-emission tomography system is modelled as a Gaussian distributed random variable and the image is assumed to be piecewise constant on a rectilinear lattice. A reconstruction algorithm using maximum-likelihood estimation is derived for the situation in which time-of-flight data are sorted as the most-likely-position array. The algorithm is formulated as a linear system described by a nonseparable, block-banded, Toeplitz matrix, and a sine-transform technique is used to implement this algorithm efficiently. The reconstruction algorithms for both the most-likely-position array and the confidence-weighted array are described by similar equations, hence similar linear systems can be used to described the reconstruction algorithm for a discrete, confidence-weighted array, when the matrix and the entries in the data array are properly identified. It is found that the mean square-error depends on the ratio of the full width at half the maximum of time-of-flight measurement over the size of a pixel. When other parameters are fixed, the larger the pixel size, the smaller is the mean square-error. In the study of resolution, parameters that affect the impulse response of time-of-flight reconstruction algorithms are identified. It is found that the larger the pixel size, the larger is the standard deviation of the impulse response. This shows that small mean square-error and fine resolution are two contradictory requirements

  18. Comparison of different reconstruction algorithms for three-dimensional ultrasound imaging in a neurosurgical setting.

    Science.gov (United States)

    Miller, D; Lippert, C; Vollmer, F; Bozinov, O; Benes, L; Schulte, D M; Sure, U

    2012-09-01

    Freehand three-dimensional ultrasound imaging (3D-US) is increasingly used in image-guided surgery. During image acquisition, a set of B-scans is acquired that is distributed in a non-parallel manner over the area of interest. Reconstructing these images into a regular array allows 3D visualization. However, the reconstruction process may introduce artefacts and may therefore reduce image quality. The aim of the study is to compare different algorithms with respect to image quality and diagnostic value for image guidance in neurosurgery. 3D-US data sets were acquired during surgery of various intracerebral lesions using an integrated ultrasound-navigation device. They were stored for post-hoc evaluation. Five different reconstruction algorithms, a standard multiplanar reconstruction with interpolation (MPR), a pixel nearest neighbour method (PNN), a voxel nearest neighbour method (VNN) and two voxel based distance-weighted algorithms (VNN2 and DW) were tested with respect to image quality and artefact formation. The capability of the algorithm to fill gaps within the sample volume was investigated and a clinical evaluation with respect to the diagnostic value of the reconstructed images was performed. MPR was significantly worse than the other algorithms in filling gaps. In an image subtraction test, VNN2 and DW reliably reconstructed images even if large amounts of data were missing. However, the quality of the reconstruction improved, if data acquisition was performed in a structured manner. When evaluating the diagnostic value of reconstructed axial, sagittal and coronal views, VNN2 and DW were judged to be significantly better than MPR and VNN. VNN2 and DW could be identified as robust algorithms that generate reconstructed US images with a high diagnostic value. These algorithms improve the utility and reliability of 3D-US imaging during intraoperative navigation. Copyright © 2012 John Wiley & Sons, Ltd.

  19. 3D dictionary learning based iterative cone beam CT reconstruction

    Directory of Open Access Journals (Sweden)

    Ti Bai

    2014-03-01

    Full Text Available Purpose: This work is to develop a 3D dictionary learning based cone beam CT (CBCT reconstruction algorithm on graphic processing units (GPU to improve the quality of sparse-view CBCT reconstruction with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms of 3 × 3 × 3 was trained from a large number of blocks extracted from a high quality volume image. On the basis, we utilized cholesky decomposition based orthogonal matching pursuit algorithm to find the sparse representation of each block. To accelerate the time-consuming sparse coding in the 3D case, we implemented the sparse coding in a parallel fashion by taking advantage of the tremendous computational power of GPU. Conjugate gradient least square algorithm was adopted to minimize the data fidelity term. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with tight frame (TF by performing reconstructions on a subset data of 121 projections. Results: Compared to TF based CBCT reconstruction that shows good overall performance, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, remove more streaking artifacts and also induce less blocky artifacts. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppress the noise, and hence to achieve high quality reconstruction under the case of sparse view. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential clinical application.-------------------------------Cite this article as: Bai T, Yan H, Shi F, Jia X, Lou Y, Xu Q, Jiang S, Mou X. 3D dictionary learning based iterative cone beam CT reconstruction. Int J Cancer Ther Oncol 2014; 2(2:020240. DOI: 10

  20. High-speed computation of the EM algorithm for PET image reconstruction

    International Nuclear Information System (INIS)

    Rajan, K.; Patnaik, L.M.; Ramakrishna, J.

    1994-01-01

    The PET image reconstruction based on the EM algorithm has several attractive advantages over the conventional convolution backprojection algorithms. However, two major drawbacks have impeded the routine use of the EM algorithm, namely, the long computational time due to slow convergence and the large memory required for the storage of the image, projection data and the probability matrix. In this study, the authors attempts to solve these two problems by parallelizing the EM algorithm on a multiprocessor system. The authors have implemented an extended hypercube (EH) architecture for the high-speed computation of the EM algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs). The authors discuss and compare the performance of the EM algorithm on a 386/387 machine, CD 4360 mainframe, and on the EH system. The results show that the computational speed performance of an EH using DSP chips as PEs executing the EM image reconstruction algorithm is about 130 times better than that of the CD 4360 mainframe. The EH topology is expandable with more number of PEs

  1. A filtered backprojection reconstruction algorithm for Compton camera

    Energy Technology Data Exchange (ETDEWEB)

    Lojacono, Xavier; Maxim, Voichita; Peyrin, Francoise; Prost, Remy [Lyon Univ., Villeurbanne (France). CNRS, Inserm, INSA-Lyon, CREATIS, UMR5220; Zoglauer, Andreas [California Univ., Berkeley, CA (United States). Space Sciences Lab.

    2011-07-01

    In this paper we present a filtered backprojection reconstruction algorithm for Compton Camera detectors of particles. Compared to iterative methods, widely used for the reconstruction of images from Compton camera data, analytical methods are fast, easy to implement and avoid convergence issues. The method we propose is exact for an idealized Compton camera composed of two parallel plates of infinite dimension. We show that it copes well with low number of detected photons simulated from a realistic device. Images reconstructed from both synthetic data and realistic ones obtained with Monte Carlo simulations demonstrate the efficiency of the algorithm. (orig.)

  2. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

    Directory of Open Access Journals (Sweden)

    Chae Young Lee

    Full Text Available The purposes of this study were to optimize a proton computed tomography system (pCT for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.

  3. Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

    Science.gov (United States)

    Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

    2017-07-01

    In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

  4. A reconstruction algorithms for helical cone-beam SPECT

    International Nuclear Information System (INIS)

    Weng, Y.; Zeng, G.L.; Gullberg, G.T.

    1993-01-01

    Cone-beam SPECT provides improved sensitivity for imaging small organs like the brain and heart. However, current cone-beam tomography with the focal point traversing a planar orbit does not acquire sufficient data to give an accurate reconstruction. In this paper, the authors employ a data-acquisition method which obtains complete data for cone-beam SPECT by simultaneously rotating the gamma camera and translating the patient bed, so that cone-beam projections can be obtained with the focal point traversing a helix surrounding the patient. An implementation of Grangeat's algorithm for helical cone-beam projections is developed. The algorithm requires a rebinning step to convert cone-beam data to parallel-beam data which are then reconstructed using the 3D Radon inversion. A fast new rebinning scheme is developed which uses all of the detected data to reconstruct the image and properly normalizes any multiply scanned data. This algorithm is shown to produce less artifacts than the commonly used Feldkamp algorithm when applied to either a circular planar orbit or a helical orbit acquisition. The algorithm can easily be extended to any arbitrary orbit

  5. Joint-2D-SL0 Algorithm for Joint Sparse Matrix Reconstruction

    Directory of Open Access Journals (Sweden)

    Dong Zhang

    2017-01-01

    Full Text Available Sparse matrix reconstruction has a wide application such as DOA estimation and STAP. However, its performance is usually restricted by the grid mismatch problem. In this paper, we revise the sparse matrix reconstruction model and propose the joint sparse matrix reconstruction model based on one-order Taylor expansion. And it can overcome the grid mismatch problem. Then, we put forward the Joint-2D-SL0 algorithm which can solve the joint sparse matrix reconstruction problem efficiently. Compared with the Kronecker compressive sensing method, our proposed method has a higher computational efficiency and acceptable reconstruction accuracy. Finally, simulation results validate the superiority of the proposed method.

  6. Motion tolerant iterative reconstruction algorithm for cone-beam helical CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu [Hitachi Medical Corporation, Chiba-ken (Japan). CT System Div.

    2011-07-01

    We have developed a new advanced iterative reconstruction algorithm for cone-beam helical CT. The features of this algorithm are: (a) it uses separable paraboloidal surrogate (SPS) technique as a foundation for reconstruction to reduce noise and cone-beam artifact, (b) it uses a view weight in the back-projection process to reduce motion artifact. To confirm the improvement of our proposed algorithm over other existing algorithm, such as Feldkamp-Davis-Kress (FDK) or SPS algorithm, we compared the motion artifact reduction, image noise reduction (standard deviation of CT number), and cone-beam artifact reduction on simulated and clinical data set. Our results demonstrate that the proposed algorithm dramatically reduces motion artifacts compared with the SPS algorithm, and decreases image noise compared with the FDK algorithm. In addition, the proposed algorithm potentially improves time resolution of iterative reconstruction. (orig.)

  7. Study on the algorithm of computational ghost imaging based on discrete fourier transform measurement matrix

    Science.gov (United States)

    Zhang, Leihong; Liang, Dong; Li, Bei; Kang, Yi; Pan, Zilan; Zhang, Dawei; Gao, Xiumin; Ma, Xiuhua

    2016-07-01

    On the basis of analyzing the cosine light field with determined analytic expression and the pseudo-inverse method, the object is illuminated by a presetting light field with a determined discrete Fourier transform measurement matrix, and the object image is reconstructed by the pseudo-inverse method. The analytic expression of the algorithm of computational ghost imaging based on discrete Fourier transform measurement matrix is deduced theoretically, and compared with the algorithm of compressive computational ghost imaging based on random measurement matrix. The reconstruction process and the reconstruction error are analyzed. On this basis, the simulation is done to verify the theoretical analysis. When the sampling measurement number is similar to the number of object pixel, the rank of discrete Fourier transform matrix is the same as the one of the random measurement matrix, the PSNR of the reconstruction image of FGI algorithm and PGI algorithm are similar, the reconstruction error of the traditional CGI algorithm is lower than that of reconstruction image based on FGI algorithm and PGI algorithm. As the decreasing of the number of sampling measurement, the PSNR of reconstruction image based on FGI algorithm decreases slowly, and the PSNR of reconstruction image based on PGI algorithm and CGI algorithm decreases sharply. The reconstruction time of FGI algorithm is lower than that of other algorithms and is not affected by the number of sampling measurement. The FGI algorithm can effectively filter out the random white noise through a low-pass filter and realize the reconstruction denoising which has a higher denoising capability than that of the CGI algorithm. The FGI algorithm can improve the reconstruction accuracy and the reconstruction speed of computational ghost imaging.

  8. New reconstruction algorithm in helical-volume CT

    International Nuclear Information System (INIS)

    Toki, Y.; Rifu, T.; Aradate, H.; Hirao, Y.; Ohyama, N.

    1990-01-01

    This paper reports on helical scanning that is an application of continuous scanning CT to acquire volume data in a short time for three-dimensional study. In a helical scan, the patient couch sustains movement during continuous-rotation scanning and then the acquired data is processed to synthesize a projection data set of vertical section by interpolation. But the synthesized section is not thin enough; also, the image may have artifacts caused by couch movement. A new reconstruction algorithm that helps resolve such problems has been developed and compared with the ordinary algorithm. The authors constructed a helical scan system based on TCT-900S, which can perform 1-second rotation continuously for 30 seconds. The authors measured section thickness using both algorithms on an AAPM phantom, and we also compared degree of artifacts on clinical data

  9. Evaluation of digital breast tomosynthesis reconstruction algorithms using synchrotron radiation in standard geometry

    International Nuclear Information System (INIS)

    Bliznakova, K.; Kolitsi, Z.; Speller, R. D.; Horrocks, J. A.; Tromba, G.; Pallikarakis, N.

    2010-01-01

    Purpose: In this article, the image quality of reconstructed volumes by four algorithms for digital tomosynthesis, applied in the case of breast, is investigated using synchrotron radiation. Methods: An angular data set of 21 images of a complex phantom with heterogeneous tissue-mimicking background was obtained using the SYRMEP beamline at ELETTRA Synchrotron Light Laboratory, Trieste, Italy. The irradiated part was reconstructed using the multiple projection algorithm (MPA) and the filtered backprojection with ramp followed by hamming windows (FBR-RH) and filtered backprojection with ramp (FBP-R). Additionally, an algorithm for reducing the noise in reconstructed planes based on noise mask subtraction from the planes of the originally reconstructed volume using MPA (MPA-NM) has been further developed. The reconstruction techniques were evaluated in terms of calculations and comparison of the contrast-to-noise ratio (CNR) and artifact spread function. Results: It was found that the MPA-NM resulted in higher CNR, comparable with the CNR of FBP-RH for high contrast details. Low contrast objects are well visualized and characterized by high CNR using the simple MPA and the MPA-NM. In addition, the image quality of the reconstructed features in terms of CNR and visual appearance as a function of the initial number of projection images and the reconstruction arc was carried out. Slices reconstructed with more input projection images result in less reconstruction artifacts and higher detail CNR, while those reconstructed from projection images acquired in reduced angular range causes pronounced streak artifacts. Conclusions: Of the reconstruction algorithms implemented, the MPA-NM and MPA are a good choice for detecting low contrast objects, while the FBP-RH, FBP-R, and MPA-NM provide high CNR and well outlined edges in case of microcalcifications.

  10. ADART: an adaptive algebraic reconstruction algorithm for discrete tomography.

    Science.gov (United States)

    Maestre-Deusto, F Javier; Scavello, Giovanni; Pizarro, Joaquín; Galindo, Pedro L

    2011-08-01

    In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.

  11. A fast iterative soft-thresholding algorithm for few-view CT reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Junfeng; Mou, Xuanqin; Zhang, Yanbo [Jiaotong Univ., Xi' an (China). Inst. of Image Processing and Pattern Recognition

    2011-07-01

    Iterative soft-thresholding algorithms with total variation regularization can produce high-quality reconstructions from few views and even in the presence of noise. However, these algorithms are known to converge quite slowly, with a proven theoretically global convergence rate O(1/k), where k is iteration number. In this paper, we present a fast iterative soft-thresholding algorithm for few-view fan beam CT reconstruction with a global convergence rate O(1/k{sup 2}), which is significantly faster than the iterative soft-thresholding algorithm. Simulation results demonstrate the superior performance of the proposed algorithm in terms of convergence speed and reconstruction quality. (orig.)

  12. Blind spectrum reconstruction algorithm with L0-sparse representation

    International Nuclear Information System (INIS)

    Liu, Hai; Zhang, Zhaoli; Liu, Sanyan; Shu, Jiangbo; Liu, Tingting; Zhang, Tianxu

    2015-01-01

    Raman spectrum often suffers from band overlap and Poisson noise. This paper presents a new blind Poissonian Raman spectrum reconstruction method, which incorporates the L 0 -sparse prior together with the total variation constraint into the maximum a posteriori framework. Furthermore, the greedy analysis pursuit algorithm is adopted to solve the L 0 -based minimization problem. Simulated and real spectrum experimental results show that the proposed method can effectively preserve spectral structure and suppress noise. The reconstructed Raman spectra are easily used for interpreting unknown chemical mixtures. (paper)

  13. Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

    Science.gov (United States)

    Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

    The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P ASIR 80% had the best and worst spatial resolution, respectively. Adaptive statistical iterative reconstruction-V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

  14. Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis

    DEFF Research Database (Denmark)

    Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization s...

  15. Implementation techniques and acceleration of DBPF reconstruction algorithm based on GPGPU for helical cone beam CT

    International Nuclear Information System (INIS)

    Shen Le; Xing Yuxiang

    2010-01-01

    The derivative back-projection filtered algorithm for a helical cone-beam CT is a newly developed exact reconstruction method. Due to its large computational complexity, the reconstruction is rather slow for practical use. General purpose graphic processing unit (GPGPU) is an SIMD paralleled hardware architecture with powerful float-point operation capacity. In this paper,we propose a new method for PI-line choice and sampling grid, and a paralleled PI-line reconstruction algorithm implemented on NVIDIA's Compute Unified Device Architecture (CUDA). Numerical simulation studies are carried out to validate our method. Compared with conventional CPU implementation, the CUDA accelerated method provides images of the same quality with a speedup factor of 318. Optimization strategies for the GPU acceleration are presented. Finally, influence of the parameters of the PI-line samples on the reconstruction speed and image quality is discussed. (authors)

  16. Evaluation of reconstruction algorithms in SPECT neuroimaging: Pt. 1

    International Nuclear Information System (INIS)

    Heejoung Kim; Zeeberg, B.R.; Reba, R.C.

    1993-01-01

    In the presence of statistical noise, an iterative reconstruction algorithm (IRA) for the quantitative reconstruction of single-photon-emission computed tomographic (SPECT) brain images overcomes major limitations of applying the standard filtered back projection (FBP) reconstruction algorithm to projection data which have been degraded by convolution of the true radioactivity distribution with a finite-resolution distance-dependent detector response: (a) the non-uniformity within the grey (or white) matter voxels which results even though the true model is uniform within these voxels; (b) a significantly lower ratio of grey/white matter voxel values than in the true model; and (c) an inability to detect an altered radioactivity value within the grey (or white) matter voxels. It is normally expected that an algorithm which improves spatial resolution and quantitative accuracy might also increase the magnitude of the statistical noise in the reconstructed image. However, the noise properties in the IRA images are very similar to those in the FBP images. (Author)

  17. An evolutionary algorithm for tomographic reconstructions in limited data sets problems

    International Nuclear Information System (INIS)

    Turcanu, Catrinel; Craciunescu, Teddy

    2000-01-01

    The paper proposes a new method for tomographic reconstructions. Unlike nuclear medicine applications, in physical science problems we are often confronted with limited data sets: constraints in the number of projections or limited angle views. The problem of image reconstruction from projections may be considered as a problem of finding an image (solution) having projections that match the experimental ones. In our approach, we choose a statistical correlation coefficient to evaluate the fitness of any potential solution. The optimization process is carried out by an evolutionary algorithm. Our algorithm has some problem-oriented characteristics. One of them is that a chromosome, representing a potential solution, is not linear but coded as a matrix of pixels corresponding to a two-dimensional image. This kind of internal representation reflects the genuine manifestation and slight differences between two points situated in the original problem space give rise to similar differences once they become coded. Another particular feature is a newly built crossover operator: the grid-based crossover, suitable for high dimension two-dimensional chromosomes. Except for the population size and the dimension of the cutting grid for the grid-based crossover, all the other parameters of the algorithm are independent of the geometry of the tomographic reconstruction. The performances of the method are evaluated in comparison with a traditional tomographic method, based on the maximization of the entropy of the image, that proved to work well with limited data sets. The test phantom is typical for an application with limited data sets: the determination of the neutron energy spectra with time resolution in case of short-pulsed neutron emission. The qualitative judgement and also the quantitative one, based on some figures of merit, point out that the proposed method ensures an improved reconstruction of shapes, sizes and resolution in the image, even in the presence of noise

  18. Accelerated Compressed Sensing Based CT Image Reconstruction.

    Science.gov (United States)

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  19. Accelerated Compressed Sensing Based CT Image Reconstruction

    Directory of Open Access Journals (Sweden)

    SayedMasoud Hashemi

    2015-01-01

    Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  20. An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Yuan, E-mail: yuan.lin@duke.edu; Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Duke University Medical Center, 2424 Erwin Road, Suite 302, Durham, North Carolina 27705 (United States)

    2014-02-15

    Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

  1. An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

    International Nuclear Information System (INIS)

    Lin, Yuan; Samei, Ehsan

    2014-01-01

    Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

  2. Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms.

    Science.gov (United States)

    Solomon, Justin; Ba, Alexandre; Bochud, François; Samei, Ehsan

    2016-12-01

    To use novel voxel-based 3D printed textured phantoms in order to compare low-contrast detectability between two reconstruction algorithms, FBP (filtered-backprojection) and SAFIRE (sinogram affirmed iterative reconstruction) and determine what impact background texture (i.e., anatomical noise) has on estimating the dose reduction potential of SAFIRE. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find CLB textures that were reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, four cylindrical phantoms (Textures A-C and uniform, 165 mm in diameter, and 30 mm height) were designed, each containing 20 low-contrast spherical signals (6 mm diameter at nominal contrast levels of ∼3.2, 5.2, 7.2, 10, and 14 HU with four repeats per signal). The phantoms were voxelized and input into a commercial multimaterial 3D printer (Object Connex 350), with custom software for voxel-based printing (using principles of digital dithering). Images of the textured phantoms and a corresponding uniform phantom were acquired at six radiation dose levels (SOMATOM Flash, Siemens Healthcare) and observer model detection performance (detectability index of a multislice channelized Hotelling observer) was estimated for each condition (5 contrasts × 6 doses × 2 reconstructions × 4 backgrounds = 240 total conditions). A multivariate generalized regression analysis was performed (linear terms, no interactions, random error term, log link function) to assess whether dose, reconstruction algorithm, signal contrast, and background type have statistically significant effects on detectability. Also, fitted curves of detectability (averaged across contrast levels

  3. Reconstruction of sparse-view X-ray computed tomography using adaptive iterative algorithms.

    Science.gov (United States)

    Liu, Li; Lin, Weikai; Jin, Mingwu

    2015-01-01

    In this paper, we propose two reconstruction algorithms for sparse-view X-ray computed tomography (CT). Treating the reconstruction problems as data fidelity constrained total variation (TV) minimization, both algorithms adapt the alternate two-stage strategy: projection onto convex sets (POCS) for data fidelity and non-negativity constraints and steepest descent for TV minimization. The novelty of this work is to determine iterative parameters automatically from data, thus avoiding tedious manual parameter tuning. In TV minimization, the step sizes of steepest descent are adaptively adjusted according to the difference from POCS update in either the projection domain or the image domain, while the step size of algebraic reconstruction technique (ART) in POCS is determined based on the data noise level. In addition, projection errors are used to compare with the error bound to decide whether to perform ART so as to reduce computational costs. The performance of the proposed methods is studied and evaluated using both simulated and physical phantom data. Our methods with automatic parameter tuning achieve similar, if not better, reconstruction performance compared to a representative two-stage algorithm. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Acceleration of the direct reconstruction of linear parametric images using nested algorithms

    International Nuclear Information System (INIS)

    Wang Guobao; Qi Jinyi

    2010-01-01

    Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

  5. Image reconstruction for an electrical capacitance tomography system based on a least-squares support vector machine and a self-adaptive particle swarm optimization algorithm

    International Nuclear Information System (INIS)

    Chen, Xia; Hu, Hong-li; Liu, Fei; Gao, Xiang Xiang

    2011-01-01

    The task of image reconstruction for an electrical capacitance tomography (ECT) system is to determine the permittivity distribution and hence the phase distribution in a pipeline by measuring the electrical capacitances between sets of electrodes placed around its periphery. In view of the nonlinear relationship between the permittivity distribution and capacitances and the limited number of independent capacitance measurements, image reconstruction for ECT is a nonlinear and ill-posed inverse problem. To solve this problem, a new image reconstruction method for ECT based on a least-squares support vector machine (LS-SVM) combined with a self-adaptive particle swarm optimization (PSO) algorithm is presented. Regarded as a special small sample theory, the SVM avoids the issues appearing in artificial neural network methods such as difficult determination of a network structure, over-learning and under-learning. However, the SVM performs differently with different parameters. As a relatively new population-based evolutionary optimization technique, PSO is adopted to realize parameters' effective selection with the advantages of global optimization and rapid convergence. This paper builds up a 12-electrode ECT system and a pneumatic conveying platform to verify this image reconstruction algorithm. Experimental results indicate that the algorithm has good generalization ability and high-image reconstruction quality

  6. Optimization-based reconstruction for reduction of CBCT artifact in IGRT

    Science.gov (United States)

    Xia, Dan; Zhang, Zheng; Paysan, Pascal; Seghers, Dieter; Brehm, Marcus; Munro, Peter; Sidky, Emil Y.; Pelizzari, Charles; Pan, Xiaochuan

    2016-04-01

    Kilo-voltage cone-beam computed tomography (CBCT) plays an important role in image guided radiation therapy (IGRT) by providing 3D spatial information of tumor potentially useful for optimizing treatment planning. In current IGRT CBCT system, reconstructed images obtained with analytic algorithms, such as FDK algorithm and its variants, may contain artifacts. In an attempt to compensate for the artifacts, we investigate optimization-based reconstruction algorithms such as the ASD-POCS algorithm for potentially reducing arti- facts in IGRT CBCT images. In this study, using data acquired with a physical phantom and a patient subject, we demonstrate that the ASD-POCS reconstruction can significantly reduce artifacts observed in clinical re- constructions. Moreover, patient images reconstructed by use of the ASD-POCS algorithm indicate a contrast level of soft-tissue improved over that of the clinical reconstruction. We have also performed reconstructions from sparse-view data, and observe that, for current clinical imaging conditions, ASD-POCS reconstructions from data collected at one half of the current clinical projection views appear to show image quality, in terms of spatial and soft-tissue-contrast resolution, higher than that of the corresponding clinical reconstructions.

  7. Dense Matching Comparison Between Census and a Convolutional Neural Network Algorithm for Plant Reconstruction

    Science.gov (United States)

    Xia, Y.; Tian, J.; d'Angelo, P.; Reinartz, P.

    2018-05-01

    3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

  8. Evaluation of the image quality in digital breast tomosynthesis (DBT) employed with a compressed-sensing (CS)-based reconstruction algorithm by using the mammographic accreditation phantom

    Energy Technology Data Exchange (ETDEWEB)

    Park, Yeonok; Cho, Heemoon; Je, Uikyu; Cho, Hyosung, E-mail: hscho1@yonsei.ac.kr; Park, Chulkyu; Lim, Hyunwoo; Kim, Kyuseok; Kim, Guna; Park, Soyoung; Woo, Taeho; Choi, Sungil

    2015-12-21

    In this work, we have developed a prototype digital breast tomosynthesis (DBT) system which mainly consists of an x-ray generator (28 kV{sub p}, 7 mA s), a CMOS-type flat-panel detector (70-μm pixel size, 230.5×339 mm{sup 2} active area), and a rotational arm to move the x-ray generator in an arc. We employed a compressed-sensing (CS)-based reconstruction algorithm, rather than a common filtered-backprojection (FBP) one, for more accurate DBT reconstruction. Here the CS is a state-of-the-art mathematical theory for solving the inverse problems, which exploits the sparsity of the image with substantially high accuracy. We evaluated the reconstruction quality in terms of the detectability, the contrast-to-noise ratio (CNR), and the slice-sensitive profile (SSP) by using the mammographic accreditation phantom (Model 015, CIRS Inc.) and compared it to the FBP-based quality. The CS-based algorithm yielded much better image quality, preserving superior image homogeneity, edge sharpening, and cross-plane resolution, compared to the FBP-based one. - Highlights: • A prototype digital breast tomosynthesis (DBT) system is developed. • Compressed-sensing (CS) based reconstruction framework is employed. • We reconstructed high-quality DBT images by using the proposed reconstruction framework.

  9. An objective algorithm for reconstructing the three-dimensional ocean temperature field based on Argo profiles and SST data

    Science.gov (United States)

    Zhou, Chaojie; Ding, Xiaohua; Zhang, Jie; Yang, Jungang; Ma, Qiang

    2017-12-01

    While global oceanic surface information with large-scale, real-time, high-resolution data is collected by satellite remote sensing instrumentation, three-dimensional (3D) observations are usually obtained from in situ measurements, but with minimal coverage and spatial resolution. To meet the needs of 3D ocean investigations, we have developed a new algorithm to reconstruct the 3D ocean temperature field based on the Array for Real-time Geostrophic Oceanography (Argo) profiles and sea surface temperature (SST) data. The Argo temperature profiles are first optimally fitted to generate a series of temperature functions of depth, with the vertical temperature structure represented continuously. By calculating the derivatives of the fitted functions, the calculation of the vertical temperature gradient of the Argo profiles at an arbitrary depth is accomplished. A gridded 3D temperature gradient field is then found by applying inverse distance weighting interpolation in the horizontal direction. Combined with the processed SST, the 3D temperature field reconstruction is realized below the surface using the gridded temperature gradient. Finally, to confirm the effectiveness of the algorithm, an experiment in the Pacific Ocean south of Japan is conducted, for which a 3D temperature field is generated. Compared with other similar gridded products, the reconstructed 3D temperature field derived by the proposed algorithm achieves satisfactory accuracy, with correlation coefficients of 0.99 obtained, including a higher spatial resolution (0.25° × 0.25°), resulting in the capture of smaller-scale characteristics. Finally, both the accuracy and the superiority of the algorithm are validated.

  10. Performances of new reconstruction algorithms for CT-TDLAS (computer tomography-tunable diode laser absorption spectroscopy)

    International Nuclear Information System (INIS)

    Jeon, Min-Gyu; Deguchi, Yoshihiro; Kamimoto, Takahiro; Doh, Deog-Hee; Cho, Gyeong-Rae

    2017-01-01

    Highlights: • The measured data were successfully used for generating absorption spectra. • Four different reconstruction algorithms, ART, MART, SART and SMART were evaluated. • The calculation speed of convergence by the SMART algorithm was the fastest. • SMART was the most reliable algorithm for reconstructing the multiple signals. - Abstract: Recent advent of the tunable lasers made to measure simultaneous temperature and concentration fields of the gases. CT-TDLAS (computed tomography-tunable diode laser absorption spectroscopy) is one the leading techniques for the measurements of temperature and concentration fields of the gases. In CT-TDLAS, the accuracies of the measurement results are strongly dependent upon the reconstruction algorithms. In this study, four different reconstruction algorithms have been tested numerically using experimental data sets measured by thermocouples for combustion fields. Three reconstruction algorithms, MART (multiplicative algebraic reconstruction technique) algorithm, SART (simultaneous algebraic reconstruction technique) algorithm and SMART (simultaneous multiplicative algebraic reconstruction technique) algorithm, are newly proposed for CT-TDLAS in this study. The calculation results obtained by the three algorithms have been compared with previous algorithm, ART (algebraic reconstruction technique) algorithm. Phantom data sets have been generated by the use of thermocouples data obtained in an actual experiment. The data of the Harvard HITRAN table in which the thermo-dynamical properties and the light spectrum of the H_2O are listed were used for the numerical test. The reconstructed temperature and concentration fields were compared with the original HITRAN data, through which the constructed methods are validated. The performances of the four reconstruction algorithms were demonstrated. This method is expected to enhance the practicality of CT-TDLAS.

  11. An Approximate Cone Beam Reconstruction Algorithm for Gantry-Tilted CT Using Tangential Filtering

    Directory of Open Access Journals (Sweden)

    Ming Yan

    2006-01-01

    Full Text Available FDK algorithm is a well-known 3D (three-dimensional approximate algorithm for CT (computed tomography image reconstruction and is also known to suffer from considerable artifacts when the scanning cone angle is large. Recently, it has been improved by performing the ramp filtering along the tangential direction of the X-ray source helix for dealing with the large cone angle problem. In this paper, we present an FDK-type approximate reconstruction algorithm for gantry-tilted CT imaging. The proposed method improves the image reconstruction by filtering the projection data along a proper direction which is determined by CT parameters and gantry-tilted angle. As a result, the proposed algorithm for gantry-tilted CT reconstruction can provide more scanning flexibilities in clinical CT scanning and is efficient in computation. The performance of the proposed algorithm is evaluated with turbell clock phantom and thorax phantom and compared with FDK algorithm and a popular 2D (two-dimensional approximate algorithm. The results show that the proposed algorithm can achieve better image quality for gantry-tilted CT image reconstruction.

  12. Research on Modified Root-MUSIC Algorithm of DOA Estimation Based on Covariance Matrix Reconstruction

    Directory of Open Access Journals (Sweden)

    Changgan SHU

    2014-09-01

    Full Text Available In the standard root multiple signal classification algorithm, the performance of direction of arrival estimation will reduce and even lose effect in circumstances that a low signal noise ratio and a small signals interval. By reconstructing and weighting the covariance matrix of received signal, the modified algorithm can provide more accurate estimation results. The computer simulation and performance analysis are given next, which show that under the condition of lower signal noise ratio and stronger correlation between signals, the proposed modified algorithm could provide preferable azimuth estimating performance than the standard method.

  13. Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

    International Nuclear Information System (INIS)

    Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang- Hee

    2014-01-01

    State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time. - Highlights: • The PDS-OSEM reconstructs PET images with iteratively compensating random and scatter corrections from prompt sinogram. • The PDS-OSEM can reconstruct PET images with low count data and data contaminations. • The PDS-OSEM provides less noise and higher quality of reconstructed images than those of OP-OSEM algorithm in statistical sense

  14. A density based algorithm to detect cavities and holes from planar points

    Science.gov (United States)

    Zhu, Jie; Sun, Yizhong; Pang, Yueyong

    2017-12-01

    Delaunay-based shape reconstruction algorithms are widely used in approximating the shape from planar points. However, these algorithms cannot ensure the optimality of varied reconstructed cavity boundaries and hole boundaries. This inadequate reconstruction can be primarily attributed to the lack of efficient mathematic formulation for the two structures (hole and cavity). In this paper, we develop an efficient algorithm for generating cavities and holes from planar points. The algorithm yields the final boundary based on an iterative removal of the Delaunay triangulation. Our algorithm is mainly divided into two steps, namely, rough and refined shape reconstructions. The rough shape reconstruction performed by the algorithm is controlled by a relative parameter. Based on the rough result, the refined shape reconstruction mainly aims to detect holes and pure cavities. Cavity and hole are conceptualized as a structure with a low-density region surrounded by the high-density region. With this structure, cavity and hole are characterized by a mathematic formulation called as compactness of point formed by the length variation of the edges incident to point in Delaunay triangulation. The boundaries of cavity and hole are then found by locating a shape gradient change in compactness of point set. The experimental comparison with other shape reconstruction approaches shows that the proposed algorithm is able to accurately yield the boundaries of cavity and hole with varying point set densities and distributions.

  15. A fully three-dimensional reconstruction algorithm with the nonstationary filter for improved single-orbit cone beam SPECT

    International Nuclear Information System (INIS)

    Cao, Z.J.; Tsui, B.M.

    1993-01-01

    Conventional single-orbit cone beam tomography presents special problems. They include incomplete sampling and inadequate three-dimensional (3D) reconstruction algorithm. The commonly used Feldkamp reconstruction algorithm simply extends the two-dimensional (2D) fan beam algorithm to 3D cone beam geometry. A truly 3D reconstruction formulation has been derived for the single-orbit cone beam SPECT based on the 3D Fourier slice theorem. In the formulation, a nonstationary filter which depends on the distance from the central plane of the cone beam was derived. The filter is applied to the 2D projection data in directions along and normal to the axis-of-rotation. The 3D reconstruction algorithm with the nonstationary filter was evaluated using both computer simulation and experimental measurements. Significant improvement in image quality was demonstrated in terms of decreased artifacts and distortions in cone beam reconstructed images. However, compared with the Feldkamp algorithm, a five-fold increase in processing time is required. Further improvement in image quality needs complete sampling in frequency space

  16. A Novel 2D Image Compression Algorithm Based on Two Levels DWT and DCT Transforms with Enhanced Minimize-Matrix-Size Algorithm for High Resolution Structured Light 3D Surface Reconstruction

    Science.gov (United States)

    Siddeq, M. M.; Rodrigues, M. A.

    2015-09-01

    Image compression techniques are widely used on 2D image 2D video 3D images and 3D video. There are many types of compression techniques and among the most popular are JPEG and JPEG2000. In this research, we introduce a new compression method based on applying a two level discrete cosine transform (DCT) and a two level discrete wavelet transform (DWT) in connection with novel compression steps for high-resolution images. The proposed image compression algorithm consists of four steps. (1) Transform an image by a two level DWT followed by a DCT to produce two matrices: DC- and AC-Matrix, or low and high frequency matrix, respectively, (2) apply a second level DCT on the DC-Matrix to generate two arrays, namely nonzero-array and zero-array, (3) apply the Minimize-Matrix-Size algorithm to the AC-Matrix and to the other high-frequencies generated by the second level DWT, (4) apply arithmetic coding to the output of previous steps. A novel decompression algorithm, Fast-Match-Search algorithm (FMS), is used to reconstruct all high-frequency matrices. The FMS-algorithm computes all compressed data probabilities by using a table of data, and then using a binary search algorithm for finding decompressed data inside the table. Thereafter, all decoded DC-values with the decoded AC-coefficients are combined in one matrix followed by inverse two levels DCT with two levels DWT. The technique is tested by compression and reconstruction of 3D surface patches. Additionally, this technique is compared with JPEG and JPEG2000 algorithm through 2D and 3D root-mean-square-error following reconstruction. The results demonstrate that the proposed compression method has better visual properties than JPEG and JPEG2000 and is able to more accurately reconstruct surface patches in 3D.

  17. DENSE MATCHING COMPARISON BETWEEN CENSUS AND A CONVOLUTIONAL NEURAL NETWORK ALGORITHM FOR PLANT RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    Y. Xia

    2018-05-01

    Full Text Available 3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

  18. Cone-beam local reconstruction based on a Radon inversion transformation

    International Nuclear Information System (INIS)

    Wang Xian-Chao; Yan Bin; Li Lei; Hu Guo-En

    2012-01-01

    The local reconstruction from truncated projection data is one area of interest in image reconstruction for computed tomography (CT), which creates the possibility for dose reduction. In this paper, a filtered-backprojection (FBP) algorithm based on the Radon inversion transform is presented to deal with the three-dimensional (3D) local reconstruction in the circular geometry. The algorithm achieves the data filtering in two steps. The first step is the derivative of projections, which acts locally on the data and can thus be carried out accurately even in the presence of data truncation. The second step is the nonlocal Hilbert filtering. The numerical simulations and the real data reconstructions have been conducted to validate the new reconstruction algorithm. Compared with the approximate truncation resistant algorithm for computed tomography (ATRACT), not only it has a comparable ability to restrain truncation artifacts, but also its reconstruction efficiency is improved. It is about twice as fast as that of the ATRACT. Therefore, this work provides a simple and efficient approach for the approximate reconstruction from truncated projections in the circular cone-beam CT

  19. Search for 'Little Higgs' and reconstruction algorithms developments in Atlas

    International Nuclear Information System (INIS)

    Rousseau, D.

    2007-05-01

    This document summarizes developments of framework and reconstruction algorithms for the ATLAS detector at the LHC. A library of reconstruction algorithms has been developed in a more and more complex environment. The reconstruction software originally designed on an optimistic Monte-Carlo simulation, has been confronted with a more detailed 'as-built' simulation. The 'Little Higgs' is an effective theory which can be taken for granted, or as an opportunity to study heavy resonances. In several cases, these resonances can be detected in original channels like tZ, ZH or WH. (author)

  20. On-line reconstruction algorithms for the CBM and ALICE experiments

    International Nuclear Information System (INIS)

    Gorbunov, Sergey

    2013-01-01

    This thesis presents various algorithms which have been developed for on-line event reconstruction in the CBM experiment at GSI, Darmstadt and the ALICE experiment at CERN, Geneve. Despite the fact that the experiments are different - CBM is a fixed target experiment with forward geometry, while ALICE has a typical collider geometry - they share common aspects when reconstruction is concerned. The thesis describes: - general modifications to the Kalman filter method, which allows one to accelerate, to improve, and to simplify existing fit algorithms; - developed algorithms for track fit in CBM and ALICE experiment, including a new method for track extrapolation in non-homogeneous magnetic field. - developed algorithms for primary and secondary vertex fit in the both experiments. In particular, a new method of reconstruction of decayed particles is presented. - developed parallel algorithm for the on-line tracking in the CBM experiment. - developed parallel algorithm for the on-line tracking in High Level Trigger of the ALICE experiment. - the realisation of the track finders on modern hardware, such as SIMD CPU registers and GPU accelerators. All the presented methods have been developed by or with the direct participation of the author.

  1. Development of computed tomography system and image reconstruction algorithm

    International Nuclear Information System (INIS)

    Khairiah Yazid; Mohd Ashhar Khalid; Azaman Ahmad; Khairul Anuar Mohd Salleh; Ab Razak Hamzah

    2006-01-01

    Computed tomography is one of the most advanced and powerful nondestructive inspection techniques, which is currently used in many different industries. In several CT systems, detection has been by combination of an X-ray image intensifier and charge -coupled device (CCD) camera or by using line array detector. The recent development of X-ray flat panel detector has made fast CT imaging feasible and practical. Therefore this paper explained the arrangement of a new detection system which is using the existing high resolution (127 μm pixel size) flat panel detector in MINT and the image reconstruction technique developed. The aim of the project is to develop a prototype flat panel detector based CT imaging system for NDE. The prototype consisted of an X-ray tube, a flat panel detector system, a rotation table and a computer system to control the sample motion and image acquisition. Hence this project is divided to two major tasks, firstly to develop image reconstruction algorithm and secondly to integrate X-ray imaging components into one CT system. The image reconstruction algorithm using filtered back-projection method is developed and compared to other techniques. The MATLAB program is the tools used for the simulations and computations for this project. (Author)

  2. Reconstruction algorithm medical imaging DRR; Algoritmo de construccion de imagenes medicas DRR

    Energy Technology Data Exchange (ETDEWEB)

    Estrada Espinosa, J. C.

    2013-07-01

    The method of reconstruction for digital radiographic Imaging (DRR), is based on two orthogonal images, on the dorsal and lateral decubitus position of the simulation. DRR images are reconstructed with an algorithm that simulates running a conventional X-ray, a single rendition team, beam emitted is not divergent, in this case, the rays are considered to be parallel in the image reconstruction DRR, for this purpose, it is necessary to use all the values of the units (HU) hounsfield of each voxel in all axial cuts that form the study TC, finally obtaining the reconstructed image DRR performing a transformation from 3D to 2D. (Author)

  3. Greedy algorithms for diffuse optical tomography reconstruction

    Science.gov (United States)

    Dileep, B. P. V.; Das, Tapan; Dutta, Pranab K.

    2018-03-01

    Diffuse optical tomography (DOT) is a noninvasive imaging modality that reconstructs the optical parameters of a highly scattering medium. However, the inverse problem of DOT is ill-posed and highly nonlinear due to the zig-zag propagation of photons that diffuses through the cross section of tissue. The conventional DOT imaging methods iteratively compute the solution of forward diffusion equation solver which makes the problem computationally expensive. Also, these methods fail when the geometry is complex. Recently, the theory of compressive sensing (CS) has received considerable attention because of its efficient use in biomedical imaging applications. The objective of this paper is to solve a given DOT inverse problem by using compressive sensing framework and various Greedy algorithms such as orthogonal matching pursuit (OMP), compressive sampling matching pursuit (CoSaMP), and stagewise orthogonal matching pursuit (StOMP), regularized orthogonal matching pursuit (ROMP) and simultaneous orthogonal matching pursuit (S-OMP) have been studied to reconstruct the change in the absorption parameter i.e, Δα from the boundary data. Also, the Greedy algorithms have been validated experimentally on a paraffin wax rectangular phantom through a well designed experimental set up. We also have studied the conventional DOT methods like least square method and truncated singular value decomposition (TSVD) for comparison. One of the main features of this work is the usage of less number of source-detector pairs, which can facilitate the use of DOT in routine applications of screening. The performance metrics such as mean square error (MSE), normalized mean square error (NMSE), structural similarity index (SSIM), and peak signal to noise ratio (PSNR) have been used to evaluate the performance of the algorithms mentioned in this paper. Extensive simulation results confirm that CS based DOT reconstruction outperforms the conventional DOT imaging methods in terms of

  4. Beard reconstruction: A surgical algorithm.

    Science.gov (United States)

    Ninkovic, M; Heidekrueger, P I; Ehrl, D; von Spiegel, F; Broer, P N

    2016-06-01

    Facial defects with loss of hair-bearing regions can be caused by trauma, infection, tumor excision, or burn injury. The presented analysis evaluates a series of different surgical approaches with a focus on male beard reconstruction, emphasizing the role of tissue expansion of regional and free flaps. Locoregional and free flap reconstructions were performed in 11 male patients with 14 facial defects affecting the hair-bearing bucco-mandibular or perioral region. In order to minimize donor-site morbidity and obtain large amounts of thin, pliable, hair-bearing tissue, pre-expansion was performed in five of 14 patients. Eight of 14 patients were treated with locoregional flap reconstructions and six with free flap reconstructions. Algorithms regarding pre- and intraoperative decision making are discussed and long-term (mean follow-up 1.5 years) results analyzed. Major complications, including tissue expander infection with the need for removal or exchange, partial or full flap loss, occurred in 0% (0/8) of patients with locoregional flaps and in 17% (1/6) of patients undergoing free flap reconstructions. Secondary refinement surgery was performed in 25% (2/8) of locoregional flaps and in 67% (4/6) of free flaps. Both locoregional and distant tissue transfers play a role in beard reconstruction, while pre-expansion remains an invaluable tool. Paying attention to the presented principles and considering the significance of aesthetic facial subunits, range of motion, aesthetics, and patient satisfaction were improved long term in all our patients while minimizing donor-site morbidity. Copyright © 2016 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  5. A subzone reconstruction algorithm for efficient staggered compatible remapping

    Energy Technology Data Exchange (ETDEWEB)

    Starinshak, D.P., E-mail: starinshak1@llnl.gov; Owen, J.M., E-mail: mikeowen@llnl.gov

    2015-09-01

    Staggered-grid Lagrangian hydrodynamics algorithms frequently make use of subzonal discretization of state variables for the purposes of improved numerical accuracy, generality to unstructured meshes, and exact conservation of mass, momentum, and energy. For Arbitrary Lagrangian–Eulerian (ALE) methods using a geometric overlay, it is difficult to remap subzonal variables in an accurate and efficient manner due to the number of subzone–subzone intersections that must be computed. This becomes prohibitive in the case of 3D, unstructured, polyhedral meshes. A new procedure is outlined in this paper to avoid direct subzonal remapping. The new algorithm reconstructs the spatial profile of a subzonal variable using remapped zonal and nodal representations of the data. The reconstruction procedure is cast as an under-constrained optimization problem. Enforcing conservation at each zone and node on the remapped mesh provides the set of equality constraints; the objective function corresponds to a quadratic variation per subzone between the values to be reconstructed and a set of target reference values. Numerical results for various pure-remapping and hydrodynamics tests are provided. Ideas for extending the algorithm to staggered-grid radiation-hydrodynamics are discussed as well as ideas for generalizing the algorithm to include inequality constraints.

  6. A three-dimensional reconstruction algorithm for an inverse-geometry volumetric CT system

    International Nuclear Information System (INIS)

    Schmidt, Taly Gilat; Fahrig, Rebecca; Pelc, Norbert J.

    2005-01-01

    An inverse-geometry volumetric computed tomography (IGCT) system has been proposed capable of rapidly acquiring sufficient data to reconstruct a thick volume in one circular scan. The system uses a large-area scanned source opposite a smaller detector. The source and detector have the same extent in the axial, or slice, direction, thus providing sufficient volumetric sampling and avoiding cone-beam artifacts. This paper describes a reconstruction algorithm for the IGCT system. The algorithm first rebins the acquired data into two-dimensional (2D) parallel-ray projections at multiple tilt and azimuthal angles, followed by a 3D filtered backprojection. The rebinning step is performed by gridding the data onto a Cartesian grid in a 4D projection space. We present a new method for correcting the gridding error caused by the finite and asymmetric sampling in the neighborhood of each output grid point in the projection space. The reconstruction algorithm was implemented and tested on simulated IGCT data. Results show that the gridding correction reduces the gridding errors to below one Hounsfield unit. With this correction, the reconstruction algorithm does not introduce significant artifacts or blurring when compared to images reconstructed from simulated 2D parallel-ray projections. We also present an investigation of the noise behavior of the method which verifies that the proposed reconstruction algorithm utilizes cross-plane rays as efficiently as in-plane rays and can provide noise comparable to an in-plane parallel-ray geometry for the same number of photons. Simulations of a resolution test pattern and the modulation transfer function demonstrate that the IGCT system, using the proposed algorithm, is capable of 0.4 mm isotropic resolution. The successful implementation of the reconstruction algorithm is an important step in establishing feasibility of the IGCT system

  7. Analytical fan-beam and cone-beam reconstruction algorithms with uniform attenuation correction for SPECT

    International Nuclear Information System (INIS)

    Tang Qiulin; Zeng, Gengsheng L; Gullberg, Grant T

    2005-01-01

    In this paper, we developed an analytical fan-beam reconstruction algorithm that compensates for uniform attenuation in SPECT. The new fan-beam algorithm is in the form of backprojection first, then filtering, and is mathematically exact. The algorithm is based on three components. The first one is the established generalized central-slice theorem, which relates the 1D Fourier transform of a set of arbitrary data and the 2D Fourier transform of the backprojected image. The second one is the fact that the backprojection of the fan-beam measurements is identical to the backprojection of the parallel measurements of the same object with the same attenuator. The third one is the stable analytical reconstruction algorithm for uniformly attenuated Radon data, developed by Metz and Pan. The fan-beam algorithm is then extended into a cone-beam reconstruction algorithm, where the orbit of the focal point of the cone-beam imaging geometry is a circle. This orbit geometry does not satisfy Tuy's condition and the obtained cone-beam algorithm is an approximation. In the cone-beam algorithm, the cone-beam data are first backprojected into the 3D image volume; then a slice-by-slice filtering is performed. This slice-by-slice filtering procedure is identical to that of the fan-beam algorithm. Both the fan-beam and cone-beam algorithms are efficient, and computer simulations are presented. The new cone-beam algorithm is compared with Bronnikov's cone-beam algorithm, and it is shown to have better performance with noisy projections

  8. A new approximate algorithm for image reconstruction in cone-beam spiral CT at small cone-angles

    International Nuclear Information System (INIS)

    Schaller, S.; Flohr, T.; Steffen, P.

    1996-01-01

    This paper presents a new approximate algorithm for image reconstruction with cone-beam spiral CT data at relatively small cone-angles. Based on the algorithm of Wang et al., our method combines a special complementary interpolation with filtered backprojection. The presented algorithm has three main advantages over Wang's algorithm: (1) It overcomes the pitch limitation of Wang's algorithm. (2) It significantly improves z-resolution when suitable sampling schemes are applied. (3) It avoids the waste of applied radiation dose inherent to Wang's algorithm. Usage of the total applied dose is an important requirement in medical imaging. Our method has been implemented on a standard workstation. Reconstructions of computer-simulated data of different phantoms, assuming sampling conditions and image quality requirements typical to medical CT, show encouraging results

  9. Quantitatively assessed CT imaging measures of pulmonary interstitial pneumonia: Effects of reconstruction algorithms on histogram parameters

    International Nuclear Information System (INIS)

    Koyama, Hisanobu; Ohno, Yoshiharu; Yamazaki, Youichi; Nogami, Munenobu; Kusaka, Akiko; Murase, Kenya; Sugimura, Kazuro

    2010-01-01

    This study aimed the influences of reconstruction algorithm for quantitative assessments in interstitial pneumonia patients. A total of 25 collagen vascular disease patients (nine male patients and 16 female patients; mean age, 57.2 years; age range 32-77 years) underwent thin-section MDCT examinations, and MDCT data were reconstructed with three kinds of reconstruction algorithm (two high-frequencies [A and B] and one standard [C]). In reconstruction algorithm B, the effect of low- and middle-frequency space was suppressed compared with reconstruction algorithm A. As quantitative CT parameters, kurtosis, skewness, and mean lung density (MLD) were acquired from a frequency histogram of the whole lung parenchyma in each reconstruction algorithm. To determine the difference of quantitative CT parameters affected by reconstruction algorithms, these parameters were compared statistically. To determine the relationships with the disease severity, these parameters were correlated with PFTs. In the results, all the histogram parameters values had significant differences each other (p < 0.0001) and those of reconstruction algorithm C were the highest. All MLDs had fair or moderate correlation with all parameters of PFT (-0.64 < r < -0.45, p < 0.05). Though kurtosis and skewness in high-frequency reconstruction algorithm A had significant correlations with all parameters of PFT (-0.61 < r < -0.45, p < 0.05), there were significant correlations only with diffusing capacity of carbon monoxide (DLco) and total lung capacity (TLC) in reconstruction algorithm C and with forced expiratory volume in 1 s (FEV1), DLco and TLC in reconstruction algorithm B. In conclusion, reconstruction algorithm has influence to quantitative assessments on chest thin-section MDCT examination in interstitial pneumonia patients.

  10. Quantitatively assessed CT imaging measures of pulmonary interstitial pneumonia: Effects of reconstruction algorithms on histogram parameters

    Energy Technology Data Exchange (ETDEWEB)

    Koyama, Hisanobu [Department of Radiology, Hyogo Kaibara Hospital, 5208-1 Kaibara, Kaibara-cho, Tanba 669-3395 (Japan)], E-mail: hisanobu19760104@yahoo.co.jp; Ohno, Yoshiharu [Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: yosirad@kobe-u.ac.jp; Yamazaki, Youichi [Department of Medical Physics and Engineering, Faculty of Health Sciences, Graduate School of Medicine, Osaka University, 1-7 Yamadaoka, Suita 565-0871 (Japan)], E-mail: y.yamazk@sahs.med.osaka-u.ac.jp; Nogami, Munenobu [Division of PET, Institute of Biomedical Research and Innovation, 2-2 MInamimachi, Minatojima, Chu0-ku, Kobe 650-0047 (Japan)], E-mail: aznogami@fbri.org; Kusaka, Akiko [Division of Radiology, Kobe University Hospital, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: a.kusaka@hosp.kobe-u.ac.jp; Murase, Kenya [Department of Medical Physics and Engineering, Faculty of Health Sciences, Graduate School of Medicine, Osaka University, 1-7 Yamadaoka, Suita 565-0871 (Japan)], E-mail: murase@sahs.med.osaka-u.ac.jp; Sugimura, Kazuro [Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: sugimura@med.kobe-u.ac.jp

    2010-04-15

    This study aimed the influences of reconstruction algorithm for quantitative assessments in interstitial pneumonia patients. A total of 25 collagen vascular disease patients (nine male patients and 16 female patients; mean age, 57.2 years; age range 32-77 years) underwent thin-section MDCT examinations, and MDCT data were reconstructed with three kinds of reconstruction algorithm (two high-frequencies [A and B] and one standard [C]). In reconstruction algorithm B, the effect of low- and middle-frequency space was suppressed compared with reconstruction algorithm A. As quantitative CT parameters, kurtosis, skewness, and mean lung density (MLD) were acquired from a frequency histogram of the whole lung parenchyma in each reconstruction algorithm. To determine the difference of quantitative CT parameters affected by reconstruction algorithms, these parameters were compared statistically. To determine the relationships with the disease severity, these parameters were correlated with PFTs. In the results, all the histogram parameters values had significant differences each other (p < 0.0001) and those of reconstruction algorithm C were the highest. All MLDs had fair or moderate correlation with all parameters of PFT (-0.64 < r < -0.45, p < 0.05). Though kurtosis and skewness in high-frequency reconstruction algorithm A had significant correlations with all parameters of PFT (-0.61 < r < -0.45, p < 0.05), there were significant correlations only with diffusing capacity of carbon monoxide (DLco) and total lung capacity (TLC) in reconstruction algorithm C and with forced expiratory volume in 1 s (FEV1), DLco and TLC in reconstruction algorithm B. In conclusion, reconstruction algorithm has influence to quantitative assessments on chest thin-section MDCT examination in interstitial pneumonia patients.

  11. Performance of the ATLAS primary vertex reconstruction algorithms

    CERN Document Server

    Zhang, Matt

    2017-01-01

    The reconstruction of primary vertices in the busy, high pile up environment of the LHC is a challenging task. The challenges and novel methods developed by the ATLAS experiment to reconstruct vertices in such environments will be presented. Such advances in vertex seeding include methods taken from medical imagining, which allow for reconstruction of very nearby vertices will be highlighted. The performance of the current vertexing algorithms using early Run-2 data will be presented and compared to results from simulation.

  12. A Study on GPU-based Iterative ML-EM Reconstruction Algorithm for Emission Computed Tomographic Imaging Systems

    Energy Technology Data Exchange (ETDEWEB)

    Ha, Woo Seok; Kim, Soo Mee; Park, Min Jae; Lee, Dong Soo; Lee, Jae Sung [Seoul National University, Seoul (Korea, Republic of)

    2009-10-15

    The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 sec, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 sec, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries

  13. A Study on GPU-based Iterative ML-EM Reconstruction Algorithm for Emission Computed Tomographic Imaging Systems

    International Nuclear Information System (INIS)

    Ha, Woo Seok; Kim, Soo Mee; Park, Min Jae; Lee, Dong Soo; Lee, Jae Sung

    2009-01-01

    The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 sec, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 sec, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries

  14. A maximum-likelihood reconstruction algorithm for tomographic gamma-ray nondestructive assay

    International Nuclear Information System (INIS)

    Prettyman, T.H.; Estep, R.J.; Cole, R.A.; Sheppard, G.A.

    1994-01-01

    A new tomographic reconstruction algorithm for nondestructive assay with high resolution gamma-ray spectroscopy (HRGS) is presented. The reconstruction problem is formulated using a maximum-likelihood approach in which the statistical structure of both the gross and continuum measurements used to determine the full-energy response in HRGS is precisely modeled. An accelerated expectation-maximization algorithm is used to determine the optimal solution. The algorithm is applied to safeguards and environmental assays of large samples (for example, 55-gal. drums) in which high continuum levels caused by Compton scattering are routinely encountered. Details of the implementation of the algorithm and a comparative study of the algorithm's performance are presented

  15. Fast dictionary-based reconstruction for diffusion spectrum imaging.

    Science.gov (United States)

    Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar

    2013-11-01

    Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.

  16. Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

    Science.gov (United States)

    Wu, Junfeng; Dai, Fang; Hu, Gang; Mou, Xuanqin

    2018-04-18

    Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has been developed to reconstruct CT images from the low dose and few-view dataset in order to reduce radiation dose. Nonetheless, the sparse regularization term adopted in this approach is l0-norm, which cannot guarantee the global convergence of the proposed algorithm. To address this problem, in this study we introduced the l1-norm dictionary learning penalty into SIR framework for low dose CT image reconstruction, and developed an alternating minimization algorithm to minimize the associated objective function, which transforms CT image reconstruction problem into a sparse coding subproblem and an image updating subproblem. During the image updating process, an efficient model function approach based on balancing principle is applied to choose the regularization parameters. The proposed alternating minimization algorithm was evaluated first using real projection data of a sheep lung CT perfusion and then using numerical simulation based on sheep lung CT image and chest image. Both visual assessment and quantitative comparison using terms of root mean square error (RMSE) and structural similarity (SSIM) index demonstrated that the new image reconstruction algorithm yielded similar performance with l0-norm dictionary learning penalty and outperformed the conventional filtered backprojection (FBP) and total variation (TV) minimization algorithms.

  17. A faster ordered-subset convex algorithm for iterative reconstruction in a rotation-free micro-CT system

    International Nuclear Information System (INIS)

    Quan, E; Lalush, D S

    2009-01-01

    We present a faster iterative reconstruction algorithm based on the ordered-subset convex (OSC) algorithm for transmission CT. The OSC algorithm was modified such that it calculates the normalization term before the iterative process in order to save computational cost. The modified version requires only one backprojection per iteration as compared to two required for the original OSC. We applied the modified OSC (MOSC) algorithm to a rotation-free micro-CT system that we proposed previously, observed its performance, and compared with the OSC algorithm for 3D cone-beam reconstruction. Measurements on the reconstructed images as well as the point spread functions show that MOSC is quite similar to OSC; in noise-resolution trade-off, MOSC is comparable with OSC in a regular-noise situation and it is slightly worse than OSC in an extremely high-noise situation. The timing record shows that MOSC saves 25-30% CPU time, depending on the number of iterations used. We conclude that the MOSC algorithm is more efficient than OSC and provides comparable images.

  18. Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Chong Fan

    2017-03-01

    Full Text Available A sub-block algorithm is usually applied in the super-resolution (SR reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

  19. A practical exact maximum compatibility algorithm for reconstruction of recent evolutionary history.

    Science.gov (United States)

    Cherry, Joshua L

    2017-02-23

    Maximum compatibility is a method of phylogenetic reconstruction that is seldom applied to molecular sequences. It may be ideal for certain applications, such as reconstructing phylogenies of closely-related bacteria on the basis of whole-genome sequencing. Here I present an algorithm that rapidly computes phylogenies according to a compatibility criterion. Although based on solutions to the maximum clique problem, this algorithm deals properly with ambiguities in the data. The algorithm is applied to bacterial data sets containing up to nearly 2000 genomes with several thousand variable nucleotide sites. Run times are several seconds or less. Computational experiments show that maximum compatibility is less sensitive than maximum parsimony to the inclusion of nucleotide data that, though derived from actual sequence reads, has been identified as likely to be misleading. Maximum compatibility is a useful tool for certain phylogenetic problems, such as inferring the relationships among closely-related bacteria from whole-genome sequence data. The algorithm presented here rapidly solves fairly large problems of this type, and provides robustness against misleading characters than can pollute large-scale sequencing data.

  20. Verification-Based Interval-Passing Algorithm for Compressed Sensing

    OpenAIRE

    Wu, Xiaofu; Yang, Zhen

    2013-01-01

    We propose a verification-based Interval-Passing (IP) algorithm for iteratively reconstruction of nonnegative sparse signals using parity check matrices of low-density parity check (LDPC) codes as measurement matrices. The proposed algorithm can be considered as an improved IP algorithm by further incorporation of the mechanism of verification algorithm. It is proved that the proposed algorithm performs always better than either the IP algorithm or the verification algorithm. Simulation resul...

  1. A parallel implementation of a maximum entropy reconstruction algorithm for PET images in a visual language

    International Nuclear Information System (INIS)

    Bastiens, K.; Lemahieu, I.

    1994-01-01

    The application of a maximum entropy reconstruction algorithm to PET images requires a lot of computing resources. A parallel implementation could seriously reduce the execution time. However, programming a parallel application is still a non trivial task, needing specialized people. In this paper a programming environment based on a visual programming language is used for a parallel implementation of the reconstruction algorithm. This programming environment allows less experienced programmers to use the performance of multiprocessor systems. (authors)

  2. A GREIT-type linear reconstruction algorithm for EIT using eigenimages

    International Nuclear Information System (INIS)

    Antink, Christoph Hoog; Pikkemaat, Robert; Leonhardt, Steffen

    2013-01-01

    Reconstruction in electrical impedance tomography (EIT) is a nonlinear, ill-posed inverse problem. Based on point-shaped training and evaluation data, the 'Graz consensus Reconstruction algorithm for EIT' (GREIT) constitutes a universal, homogenous method. While this is a very reasonable approach to the general problem, we ask the question if an optimized reconstruction method for a specific application of EIT, i.e. thoracic imaging, can be found. Instead of point-shaped training data we propose to use spatially extended training data consisting of eigenimages. To evaluate the quality of reconstruction of the proposed approach, figures of merit (FOMs) derived from the ones used in GREIT are developed. For the application of thoracic imaging, lung-shapes were segmented from a publicly available CT-database (www.dir-lab.com) and used to calculate the novel FOMs. With those, the general feasibility of using eigenimages is demonstrated and compared to the standard approach. In addition, it is shown that by using different sets of training data, the creation of an individually optimized linear method of reconstruction is possible.

  3. Noise propagation in iterative reconstruction algorithms with line searches

    International Nuclear Information System (INIS)

    Qi, Jinyi

    2003-01-01

    In this paper we analyze the propagation of noise in iterative image reconstruction algorithms. We derive theoretical expressions for the general form of preconditioned gradient algorithms with line searches. The results are applicable to a wide range of iterative reconstruction problems, such as emission tomography, transmission tomography, and image restoration. A unique contribution of this paper comparing to our previous work [1] is that the line search is explicitly modeled and we do not use the approximation that the gradient of the objective function is zero. As a result, the error in the estimate of noise at early iterations is significantly reduced

  4. Intermediate view reconstruction using adaptive disparity search algorithm for real-time 3D processing

    Science.gov (United States)

    Bae, Kyung-hoon; Park, Changhan; Kim, Eun-soo

    2008-03-01

    In this paper, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (ASDA) is for realtime 3-dimensional (3D) processing proposed. The proposed algorithm can reduce processing time of disparity estimation by selecting adaptive disparity search range. Also, the proposed algorithm can increase the quality of the 3D imaging. That is, by adaptively predicting the mutual correlation between stereo images pair using the proposed algorithm, the bandwidth of stereo input images pair can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and disparity vectors. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm improves the PSNRs of a reconstructed image to about 4.8 dB by comparing with that of conventional algorithms, and reduces the Synthesizing time of a reconstructed image to about 7.02 sec by comparing with that of conventional algorithms.

  5. QR-decomposition based SENSE reconstruction using parallel architecture.

    Science.gov (United States)

    Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

    2018-04-01

    Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

  6. Weighted expectation maximization reconstruction algorithms with application to gated megavoltage tomography

    International Nuclear Information System (INIS)

    Zhang Jin; Shi Daxin; Anastasio, Mark A; Sillanpaa, Jussi; Chang Jenghwa

    2005-01-01

    We propose and investigate weighted expectation maximization (EM) algorithms for image reconstruction in x-ray tomography. The development of the algorithms is motivated by the respiratory-gated megavoltage tomography problem, in which the acquired asymmetric cone-beam projections are limited in number and unevenly sampled over view angle. In these cases, images reconstructed by use of the conventional EM algorithm can contain ring- and streak-like artefacts that are attributable to a combination of data inconsistencies and truncation of the projection data. By use of computer-simulated and clinical gated fan-beam megavoltage projection data, we demonstrate that the proposed weighted EM algorithms effectively mitigate such image artefacts. (note)

  7. The SRT reconstruction algorithm for semiquantification in PET imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kastis, George A., E-mail: gkastis@academyofathens.gr [Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece); Gaitanis, Anastasios [Biomedical Research Foundation of the Academy of Athens (BRFAA), Athens 11527 (Greece); Samartzis, Alexandros P. [Nuclear Medicine Department, Evangelismos General Hospital, Athens 10676 (Greece); Fokas, Athanasios S. [Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB30WA, United Kingdom and Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece)

    2015-10-15

    Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of {sup 18}F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT

  8. The SRT reconstruction algorithm for semiquantification in PET imaging

    International Nuclear Information System (INIS)

    Kastis, George A.; Gaitanis, Anastasios; Samartzis, Alexandros P.; Fokas, Athanasios S.

    2015-01-01

    Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of 18 F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT

  9. Novel automated inversion algorithm for temperature reconstruction using gas isotopes from ice cores

    Directory of Open Access Journals (Sweden)

    M. Döring

    2018-06-01

    Full Text Available Greenland past temperature history can be reconstructed by forcing the output of a firn-densification and heat-diffusion model to fit multiple gas-isotope data (δ15N or δ40Ar or δ15Nexcess extracted from ancient air in Greenland ice cores using published accumulation-rate (Acc datasets. We present here a novel methodology to solve this inverse problem, by designing a fully automated algorithm. To demonstrate the performance of this novel approach, we begin by intentionally constructing synthetic temperature histories and associated δ15N datasets, mimicking real Holocene data that we use as true values (targets to be compared to the output of the algorithm. This allows us to quantify uncertainties originating from the algorithm itself. The presented approach is completely automated and therefore minimizes the subjective impact of manual parameter tuning, leading to reproducible temperature estimates. In contrast to many other ice-core-based temperature reconstruction methods, the presented approach is completely independent from ice-core stable-water isotopes, providing the opportunity to validate water-isotope-based reconstructions or reconstructions where water isotopes are used together with δ15N or δ40Ar. We solve the inverse problem T(δ15N, Acc by using a combination of a Monte Carlo based iterative approach and the analysis of remaining mismatches between modelled and target data, based on cubic-spline filtering of random numbers and the laboratory-determined temperature sensitivity for nitrogen isotopes. Additionally, the presented reconstruction approach was tested by fitting measured δ40Ar and δ15Nexcess data, which led as well to a robust agreement between modelled and measured data. The obtained final mismatches follow a symmetric standard-distribution function. For the study on synthetic data, 95 % of the mismatches compared to the synthetic target data are in an envelope between 3.0 to 6.3 permeg for δ15N and 0.23 to 0

  10. Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging

    Science.gov (United States)

    Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar

    2015-01-01

    Diffusion Spectrum Imaging (DSI) reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation (TV) transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using Matlab running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using Principal Component Analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466

  11. Backtracking algorithm for lepton reconstruction with HADES

    International Nuclear Information System (INIS)

    Sellheim, P

    2015-01-01

    The High Acceptance Di-Electron Spectrometer (HADES) at the GSI Helmholtzzentrum für Schwerionenforschung investigates dilepton and strangeness production in elementary and heavy-ion collisions. In April - May 2012 HADES recorded 7 billion Au+Au events at a beam energy of 1.23 GeV/u with the highest multiplicities measured so far. The track reconstruction and particle identification in the high track density environment are challenging. The most important detector component for lepton identification is the Ring Imaging Cherenkov detector. Its main purpose is the separation of electrons and positrons from large background of charged hadrons produced in heavy-ion collisions. In order to improve lepton identification this backtracking algorithm was developed. In this contribution we will show the results of the algorithm compared to the currently applied method for e +/- identification. Efficiency and purity of a reconstructed e +/- sample will be discussed as well. (paper)

  12. A parallel implementation of a maximum entropy reconstruction algorithm for PET images in a visual language

    Energy Technology Data Exchange (ETDEWEB)

    Bastiens, K; Lemahieu, I [University of Ghent - ELIS Department, St. Pietersnieuwstraat 41, B-9000 Ghent (Belgium)

    1994-12-31

    The application of a maximum entropy reconstruction algorithm to PET images requires a lot of computing resources. A parallel implementation could seriously reduce the execution time. However, programming a parallel application is still a non trivial task, needing specialized people. In this paper a programming environment based on a visual programming language is used for a parallel implementation of the reconstruction algorithm. This programming environment allows less experienced programmers to use the performance of multiprocessor systems. (authors). 8 refs, 3 figs, 1 tab.

  13. Computed laminography and reconstruction algorithm

    International Nuclear Information System (INIS)

    Que Jiemin; Cao Daquan; Zhao Wei; Tang Xiao

    2012-01-01

    Computed laminography (CL) is an alternative to computed tomography if large objects are to be inspected with high resolution. This is especially true for planar objects. In this paper, we set up a new scanning geometry for CL, and study the algebraic reconstruction technique (ART) for CL imaging. We compare the results of ART with variant weighted functions by computer simulation with a digital phantom. It proves that ART algorithm is a good choice for the CL system. (authors)

  14. GNSS troposphere tomography based on two-step reconstructions using GPS observations and COSMIC profiles

    Directory of Open Access Journals (Sweden)

    P. Xia

    2013-10-01

    Full Text Available Traditionally, balloon-based radiosonde soundings are used to study the spatial distribution of atmospheric water vapour. However, this approach cannot be frequently employed due to its high cost. In contrast, GPS tomography technique can obtain water vapour in a high temporal resolution. In the tomography technique, an iterative or non-iterative reconstruction algorithm is usually utilised to overcome rank deficiency of observation equations for water vapour inversion. However, the single iterative or non-iterative reconstruction algorithm has their limitations. For instance, the iterative reconstruction algorithm requires accurate initial values of water vapour while the non-iterative reconstruction algorithm needs proper constraint conditions. To overcome these drawbacks, we present a combined iterative and non-iterative reconstruction approach for the three-dimensional (3-D water vapour inversion using GPS observations and COSMIC profiles. In this approach, the non-iterative reconstruction algorithm is first used to estimate water vapour density based on a priori water vapour information derived from COSMIC radio occultation data. The estimates are then employed as initial values in the iterative reconstruction algorithm. The largest advantage of this approach is that precise initial values of water vapour density that are essential in the iterative reconstruction algorithm can be obtained. This combined reconstruction algorithm (CRA is evaluated using 10-day GPS observations in Hong Kong and COSMIC profiles. The test results indicate that the water vapor accuracy from CRA is 16 and 14% higher than that of iterative and non-iterative reconstruction approaches, respectively. In addition, the tomography results obtained from the CRA are further validated using radiosonde data. Results indicate that water vapour densities derived from the CRA agree with radiosonde results very well at altitudes above 2.5 km. The average RMS value of their

  15. Principle and Reconstruction Algorithm for Atomic-Resolution Holography

    Science.gov (United States)

    Matsushita, Tomohiro; Muro, Takayuki; Matsui, Fumihiko; Happo, Naohisa; Hosokawa, Shinya; Ohoyama, Kenji; Sato-Tomita, Ayana; Sasaki, Yuji C.; Hayashi, Kouichi

    2018-06-01

    Atomic-resolution holography makes it possible to obtain the three-dimensional (3D) structure around a target atomic site. Translational symmetry of the atomic arrangement of the sample is not necessary, and the 3D atomic image can be measured when the local structure of the target atomic site is oriented. Therefore, 3D local atomic structures such as dopants and adsorbates are observable. Here, the atomic-resolution holography comprising photoelectron holography, X-ray fluorescence holography, neutron holography, and their inverse modes are treated. Although the measurement methods are different, they can be handled with a unified theory. The algorithm for reconstructing 3D atomic images from holograms plays an important role. Although Fourier transform-based methods have been proposed, they require the multiple-energy holograms. In addition, they cannot be directly applied to photoelectron holography because of the phase shift problem. We have developed methods based on the fitting method for reconstructing from single-energy and photoelectron holograms. The developed methods are applicable to all types of atomic-resolution holography.

  16. Inference-Based Surface Reconstruction of Cluttered Environments

    KAUST Repository

    Biggers, K.

    2012-08-01

    We present an inference-based surface reconstruction algorithm that is capable of identifying objects of interest among a cluttered scene, and reconstructing solid model representations even in the presence of occluded surfaces. Our proposed approach incorporates a predictive modeling framework that uses a set of user-provided models for prior knowledge, and applies this knowledge to the iterative identification and construction process. Our approach uses a local to global construction process guided by rules for fitting high-quality surface patches obtained from these prior models. We demonstrate the application of this algorithm on several example data sets containing heavy clutter and occlusion. © 2012 IEEE.

  17. Compressed Sensing, Pseudodictionary-Based, Superresolution Reconstruction

    Directory of Open Access Journals (Sweden)

    Chun-mei Li

    2016-01-01

    Full Text Available The spatial resolution of digital images is the critical factor that affects photogrammetry precision. Single-frame, superresolution, image reconstruction is a typical underdetermined, inverse problem. To solve this type of problem, a compressive, sensing, pseudodictionary-based, superresolution reconstruction method is proposed in this study. The proposed method achieves pseudodictionary learning with an available low-resolution image and uses the K-SVD algorithm, which is based on the sparse characteristics of the digital image. Then, the sparse representation coefficient of the low-resolution image is obtained by solving the norm of l0 minimization problem, and the sparse coefficient and high-resolution pseudodictionary are used to reconstruct image tiles with high resolution. Finally, single-frame-image superresolution reconstruction is achieved. The proposed method is applied to photogrammetric images, and the experimental results indicate that the proposed method effectively increase image resolution, increase image information content, and achieve superresolution reconstruction. The reconstructed results are better than those obtained from traditional interpolation methods in aspect of visual effects and quantitative indicators.

  18. Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

    Science.gov (United States)

    Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang-Hee

    2014-03-01

    State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time.

  19. A fast method to emulate an iterative POCS image reconstruction algorithm.

    Science.gov (United States)

    Zeng, Gengsheng L

    2017-10-01

    Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. © 2017 American Association of Physicists in Medicine.

  20. A three-dimensional-weighted cone beam filtered backprojection (CB-FBP) algorithm for image reconstruction in volumetric CT-helical scanning

    International Nuclear Information System (INIS)

    Tang Xiangyang; Hsieh Jiang; Nilsen, Roy A; Dutta, Sandeep; Samsonov, Dmitry; Hagiwara, Akira

    2006-01-01

    Based on the structure of the original helical FDK algorithm, a three-dimensional (3D)-weighted cone beam filtered backprojection (CB-FBP) algorithm is proposed for image reconstruction in volumetric CT under helical source trajectory. In addition to its dependence on view and fan angles, the 3D weighting utilizes the cone angle dependency of a ray to improve reconstruction accuracy. The 3D weighting is ray-dependent and the underlying mechanism is to give a favourable weight to the ray with the smaller cone angle out of a pair of conjugate rays but an unfavourable weight to the ray with the larger cone angle out of the conjugate ray pair. The proposed 3D-weighted helical CB-FBP reconstruction algorithm is implemented in the cone-parallel geometry that can improve noise uniformity and image generation speed significantly. Under the cone-parallel geometry, the filtering is naturally carried out along the tangential direction of the helical source trajectory. By exploring the 3D weighting's dependence on cone angle, the proposed helical 3D-weighted CB-FBP reconstruction algorithm can provide significantly improved reconstruction accuracy at moderate cone angle and high helical pitches. The 3D-weighted CB-FBP algorithm is experimentally evaluated by computer-simulated phantoms and phantoms scanned by a diagnostic volumetric CT system with a detector dimension of 64 x 0.625 mm over various helical pitches. The computer simulation study shows that the 3D weighting enables the proposed algorithm to reach reconstruction accuracy comparable to that of exact CB reconstruction algorithms, such as the Katsevich algorithm, under a moderate cone angle (4 deg.) and various helical pitches. Meanwhile, the experimental evaluation using the phantoms scanned by a volumetric CT system shows that the spatial resolution along the z-direction and noise characteristics of the proposed 3D-weighted helical CB-FBP reconstruction algorithm are maintained very well in comparison to the FDK

  1. Algorithm of hadron energy reconstruction for combined calorimeters in the DELPHI detector

    International Nuclear Information System (INIS)

    Gotra, Yu.N.; Tsyganov, E.N.; Zimin, N.I.; Zinchenko, A.I.

    1989-01-01

    The algorithm of hadron energy reconstruction from responses of electromagnetic and hadron calorimeters is described. The investigations have been carried out using the full-scale prototype of the hadron calorimeter cylindrical part modules. The supposed algorithm allows one to improve energy resolution by 5-7% with conserving the linearly of reconstructed hadron energy. 5 refs.; 4 figs.; 1 tab

  2. Statistical image reconstruction for transmission tomography using relaxed ordered subset algorithms

    International Nuclear Information System (INIS)

    Kole, J S

    2005-01-01

    Statistical reconstruction methods offer possibilities for improving image quality as compared to analytical methods, but current reconstruction times prohibit routine clinical applications in x-ray computed tomography (CT). To reduce reconstruction times, we have applied (under) relaxation to ordered subset algorithms. This enables us to use subsets consisting of only single projection angle, effectively increasing the number of image updates within an entire iteration. A second advantage of applying relaxation is that it can help improve convergence by removing the limit cycle behaviour of ordered subset algorithms, which normally do not converge to an optimal solution but rather a suboptimal limit cycle consisting of as many points as there are subsets. Relaxation suppresses the limit cycle behaviour by decreasing the stepsize for approaching the solution. A simulation study for a 2D mathematical phantom and three different ordered subset algorithms shows that all three algorithms benefit from relaxation: equal noise-to-resolution trade-off can be achieved using fewer iterations than the conventional algorithms, while a lower minimal normalized mean square error (NMSE) clearly indicates a better convergence. Two different schemes for setting the relaxation parameter are studied, and both schemes yield approximately the same minimal NMSE

  3. Magneto-acousto-electrical Measurement Based Electrical Conductivity Reconstruction for Tissues.

    Science.gov (United States)

    Zhou, Yan; Ma, Qingyu; Guo, Gepu; Tu, Juan; Zhang, Dong

    2018-05-01

    Based on the interaction of ultrasonic excitation and magnetoelectrical induction, magneto-acousto-electrical (MAE) technology was demonstrated to have the capability of differentiating conductivity variations along the acoustic transmission. By applying the characteristics of the MAE voltage, a simplified algorithm of MAE measurement based conductivity reconstruction was developed. With the analyses of acoustic vibration, ultrasound propagation, Hall effect, and magnetoelectrical induction, theoretical and experimental studies of MAE measurement and conductivity reconstruction were performed. The formula of MAE voltage was derived and simplified for the transducer with strong directivity. MAE voltage was simulated for a three-layer gel phantom and the conductivity distribution was reconstructed using the modified Wiener inverse filter and Hilbert transform, which was also verified by experimental measurements. The experimental results are basically consistent with the simulations, and demonstrate that the wave packets of MAE voltage are generated at tissue interfaces with the amplitudes and vibration polarities representing the values and directions of conductivity variations. With the proposed algorithm, the amplitude and polarity of conductivity gradient can be restored and the conductivity distribution can also be reconstructed accurately. The favorable results demonstrate the feasibility of accurate conductivity reconstruction with improved spatial resolution using MAE measurement for tissues with conductivity variations, especially suitable for nondispersive tissues with abrupt conductivity changes. This study demonstrates that the MAE measurement based conductivity reconstruction algorithm can be applied as a new strategy for nondestructive real-time monitoring of conductivity variations in biomedical engineering.

  4. Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

    Science.gov (United States)

    Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

    2015-11-01

    The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of

  5. Fast neural-net based fake track rejection in the LHCb reconstruction

    CERN Document Server

    De Cian, Michel; Seyfert, Paul; Stahl, Sascha

    2017-01-01

    A neural-network based algorithm to identify fake tracks in the LHCb pattern recognition is presented. This algorithm, called ghost probability, retains more than 99 % of well reconstructed tracks while reducing the number of fake tracks by 60 %. It is fast enough to fit into the CPU time budget of the software trigger farm and thus reduces the combinatorics of the decay reconstructions, as well as the number of tracks that need to be processed by the particle identification algorithms. As a result, it strongly contributes to the achievement of having the same reconstruction online and offline in the LHCb experiment in Run II of the LHC.

  6. A fast image reconstruction technique based on ART

    International Nuclear Information System (INIS)

    Zhang Shunli; Zhang Dinghua; Wang Kai; Huang Kuidong; Li Weibin

    2007-01-01

    Algebraic Reconstruction Technique (ART) is an iterative method for image reconstruction. Improving its reconstruction speed has been one of the important researching aspects of ART. For the simplified weight coefficients reconstruction model of ART, a fast grid traverse algorithm is proposed, which can determine the grid index by simple operations such as addition, subtraction and comparison. Since the weight coefficients are calculated at real time during iteration, large amount of storage is saved and the reconstruction speed is greatly increased. Experimental results show that the new algorithm is very effective and the reconstruction speed is improved about 10 times compared with the traditional algorithm. (authors)

  7. Image Reconstruction Algorithm For Electrical Capacitance Tomography (ECT)

    International Nuclear Information System (INIS)

    Arko

    2001-01-01

    ). Most image reconstruction algorithms for electrical capacitance tomography (ECT) use sensitivity maps as weighting factors. The computation is fast, involving a simple multiply-and- accumulate (MAC) operation, but the resulting image suffers from blurring due to the soft-field effect of the sensor. This paper presents a low cost iterative method employing proportional thresholding, which improves image quality dramatically. The strategy for implementation, computational cost, and achievable speed is examined when using a personal computer (PC) and Digital Signal Processor (DSP). For PC implementation, Watcom C++ 10.6 and Visual C++ 5.0 compilers were used. The experimental results are compared to the images reconstructed by commercially available software. The new algorithm improves the image quality significantly at a cost of a few iterations. This technique can be readily exploited for online applications

  8. An ART iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging

    International Nuclear Information System (INIS)

    Wang Zhentian; Zhang Li; Huang Zhifeng; Kang Kejun; Chen Zhiqiang; Fang Qiaoguang; Zhu Peiping

    2009-01-01

    X-ray diffraction enhanced imaging (DEI) has extremely high sensitivity for weakly absorbing low-Z samples in medical and biological fields. In this paper, we propose an Algebra Reconstruction Technique (ART) iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging (DEI-CT). An Ordered Subsets (OS) technique is used to accelerate the ART reconstruction. Few-view reconstruction is also studied, and a partial differential equation (PDE) type filter which has the ability of edge-preserving and denoising is used to improve the image quality and eliminate the artifacts. The proposed algorithm is validated with both the numerical simulations and the experiment at the Beijing synchrotron radiation facility (BSRF). (authors)

  9. Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms

    Science.gov (United States)

    Clapuyt, Francois; Vanacker, Veerle; Van Oost, Kristof

    2016-05-01

    Combination of UAV-based aerial pictures and Structure-from-Motion (SfM) algorithm provides an efficient, low-cost and rapid framework for remote sensing and monitoring of dynamic natural environments. This methodology is particularly suitable for repeated topographic surveys in remote or poorly accessible areas. However, temporal analysis of landform topography requires high accuracy of measurements and reproducibility of the methodology as differencing of digital surface models leads to error propagation. In order to assess the repeatability of the SfM technique, we surveyed a study area characterized by gentle topography with an UAV platform equipped with a standard reflex camera, and varied the focal length of the camera and location of georeferencing targets between flights. Comparison of different SfM-derived topography datasets shows that precision of measurements is in the order of centimetres for identical replications which highlights the excellent performance of the SfM workflow, all parameters being equal. The precision is one order of magnitude higher for 3D topographic reconstructions involving independent sets of ground control points, which results from the fact that the accuracy of the localisation of ground control points strongly propagates into final results.

  10. X-ray dose reduction in abdominal computed tomography using advanced iterative reconstruction algorithms.

    Directory of Open Access Journals (Sweden)

    Peigang Ning

    Full Text Available OBJECTIVE: This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR and model-based iterative reconstruction (MBIR algorithms in reducing computed tomography (CT radiation dosages in abdominal imaging. METHODS: CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP, 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol were recorded. RESULTS: At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. CONCLUSIONS: Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.

  11. A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.

    Science.gov (United States)

    De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc

    2010-09-01

    In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.

  12. A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging.

    Science.gov (United States)

    Yan, Hao; Zhen, Xin; Folkerts, Michael; Li, Yongbao; Pan, Tinsu; Cervino, Laura; Jiang, Steve B; Jia, Xun

    2014-07-01

    4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3-0.5 mm for patients 1-3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1-1.5 min per phase. High-quality 4D-CBCT imaging based

  13. A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Yan, Hao; Folkerts, Michael; Jiang, Steve B., E-mail: xun.jia@utsouthwestern.edu, E-mail: steve.jiang@UTSouthwestern.edu; Jia, Xun, E-mail: xun.jia@utsouthwestern.edu, E-mail: steve.jiang@UTSouthwestern.edu [Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390 (United States); Zhen, Xin [Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515 (China); Li, Yongbao [Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390 and Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Pan, Tinsu [Department of Imaging Physics, The University of Texas, MD Anderson Cancer Center, Houston, Texas 77030 (United States); Cervino, Laura [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States)

    2014-07-15

    Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3–0.5 mm for patients 1–3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1–1.5 min per phase

  14. Identifying Septal Support Reconstructions for Saddle Nose Deformity: The Cakmak Algorithm.

    Science.gov (United States)

    Cakmak, Ozcan; Emre, Ismet Emrah; Ozkurt, Fazil Emre

    2015-01-01

    The saddle nose deformity is one of the most challenging problems in nasal surgery with a less predictable and reproducible result than other nasal procedures. The main feature of this deformity is loss of septal support with both functional and aesthetic implications. Most reports on saddle nose have focused on aesthetic improvement and neglected the reestablishment of septal support to improve airway. To explain how the Cakmak algorithm, an algorithm that describes various fixation techniques and grafts in different types of saddle nose deformities, aids in identifying saddle nose reconstructions that restore supportive nasal framework and provide the aesthetic improvements typically associated with procedures to correct saddle nose deformities. This algorithm presents septal support reconstruction of patients with saddle nose deformity based on the experience of the senior author in 206 patients with saddle nose deformity. Preoperative examination, intraoperative assessment, reconstruction techniques, graft materials, and patient evaluation of aesthetic success were documented, and 4 different types of saddle nose deformities were defined. The Cakmak algorithm classifies varying degrees of saddle nose deformity from type 0 to type 4 and helps identify the most appropriate surgical procedure to restore the supportive nasal framework and aesthetic dorsum. Among the 206 patients, 110 women and 96 men, mean (range) age was 39.7 years (15-68 years), and mean (range) of follow-up was 32 months (6-148 months). All but 12 patients had a history of previous nasal surgeries. Application of the Cakmak algorithm resulted in 36 patients categorized with type 0 saddle nose deformities; 79, type 1; 50, type 2; 20, type 3a; 7, type 3b; and 14, type 4. Postoperative photographs showed improvement of deformities, and patient surveys revealed aesthetic improvement in 201 patients and improvement in nasal breathing in 195 patients. Three patients developed postoperative infection

  15. Honey bee-inspired algorithms for SNP haplotype reconstruction problem

    Science.gov (United States)

    PourkamaliAnaraki, Maryam; Sadeghi, Mehdi

    2016-03-01

    Reconstructing haplotypes from SNP fragments is an important problem in computational biology. There have been a lot of interests in this field because haplotypes have been shown to contain promising data for disease association research. It is proved that haplotype reconstruction in Minimum Error Correction model is an NP-hard problem. Therefore, several methods such as clustering techniques, evolutionary algorithms, neural networks and swarm intelligence approaches have been proposed in order to solve this problem in appropriate time. In this paper, we have focused on various evolutionary clustering techniques and try to find an efficient technique for solving haplotype reconstruction problem. It can be referred from our experiments that the clustering methods relying on the behaviour of honey bee colony in nature, specifically bees algorithm and artificial bee colony methods, are expected to result in more efficient solutions. An application program of the methods is available at the following link. http://www.bioinf.cs.ipm.ir/software/haprs/

  16. Tensor-based dictionary learning for dynamic tomographic reconstruction

    International Nuclear Information System (INIS)

    Tan, Shengqi; Wu, Zhifang; Zhang, Yanbo; Mou, Xuanqin; Wang, Ge; Cao, Guohua; Yu, Hengyong

    2015-01-01

    In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. (paper)

  17. Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction

    Science.gov (United States)

    Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong

    2015-01-01

    In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991

  18. Improved adaptive genetic algorithm with sparsity constraint applied to thermal neutron CT reconstruction of two-phase flow

    Science.gov (United States)

    Yan, Mingfei; Hu, Huasi; Otake, Yoshie; Taketani, Atsushi; Wakabayashi, Yasuo; Yanagimachi, Shinzo; Wang, Sheng; Pan, Ziheng; Hu, Guang

    2018-05-01

    Thermal neutron computer tomography (CT) is a useful tool for visualizing two-phase flow due to its high imaging contrast and strong penetrability of neutrons for tube walls constructed with metallic material. A novel approach for two-phase flow CT reconstruction based on an improved adaptive genetic algorithm with sparsity constraint (IAGA-SC) is proposed in this paper. In the algorithm, the neighborhood mutation operator is used to ensure the continuity of the reconstructed object. The adaptive crossover probability P c and mutation probability P m are improved to help the adaptive genetic algorithm (AGA) achieve the global optimum. The reconstructed results for projection data, obtained from Monte Carlo simulation, indicate that the comprehensive performance of the IAGA-SC algorithm exceeds the adaptive steepest descent-projection onto convex sets (ASD-POCS) algorithm in restoring typical and complex flow regimes. It especially shows great advantages in restoring the simply connected flow regimes and the shape of object. In addition, the CT experiment for two-phase flow phantoms was conducted on the accelerator-driven neutron source to verify the performance of the developed IAGA-SC algorithm.

  19. TauFinder: A Reconstruction Algorithm for τ Leptons at Linear Colliders

    CERN Document Server

    Muennich, A

    2010-01-01

    An algorithm to find and reconstruct τ leptons was developed, which targets τs that produce high energetic, low multiplicity jets as can be observed at multi TeV e+e− collisions. However, it makes no assumption about the decay of the τ candidate thus finding hadronic as well as leptonic decays. The algorithm delivers a reconstructed τ as seen by the detector. This note provides an overview of the algorithm, the cuts used and gives some evaluation of the performance. A first implementation is available within the ILC software framework as a MAR- LIN processor . Appendix A is intended as a short user manual.

  20. Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

    Science.gov (United States)

    Goolsby, Eric W

    2017-04-01

    Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non-Brownian models, missing data, and within-species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time-consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000-species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within-species variation, non-Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time-consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation-Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars

  1. Reconstruction of a uniform star object from interior x-ray data: uniqueness, stability and algorithm

    International Nuclear Information System (INIS)

    Van Gompel, Gert; Batenburg, K Joost; Defrise, Michel

    2009-01-01

    In this paper we consider the problem of reconstructing a two-dimensional star-shaped object of uniform density from truncated projections of the object. In particular, we prove that such an object is uniquely determined by its parallel projections sampled over a full π angular range with a detector that only covers an interior field-of-view, even if the density of the object is not known a priori. We analyze the stability of this reconstruction problem and propose a reconstruction algorithm. Simulation experiments demonstrate that the algorithm is capable of reconstructing a star-shaped object from interior data, even if the interior region is much smaller than the size of the object. In addition, we present results for a heuristic reconstruction algorithm called DART, that was recently proposed. The heuristic method is shown to yield accurate reconstructions if the density is known in advance, and to have a very good stability in the presence of noisy projection data. Finally, the performance of the DBP and DART algorithms is illustrated for the reconstruction of real micro-CT data of a diamond

  2. A joint Richardson—Lucy deconvolution algorithm for the reconstruction of multifocal structured illumination microscopy data

    International Nuclear Information System (INIS)

    Ströhl, Florian; Kaminski, Clemens F

    2015-01-01

    We demonstrate the reconstruction of images obtained by multifocal structured illumination microscopy, MSIM, using a joint Richardson–Lucy, jRL-MSIM, deconvolution algorithm, which is based on an underlying widefield image-formation model. The method is efficient in the suppression of out-of-focus light and greatly improves image contrast and resolution. Furthermore, it is particularly well suited for the processing of noise corrupted data. The principle is verified on simulated as well as experimental data and a comparison of the jRL-MSIM approach with the standard reconstruction procedure, which is based on image scanning microscopy, ISM, is made. Our algorithm is efficient and freely available in a user friendly software package. (paper)

  3. Optimization of the muon reconstruction algorithms for LHCb Run 2

    CERN Document Server

    Aaij, Roel; Dettori, Francesco; Dungs, Kevin; Lopes, Helder; Martinez Santos, Diego; Prisciandaro, Jessica; Sciascia, Barbara; Syropoulos, Vasileios; Stahl, Sascha; Vazquez Gomez, Ricardo

    2017-01-01

    The muon identification algorithm in the LHCb HLT software trigger and offline reconstruction has been revisited in view of the LHC Run 2. This software has undergone a significant refactorisation, resulting in a modularized common code base between the HLT and offline event processing. Because of the latter, the muon identification is now identical in HLT and offline. The HLT1 algorithm sequence has been updated given the new rate and timing constraints. Also, information from the TT subdetector is used in order to reduce ghost tracks and optimize for low $p_T$ muons. The current software is presented here together with performance studies showing improved efficiencies and reduced timing.

  4. ℓ0 Gradient Minimization Based Image Reconstruction for Limited-Angle Computed Tomography.

    Directory of Open Access Journals (Sweden)

    Wei Yu

    Full Text Available In medical and industrial applications of computed tomography (CT imaging, limited by the scanning environment and the risk of excessive X-ray radiation exposure imposed to the patients, reconstructing high quality CT images from limited projection data has become a hot topic. X-ray imaging in limited scanning angular range is an effective imaging modality to reduce the radiation dose to the patients. As the projection data available in this modality are incomplete, limited-angle CT image reconstruction is actually an ill-posed inverse problem. To solve the problem, image reconstructed by conventional filtered back projection (FBP algorithm frequently results in conspicuous streak artifacts and gradual changed artifacts nearby edges. Image reconstruction based on total variation minimization (TVM can significantly reduce streak artifacts in few-view CT, but it suffers from the gradual changed artifacts nearby edges in limited-angle CT. To suppress this kind of artifacts, we develop an image reconstruction algorithm based on ℓ0 gradient minimization for limited-angle CT in this paper. The ℓ0-norm of the image gradient is taken as the regularization function in the framework of developed reconstruction model. We transformed the optimization problem into a few optimization sub-problems and then, solved these sub-problems in the manner of alternating iteration. Numerical experiments are performed to validate the efficiency and the feasibility of the developed algorithm. From the statistical analysis results of the performance evaluations peak signal-to-noise ratio (PSNR and normalized root mean square distance (NRMSD, it shows that there are significant statistical differences between different algorithms from different scanning angular ranges (p<0.0001. From the experimental results, it also indicates that the developed algorithm outperforms classical reconstruction algorithms in suppressing the streak artifacts and the gradual changed

  5. A new simple iterative reconstruction algorithm for SPECT transmission measurement

    International Nuclear Information System (INIS)

    Hwang, D.S.; Zeng, G.L.

    2005-01-01

    This paper proposes a new iterative reconstruction algorithm for transmission tomography and compares this algorithm with several other methods. The new algorithm is simple and resembles the emission ML-EM algorithm in form. Due to its simplicity, it is easy to implement and fast to compute a new update at each iteration. The algorithm also always guarantees non-negative solutions. Evaluations are performed using simulation studies and real phantom data. Comparisons with other algorithms such as convex, gradient, and logMLEM show that the proposed algorithm is as good as others and performs better in some cases

  6. Direct cone-beam cardiac reconstruction algorithm with cardiac banding artifact correction

    International Nuclear Information System (INIS)

    Taguchi, Katsuyuki; Chiang, Beshan S.; Hein, Ilmar A.

    2006-01-01

    Multislice helical computed tomography (CT) is a promising noninvasive technique for coronary artery imaging. Various factors can cause inconsistencies in cardiac CT data, which can result in degraded image quality. These inconsistencies may be the result of the patient physiology (e.g., heart rate variations), the nature of the data (e.g., cone-angle), or the reconstruction algorithm itself. An algorithm which provides the best temporal resolution for each slice, for example, often provides suboptimal image quality for the entire volume since the cardiac temporal resolution (TRc) changes from slice to slice. Such variations in TRc can generate strong banding artifacts in multi-planar reconstruction images or three-dimensional images. Discontinuous heart walls and coronary arteries may compromise the accuracy of the diagnosis. A β-blocker is often used to reduce and stabilize patients' heart rate but cannot eliminate the variation. In order to obtain robust and optimal image quality, a software solution that increases the temporal resolution and decreases the effect of heart rate is highly desirable. This paper proposes an ECG-correlated direct cone-beam reconstruction algorithm (TCOT-EGR) with cardiac banding artifact correction (CBC) and disconnected projections redundancy compensation technique (DIRECT). First the theory and analytical model of the cardiac temporal resolution is outlined. Next, the performance of the proposed algorithms is evaluated by using computer simulations as well as patient data. It will be shown that the proposed algorithms enhance the robustness of the image quality against inconsistencies by guaranteeing smooth transition of heart cycles used in reconstruction

  7. Implementations of PI-line based FBP and BPF algorithms on GPGPU

    Energy Technology Data Exchange (ETDEWEB)

    Shen, Le [Tsinghua Univ., Beijing (China). Dept. of Engineering Physics; Xing, Yuxiang [Tsinghua Univ., Beijing (China). Dept. of Engineering Physics; Ministry of Education, Beijing (China). Key Lab. of Particle and Radiation Imaging

    2011-07-01

    Exact reconstruction is under the spotlight in cone beam CT. Katsevich put forward the first exact inversion formula for helical cone beam CT, which belongs to FBP type. Also, Pan Xiaochuan's group proposed another PI-line based exact reconstruction algorithm of BPF type. These two exact reconstruction algorithms and their derivative forms have been widely studied. In this paper, we present a different way of selecting PI-line segments appropriate for both Katsevich's FBP and Pan Xiaochuan's BPF algorithms. As 3D reconstruction contributes to massive computations and takes long time, people have made efforts to speed up the algorithms with the help of multi-core CPUs and GPGPU (General Purpose Graphics Processing Unit). In this paper, we also presents implementations for these two algorithms on GPGPU using an innovative way of selecting PI-line segments. Acceleration techniques and implementations are addressed in detail. The methods are tested on the Shepp-Logan phantom. Compared with our CPU's implementations, the accelerated algorithms on GPGPU are tens to hundreds times faster. (orig.)

  8. Track reconstruction algorithms for the CBM experiment at FAIR

    International Nuclear Information System (INIS)

    Lebedev, Andrey; Hoehne, Claudia; Kisel, Ivan; Ososkov, Gennady

    2010-01-01

    The Compressed Baryonic Matter (CBM) experiment at the future FAIR accelerator complex at Darmstadt is being designed for a comprehensive measurement of hadron and lepton production in heavy-ion collisions from 8-45 AGeV beam energy, producing events with large track multiplicity and high hit density. The setup consists of several detectors including as tracking detectors the silicon tracking system (STS), the muon detector (MUCH) or alternatively a set of Transition Radiation Detectors (TRD). In this contribution, the status of the track reconstruction software including track finding, fitting and propagation is presented for the MUCH and TRD detectors. The track propagation algorithm takes into account an inhomogeneous magnetic field and includes accurate calculation of multiple scattering and energy losses in the detector material. Track parameters and covariance matrices are estimated using the Kalman filter method and a Kalman filter modification by assigning weights to hits and using simulated annealing. Three different track finder algorithms based on track following have been developed which either allow for track branches, just select nearest hits or use the mentioned weighting method. The track reconstruction efficiency for central Au+Au collisions at 25 AGeV beam energy using events from the UrQMD model is at the level of 93-95% for both detectors.

  9. Novel Fourier-based iterative reconstruction for sparse fan projection using alternating direction total variation minimization

    International Nuclear Information System (INIS)

    Jin Zhao; Zhang Han-Ming; Yan Bin; Li Lei; Wang Lin-Yuan; Cai Ai-Long

    2016-01-01

    Sparse-view x-ray computed tomography (CT) imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform (NUFFT) is presented in this work along with advanced total variation (TV) regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively. (paper)

  10. Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

    Science.gov (United States)

    Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

    2013-09-15

    For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

  11. A shape-based quality evaluation and reconstruction method for electrical impedance tomography.

    Science.gov (United States)

    Antink, Christoph Hoog; Pikkemaat, Robert; Malmivuo, Jaakko; Leonhardt, Steffen

    2015-06-01

    Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community. In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed. Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images.

  12. A shape-based quality evaluation and reconstruction method for electrical impedance tomography

    International Nuclear Information System (INIS)

    Antink, Christoph Hoog; Pikkemaat, Robert; Leonhardt, Steffen; Malmivuo, Jaakko

    2015-01-01

    Linear methods of reconstruction play an important role in medical electrical impedance tomography (EIT) and there is a wide variety of algorithms based on several assumptions. With the Graz consensus reconstruction algorithm for EIT (GREIT), a novel linear reconstruction algorithm as well as a standardized framework for evaluating and comparing methods of reconstruction were introduced that found widespread acceptance in the community.In this paper, we propose a two-sided extension of this concept by first introducing a novel method of evaluation. Instead of being based on point-shaped resistivity distributions, we use 2759 pairs of real lung shapes for evaluation that were automatically segmented from human CT data. Necessarily, the figures of merit defined in GREIT were adjusted. Second, a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed.Using our novel method of evaluation, this approach is compared to the classical point-shaped approach. Results show that most figures of merit improve with the use of eigenimages as training data. Moreover, the possibility of tuning the reconstruction by modifying the desired point spread function is shown. Finally, the reconstruction of real EIT data shows that higher contrasts and fewer artifacts can be achieved in ventilation- and perfusion-related images. (paper)

  13. Wobbling and LSF-based maximum likelihood expectation maximization reconstruction for wobbling PET

    International Nuclear Information System (INIS)

    Kim, Hang-Keun; Son, Young-Don; Kwon, Dae-Hyuk; Joo, Yohan; Cho, Zang-Hee

    2016-01-01

    Positron emission tomography (PET) is a widely used imaging modality; however, the PET spatial resolution is not yet satisfactory for precise anatomical localization of molecular activities. Detector size is the most important factor because it determines the intrinsic resolution, which is approximately half of the detector size and determines the ultimate PET resolution. Detector size, however, cannot be made too small because both the decreased detection efficiency and the increased septal penetration effect degrade the image quality. A wobbling and line spread function (LSF)-based maximum likelihood expectation maximization (WL-MLEM) algorithm, which combined the MLEM iterative reconstruction algorithm with wobbled sampling and LSF-based deconvolution using the system matrix, was proposed for improving the spatial resolution of PET without reducing the scintillator or detector size. The new algorithm was evaluated using a simulation, and its performance was compared with that of the existing algorithms, such as conventional MLEM and LSF-based MLEM. Simulations demonstrated that the WL-MLEM algorithm yielded higher spatial resolution and image quality than the existing algorithms. The WL-MLEM algorithm with wobbling PET yielded substantially improved resolution compared with conventional algorithms with stationary PET. The algorithm can be easily extended to other iterative reconstruction algorithms, such as maximum a priori (MAP) and ordered subset expectation maximization (OSEM). The WL-MLEM algorithm with wobbling PET may offer improvements in both sensitivity and resolution, the two most sought-after features in PET design. - Highlights: • This paper proposed WL-MLEM algorithm for PET and demonstrated its performance. • WL-MLEM algorithm effectively combined wobbling and line spread function based MLEM. • WL-MLEM provided improvements in the spatial resolution and the PET image quality. • WL-MLEM can be easily extended to the other iterative

  14. Convergence of Algorithms for Reconstructing Convex Bodies and Directional Measures

    DEFF Research Database (Denmark)

    Gardner, Richard; Kiderlen, Markus; Milanfar, Peyman

    2006-01-01

    We investigate algorithms for reconstructing a convex body K in Rn from noisy measurements of its support function or its brightness function in k directions u1, . . . , uk. The key idea of these algorithms is to construct a convex polytope Pk whose support function (or brightness function) best...

  15. Novel image reconstruction algorithm for multi-phase flow tomography system using γ ray method

    International Nuclear Information System (INIS)

    Hao Kuihong; Wang Huaxiang; Gao Mei

    2007-01-01

    After analyzing the reason of image reconstructed algorithm by using the conventional back projection (IBP) is prone to produce spurious line, and considering the characteristic of multi-phase flow tomography, a novel image reconstruction algorithm is proposed, which carries out the intersection calculation using back projection data. This algorithm can obtain a perfect system point spread function, and can eliminate spurious line better. Simulating results show that the algorithm is effective for identifying multi-phase flow pattern. (authors)

  16. A novel standalone track reconstruction algorithm for the LHCb upgrade

    CERN Multimedia

    Quagliani, Renato

    2018-01-01

    During the LHC Run III, starting in 2020, the instantaneous luminosity of LHCb will be increased up to 2×1033 cm−2 s−1, five times larger than in Run II. The LHCb detector will then have to be upgraded in 2019. In fact, a full software event reconstruction will be performed at the full bunch crossing rate by the trigger, in order to profit of the higher instantaneous luminosity provided by the accelerator. In addition, all the tracking devices will be replaced and, in particular, a scintillating fiber tracker (SciFi) will be installed after the magnet, allowing to cope with the higher occupancy. The new running conditions, and the tighter timing constraints in the software trigger, represent a big challenge for the track reconstruction. This talk presents the design and performance of a novel algorithm that has been developed to reconstruct track segments using solely hits from the SciFi. This algorithm is crucial for the reconstruction of tracks originating from long-lived particles such as KS and Λ. ...

  17. GPU-based Scalable Volumetric Reconstruction for Multi-view Stereo

    Energy Technology Data Exchange (ETDEWEB)

    Kim, H; Duchaineau, M; Max, N

    2011-09-21

    We present a new scalable volumetric reconstruction algorithm for multi-view stereo using a graphics processing unit (GPU). It is an effectively parallelized GPU algorithm that simultaneously uses a large number of GPU threads, each of which performs voxel carving, in order to integrate depth maps with images from multiple views. Each depth map, triangulated from pair-wise semi-dense correspondences, represents a view-dependent surface of the scene. This algorithm also provides scalability for large-scale scene reconstruction in a high resolution voxel grid by utilizing streaming and parallel computation. The output is a photo-realistic 3D scene model in a volumetric or point-based representation. We demonstrate the effectiveness and the speed of our algorithm with a synthetic scene and real urban/outdoor scenes. Our method can also be integrated with existing multi-view stereo algorithms such as PMVS2 to fill holes or gaps in textureless regions.

  18. GPU-based online track reconstruction for PANDA and application to the analysis of D→Kππ

    Energy Technology Data Exchange (ETDEWEB)

    Herten, Andreas

    2015-07-02

    The PANDA experiment is a new hadron physics experiment which is being built for the FAIR facility in Darmstadt, Germany. PANDA will employ a novel scheme of data acquisition: the experiment will reconstruct the full stream of events in realtime to make trigger decisions based on the event topology. An important part of this online event reconstruction is online track reconstruction. Online track reconstruction algorithms need to reconstruct particle trajectories in nearly realtime. This work uses the high-throughput devices of Graphics Processing Units to benchmark different online track reconstruction algorithms. The reconstruction of D{sup ±}→K{sup -+}π{sup ±}π{sup ±} is studied extensively and one online track reconstruction algorithm applied.

  19. TV-constrained incremental algorithms for low-intensity CT image reconstruction

    DEFF Research Database (Denmark)

    Rose, Sean D.; Andersen, Martin S.; Sidky, Emil Y.

    2015-01-01

    constraint can be guided by an image reconstructed by filtered backprojection (FBP). We apply our algorithm to low-dose synchrotron X-ray CT data from the Advanced Photon Source (APS) at Argonne National Labs (ANL) to demonstrate its potential utility. We find that the algorithm provides a means of edge-preserving...

  20. High-speed parallel implementation of a modified PBR algorithm on DSP-based EH topology

    Science.gov (United States)

    Rajan, K.; Patnaik, L. M.; Ramakrishna, J.

    1997-08-01

    Algebraic Reconstruction Technique (ART) is an age-old method used for solving the problem of three-dimensional (3-D) reconstruction from projections in electron microscopy and radiology. In medical applications, direct 3-D reconstruction is at the forefront of investigation. The simultaneous iterative reconstruction technique (SIRT) is an ART-type algorithm with the potential of generating in a few iterations tomographic images of a quality comparable to that of convolution backprojection (CBP) methods. Pixel-based reconstruction (PBR) is similar to SIRT reconstruction, and it has been shown that PBR algorithms give better quality pictures compared to those produced by SIRT algorithms. In this work, we propose a few modifications to the PBR algorithms. The modified algorithms are shown to give better quality pictures compared to PBR algorithms. The PBR algorithm and the modified PBR algorithms are highly compute intensive, Not many attempts have been made to reconstruct objects in the true 3-D sense because of the high computational overhead. In this study, we have developed parallel two-dimensional (2-D) and 3-D reconstruction algorithms based on modified PBR. We attempt to solve the two problems encountered by the PBR and modified PBR algorithms, i.e., the long computational time and the large memory requirements, by parallelizing the algorithm on a multiprocessor system. We investigate the possible task and data partitioning schemes by exploiting the potential parallelism in the PBR algorithm subject to minimizing the memory requirement. We have implemented an extended hypercube (EH) architecture for the high-speed execution of the 3-D reconstruction algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs) and dual-port random access memories (DPR) as channels between the PEs. We discuss and compare the performances of the PBR algorithm on an IBM 6000 RISC workstation, on a Silicon

  1. Derivation and implementation of a cone-beam reconstruction algorithm for nonplanar orbits

    International Nuclear Information System (INIS)

    Kudo, Hiroyuki; Saito, Tsuneo

    1994-01-01

    Smith and Grangeat derived a cone-beam inversion formula that can be applied when a nonplanar orbit satisfying the completeness condition is used. Although Grangeat's inversion formula is mathematically different from Smith's, they have similar overall structures to each other. The contribution of this paper is two-fold. First, based on the derivation of Smith, the authors point out that Grangeat's inversion formula and Smith's can be conveniently described using a single formula (the Smith-Grangeat inversion formula) that is in the form of space-variant filtering followed by cone-beam backprojection. Furthermore, the resulting formula is reformulated for data acquisition systems with a planar detector to obtain a new reconstruction algorithm. Second, the authors make two significant modifications to the new algorithm to reduce artifacts and numerical errors encountered in direct implementation of the new algorithm. As for exactness of the new algorithm, the following fact can be stated. The algorithm based on Grangeat's intermediate function is exact for any complete orbit, whereas that based on Smith's intermediate function should be considered as an approximate inverse excepting the special case where almost every plane in 3-D space meets the orbit. The validity of the new algorithm is demonstrated by simulation studies

  2. Eigenvalue Decomposition-Based Modified Newton Algorithm

    Directory of Open Access Journals (Sweden)

    Wen-jun Wang

    2013-01-01

    Full Text Available When the Hessian matrix is not positive, the Newton direction may not be the descending direction. A new method named eigenvalue decomposition-based modified Newton algorithm is presented, which first takes the eigenvalue decomposition of the Hessian matrix, then replaces the negative eigenvalues with their absolute values, and finally reconstructs the Hessian matrix and modifies the searching direction. The new searching direction is always the descending direction. The convergence of the algorithm is proven and the conclusion on convergence rate is presented qualitatively. Finally, a numerical experiment is given for comparing the convergence domains of the modified algorithm and the classical algorithm.

  3. A First-Order Primal-Dual Reconstruction Algorithm for Few-View SPECT

    DEFF Research Database (Denmark)

    Wolf, Paul; Jørgensen, Jakob Heide; Gilat-Schmidt, Taly

    2012-01-01

    A sparsity-exploiting algorithm intended for few-view Single Photon Emission Computed Tomography (SPECT) reconstruction is proposed and characterized. The algorithm models the object as piecewise constant subject to a blurring operation. Monte Carlo simulations were performed to provide more proj...

  4. Improving head and neck CTA with hybrid and model-based iterative reconstruction techniques

    NARCIS (Netherlands)

    Niesten, J. M.; van der Schaaf, I. C.; Vos, P. C.; Willemink, MJ; Velthuis, B. K.

    2015-01-01

    AIM: To compare image quality of head and neck computed tomography angiography (CTA) reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR) and model-based iterative reconstruction (MIR) algorithms. MATERIALS AND METHODS: The raw data of 34 studies were

  5. A parallel algorithm for 3D particle tracking and Lagrangian trajectory reconstruction

    International Nuclear Information System (INIS)

    Barker, Douglas; Zhang, Yuanhui; Lifflander, Jonathan; Arya, Anshu

    2012-01-01

    Particle-tracking methods are widely used in fluid mechanics and multi-target tracking research because of their unique ability to reconstruct long trajectories with high spatial and temporal resolution. Researchers have recently demonstrated 3D tracking of several objects in real time, but as the number of objects is increased, real-time tracking becomes impossible due to data transfer and processing bottlenecks. This problem may be solved by using parallel processing. In this paper, a parallel-processing framework has been developed based on frame decomposition and is programmed using the asynchronous object-oriented Charm++ paradigm. This framework can be a key step in achieving a scalable Lagrangian measurement system for particle-tracking velocimetry and may lead to real-time measurement capabilities. The parallel tracking algorithm was evaluated with three data sets including the particle image velocimetry standard 3D images data set #352, a uniform data set for optimal parallel performance and a computational-fluid-dynamics-generated non-uniform data set to test trajectory reconstruction accuracy, consistency with the sequential version and scalability to more than 500 processors. The algorithm showed strong scaling up to 512 processors and no inherent limits of scalability were seen. Ultimately, up to a 200-fold speedup is observed compared to the serial algorithm when 256 processors were used. The parallel algorithm is adaptable and could be easily modified to use any sequential tracking algorithm, which inputs frames of 3D particle location data and outputs particle trajectories

  6. An Algorithmic Approach to Total Breast Reconstruction with Free Tissue Transfer

    Directory of Open Access Journals (Sweden)

    Seong Cheol Yu

    2013-05-01

    Full Text Available As microvascular techniques continue to improve, perforator flap free tissue transfer is now the gold standard for autologous breast reconstruction. Various options are available for breast reconstruction with autologous tissue. These include the free transverse rectus abdominis myocutaneous (TRAM flap, deep inferior epigastric perforator flap, superficial inferior epigastric artery flap, superior gluteal artery perforator flap, and transverse/vertical upper gracilis flap. In addition, pedicled flaps can be very successful in the right hands and the right patient, such as the pedicled TRAM flap, latissimus dorsi flap, and thoracodorsal artery perforator. Each flap comes with its own advantages and disadvantages related to tissue properties and donor-site morbidity. Currently, the problem is how to determine the most appropriate flap for a particular patient among those potential candidates. Based on a thorough review of the literature and accumulated experiences in the author’s institution, this article provides a logical approach to autologous breast reconstruction. The algorithms presented here can be helpful to customize breast reconstruction to individual patient needs.

  7. Triggerless Readout with Time and Amplitude Reconstruction of Event Based on Deconvolution Algorithm

    International Nuclear Information System (INIS)

    Kulis, S.; Idzik, M.

    2011-01-01

    In future linear colliders like CLIC, where the period between the bunch crossings is in a sub-nanoseconds range ( 500 ps), an appropriate detection technique with triggerless signal processing is needed. In this work we discuss a technique, based on deconvolution algorithm, suitable for time and amplitude reconstruction of an event. In the implemented method the output of a relatively slow shaper (many bunch crossing periods) is sampled and digitalised in an ADC and then the deconvolution procedure is applied to digital data. The time of an event can be found with a precision of few percent of sampling time. The signal to noise ratio is only slightly decreased after passing through the deconvolution filter. The performed theoretical and Monte Carlo studies are confirmed by the results of preliminary measurements obtained with the dedicated system comprising of radiation source, silicon sensor, front-end electronics, ADC and further digital processing implemented on a PC computer. (author)

  8. Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms

    Science.gov (United States)

    Ott, Julien G.; Becce, Fabio; Monnin, Pascal; Schmidt, Sabine; Bochud, François O.; Verdun, Francis R.

    2014-08-01

    The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

  9. Wavelet-LMS algorithm-based echo cancellers

    Science.gov (United States)

    Seetharaman, Lalith K.; Rao, Sathyanarayana S.

    2002-12-01

    This paper presents Echo Cancellers based on the Wavelet-LMS Algorithm. The performance of the Least Mean Square Algorithm in Wavelet transform domain is observed and its application in Echo cancellation is analyzed. The Widrow-Hoff Least Mean Square Algorithm is most widely used algorithm for Adaptive filters that function as Echo Cancellers. The present day communication signals are widely non-stationary in nature and some errors crop up when Least Mean Square Algorithm is used for the Echo Cancellers handling such signals. The analysis of non-stationary signals often involves a compromise between how well transitions or discontinuities can be located. The multi-scale or multi-resolution of signal analysis, which is the essence of wavelet transform, makes Wavelets popular in non-stationary signal analysis. In this paper, we present a Wavelet-LMS algorithm wherein the wavelet coefficients of a signal are modified adaptively using the Least Mean Square Algorithm and then reconstructed to give an Echo-free signal. The Echo Canceller based on this Algorithm is found to have a better convergence and a comparatively lesser MSE (Mean Square error).

  10. LBP-based penalized weighted least-squares approach to low-dose cone-beam computed tomography reconstruction

    Science.gov (United States)

    Ma, Ming; Wang, Huafeng; Liu, Yan; Zhang, Hao; Gu, Xianfeng; Liang, Zhengrong

    2014-03-01

    Cone-beam computed tomography (CBCT) has attracted growing interest of researchers in image reconstruction. The mAs level of the X-ray tube current, in practical application of CBCT, is mitigated in order to reduce the CBCT dose. The lowering of the X-ray tube current, however, results in the degradation of image quality. Thus, low-dose CBCT image reconstruction is in effect a noise problem. To acquire clinically acceptable quality of image, and keep the X-ray tube current as low as achievable in the meanwhile, some penalized weighted least-squares (PWLS)-based image reconstruction algorithms have been developed. One representative strategy in previous work is to model the prior information for solution regularization using an anisotropic penalty term. To enhance the edge preserving and noise suppressing in a finer scale, a novel algorithm combining the local binary pattern (LBP) with penalized weighted leastsquares (PWLS), called LBP-PWLS-based image reconstruction algorithm, is proposed in this work. The proposed LBP-PWLS-based algorithm adaptively encourages strong diffusion on the local spot/flat region around a voxel and less diffusion on edge/corner ones by adjusting the penalty for cost function, after the LBP is utilized to detect the region around the voxel as spot, flat and edge ones. The LBP-PWLS-based reconstruction algorithm was evaluated using the sinogram data acquired by a clinical CT scanner from the CatPhan® 600 phantom. Experimental results on the noiseresolution tradeoff measurement and other quantitative measurements demonstrated its feasibility and effectiveness in edge preserving and noise suppressing in comparison with a previous PWLS reconstruction algorithm.

  11. Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

    International Nuclear Information System (INIS)

    Xu, Qiaofeng; Sawatzky, Alex; Anastasio, Mark A.; Yang, Deshan; Tan, Jun

    2016-01-01

    Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated

  12. Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

    Science.gov (United States)

    Xu, Qiaofeng; Yang, Deshan; Tan, Jun; Sawatzky, Alex; Anastasio, Mark A.

    2016-01-01

    Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated

  13. Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR).

    Science.gov (United States)

    Notohamiprodjo, S; Deak, Z; Meurer, F; Maertz, F; Mueck, F G; Geyer, L L; Wirth, S

    2015-01-01

    The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p ASiR was 2 (p ASiR (p ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. • Model-Based iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT. • MBIR reconstructed images were rated with significantly higher scores for image quality. • Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.

  14. Experimental study of stochastic noise propagation in SPECT images reconstructed using the conjugate gradient algorithm.

    Science.gov (United States)

    Mariano-Goulart, D; Fourcade, M; Bernon, J L; Rossi, M; Zanca, M

    2003-01-01

    Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.

  15. Design of 4D x-ray tomography experiments for reconstruction using regularized iterative algorithms

    Science.gov (United States)

    Mohan, K. Aditya

    2017-10-01

    4D X-ray computed tomography (4D-XCT) is widely used to perform non-destructive characterization of time varying physical processes in various materials. The conventional approach to improving temporal resolution in 4D-XCT involves the development of expensive and complex instrumentation that acquire data faster with reduced noise. It is customary to acquire data with many tomographic views at a high signal to noise ratio. Instead, temporal resolution can be improved using regularized iterative algorithms that are less sensitive to noise and limited views. These algorithms benefit from optimization of other parameters such as the view sampling strategy while improving temporal resolution by reducing the total number of views or the detector exposure time. This paper presents the design principles of 4D-XCT experiments when using regularized iterative algorithms derived using the framework of model-based reconstruction. A strategy for performing 4D-XCT experiments is presented that allows for improving the temporal resolution by progressively reducing the number of views or the detector exposure time. Theoretical analysis of the effect of the data acquisition parameters on the detector signal to noise ratio, spatial reconstruction resolution, and temporal reconstruction resolution is also presented in this paper.

  16. Extended-Search, Bézier Curve-Based Lane Detection and Reconstruction System for an Intelligent Vehicle

    Directory of Open Access Journals (Sweden)

    Xiaoyun Huang

    2015-09-01

    Full Text Available To improve the real-time performance and detection rate of a Lane Detection and Reconstruction (LDR system, an extended-search-based lane detection method and a Bézier curve-based lane reconstruction algorithm are proposed in this paper. The extended-search-based lane detection method is designed to search boundary blocks from the initial position, in an upwards direction and along the lane, with small search areas including continuous search, discontinuous search and bending search in order to detect different lane boundaries. The Bézier curve-based lane reconstruction algorithm is employed to describe a wide range of lane boundary forms with comparatively simple expressions. In addition, two Bézier curves are adopted to reconstruct the lanes' outer boundaries with large curvature variation. The lane detection and reconstruction algorithm — including initial-blocks' determining, extended search, binarization processing and lane boundaries' fitting in different scenarios — is verified in road tests. The results show that this algorithm is robust against different shadows and illumination variations; the average processing time per frame is 13 ms. Significantly, it presents an 88.6% high-detection rate on curved lanes with large or variable curvatures, where the accident rate is higher than that of straight lanes.

  17. A system for the 3D reconstruction of retracted-septa PET data using the EM algorithm

    International Nuclear Information System (INIS)

    Johnson, C.A.; Yan, Y.; Carson, R.E.; Martino, R.L.; Daube-Witherspoon, M.E.

    1995-01-01

    The authors have implemented the EM reconstruction algorithm for volume acquisition from current generation retracted-septa PET scanners. Although the software was designed for a GE Advance scanner, it is easily adaptable to other 3D scanners. The reconstruction software was written for an Intel iPSC/860 parallel computer with 128 compute nodes. Running on 32 processors, the algorithm requires approximately 55 minutes per iteration to reconstruct a 128 x 128 x 35 image. No projection data compression schemes or other approximations were used in the implementation. Extensive use of EM system matrix (C ij ) symmetries (including the 8-fold in-plane symmetries, 2-fold axial symmetries, and axial parallel line redundancies) reduces the storage cost by a factor of 188. The parallel algorithm operates on distributed projection data which are decomposed by base-symmetry angles. Symmetry operators copy and index the C ij chord to the form required for the particular symmetry. The use of asynchronous reads, lookup tables, and optimized image indexing improves computational performance

  18. Effect of filters and reconstruction algorithms on I-124 PET in Siemens Inveon PET scanner

    Science.gov (United States)

    Ram Yu, A.; Kim, Jin Su

    2015-10-01

    Purpose: To assess the effects of filtering and reconstruction on Siemens I-124 PET data. Methods: A Siemens Inveon PET was used. Spatial resolution of I-124 was measured to a transverse offset of 50 mm from the center FBP, 2D ordered subset expectation maximization (OSEM2D), 3D re-projection algorithm (3DRP), and maximum a posteriori (MAP) methods were tested. Non-uniformity (NU), recovery coefficient (RC), and spillover ratio (SOR) parameterized image quality. Mini deluxe phantom data of I-124 was also assessed. Results: Volumetric resolution was 7.3 mm3 from the transverse FOV center when FBP reconstruction algorithms with ramp filter was used. MAP yielded minimal NU with β =1.5. OSEM2D yielded maximal RC. SOR was below 4% for FBP with ramp, Hamming, Hanning, or Shepp-Logan filters. Based on the mini deluxe phantom results, an FBP with Hanning or Parzen filters, or a 3DRP with Hanning filter yielded feasible I-124 PET data.Conclusions: Reconstruction algorithms and filters were compared. FBP with Hanning or Parzen filters, or 3DRP with Hanning filter yielded feasible data for quantifying I-124 PET.

  19. High resolution reconstruction of PET images using the iterative OSEM algorithm

    International Nuclear Information System (INIS)

    Doll, J.; Bublitz, O.; Werling, A.; Haberkorn, U.; Semmler, W.; Adam, L.E.; Pennsylvania Univ., Philadelphia, PA; Brix, G.

    2004-01-01

    Aim: Improvement of the spatial resolution in positron emission tomography (PET) by incorporation of the image-forming characteristics of the scanner into the process of iterative image reconstruction. Methods: All measurements were performed at the whole-body PET system ECAT EXACT HR + in 3D mode. The acquired 3D sinograms were sorted into 2D sinograms by means of the Fourier rebinning (FORE) algorithm, which allows the usage of 2D algorithms for image reconstruction. The scanner characteristics were described by a spatially variant line-spread function (LSF), which was determined from activated copper-64 line sources. This information was used to model the physical degradation processes in PET measurements during the course of 2D image reconstruction with the iterative OSEM algorithm. To assess the performance of the high-resolution OSEM algorithm, phantom measurements performed at a cylinder phantom, the hotspot Jaszczack phantom, and the 3D Hoffmann brain phantom as well as different patient examinations were analyzed. Results: Scanner characteristics could be described by a Gaussian-shaped LSF with a full-width at half-maximum increasing from 4.8 mm at the center to 5.5 mm at a radial distance of 10.5 cm. Incorporation of the LSF into the iteration formula resulted in a markedly improved resolution of 3.0 and 3.5 mm, respectively. The evaluation of phantom and patient studies showed that the high-resolution OSEM algorithm not only lead to a better contrast resolution in the reconstructed activity distributions but also to an improved accuracy in the quantification of activity concentrations in small structures without leading to an amplification of image noise or even the occurrence of image artifacts. Conclusion: The spatial and contrast resolution of PET scans can markedly be improved by the presented image restauration algorithm, which is of special interest for the examination of both patients with brain disorders and small animals. (orig.)

  20. A theoretically exact reconstruction algorithm for helical cone-beam differential phase-contrast computed tomography

    International Nuclear Information System (INIS)

    Li Jing; Sun Yi; Zhu Peiping

    2013-01-01

    Differential phase-contrast computed tomography (DPC-CT) reconstruction problems are usually solved by using parallel-, fan- or cone-beam algorithms. For rod-shaped objects, the x-ray beams cannot recover all the slices of the sample at the same time. Thus, if a rod-shaped sample is required to be reconstructed by the above algorithms, one should alternately perform translation and rotation on this sample, which leads to lower efficiency. The helical cone-beam CT may significantly improve scanning efficiency for rod-shaped objects over other algorithms. In this paper, we propose a theoretically exact filter-backprojection algorithm for helical cone-beam DPC-CT, which can be applied to reconstruct the refractive index decrement distribution of the samples directly from two-dimensional differential phase-contrast images. Numerical simulations are conducted to verify the proposed algorithm. Our work provides a potential solution for inspecting the rod-shaped samples using DPC-CT, which may be applicable with the evolution of DPC-CT equipments. (paper)

  1. Superiorized algorithm for reconstruction of CT images from sparse-view and limited-angle polyenergetic data

    Science.gov (United States)

    Humphries, T.; Winn, J.; Faridani, A.

    2017-08-01

    Recent work in CT image reconstruction has seen increasing interest in the use of total variation (TV) and related penalties to regularize problems involving reconstruction from undersampled or incomplete data. Superiorization is a recently proposed heuristic which provides an automatic procedure to ‘superiorize’ an iterative image reconstruction algorithm with respect to a chosen objective function, such as TV. Under certain conditions, the superiorized algorithm is guaranteed to find a solution that is as satisfactory as any found by the original algorithm with respect to satisfying the constraints of the problem; this solution is also expected to be superior with respect to the chosen objective. Most work on superiorization has used reconstruction algorithms which assume a linear measurement model, which in the case of CT corresponds to data generated from a monoenergetic x-ray beam. Many CT systems generate x-rays from a polyenergetic spectrum, however, in which the measured data represent an integral of object attenuation over all energies in the spectrum. This inconsistency with the linear model produces the well-known beam hardening artifacts, which impair analysis of CT images. In this work we superiorize an iterative algorithm for reconstruction from polyenergetic data, using both TV and an anisotropic TV (ATV) penalty. We apply the superiorized algorithm in numerical phantom experiments modeling both sparse-view and limited-angle scenarios. In our experiments, the superiorized algorithm successfully finds solutions which are as constraints-compatible as those found by the original algorithm, with significantly reduced TV and ATV values. The superiorized algorithm thus produces images with greatly reduced sparse-view and limited angle artifacts, which are also largely free of the beam hardening artifacts that would be present if a superiorized version of a monoenergetic algorithm were used.

  2. Fast algorithm of track reconstruction for the Delphy TPC

    International Nuclear Information System (INIS)

    Maillard, J.

    1984-01-01

    We describe a simple geometrical method (polar inversion) to reconstruct tracks. When the magnetic field is constant in magnitude and direction. This method uses geometrical properties of the trajectories. In the case of the DELPHI apparatus, the track reconstruction is done using TPC informations. After explaining the algorithm, we give results on ''GEANT'' simulated events using the ''Lund'' generator. Today we get a computer time of the order of 1.2 milliseconds on a CDC 7600 and an efficiency of 98% [fr

  3. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

    DEFF Research Database (Denmark)

    Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    The primal–dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1–26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems...... for the purpose of designing iterative image reconstruction algorithms for CT. The primal–dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application...

  4. Evaluation of proxy-based millennial reconstruction methods

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Terry C.K.; Tsao, Min [University of Victoria, Department of Mathematics and Statistics, Victoria, BC (Canada); Zwiers, Francis W. [Environment Canada, Climate Research Division, Toronto, ON (Canada)

    2008-08-15

    A range of existing statistical approaches for reconstructing historical temperature variations from proxy data are compared using both climate model data and real-world paleoclimate proxy data. We also propose a new method for reconstruction that is based on a state-space time series model and Kalman filter algorithm. The state-space modelling approach and the recently developed RegEM method generally perform better than their competitors when reconstructing interannual variations in Northern Hemispheric mean surface air temperature. On the other hand, a variety of methods are seen to perform well when reconstructing surface air temperature variability on decadal time scales. An advantage of the new method is that it can incorporate additional, non-temperature, information into the reconstruction, such as the estimated response to external forcing, thereby permitting a simultaneous reconstruction and detection analysis as well as future projection. An application of these extensions is also demonstrated in the paper. (orig.)

  5. Gamma regularization based reconstruction for low dose CT

    International Nuclear Information System (INIS)

    Zhang, Junfeng; Chen, Yang; Hu, Yining; Luo, Limin; Shu, Huazhong; Li, Bicao; Liu, Jin; Coatrieux, Jean-Louis

    2015-01-01

    Reducing the radiation in computerized tomography is today a major concern in radiology. Low dose computerized tomography (LDCT) offers a sound way to deal with this problem. However, more severe noise in the reconstructed CT images is observed under low dose scan protocols (e.g. lowered tube current or voltage values). In this paper we propose a Gamma regularization based algorithm for LDCT image reconstruction. This solution is flexible and provides a good balance between the regularizations based on l 0 -norm and l 1 -norm. We evaluate the proposed approach using the projection data from simulated phantoms and scanned Catphan phantoms. Qualitative and quantitative results show that the Gamma regularization based reconstruction can perform better in both edge-preserving and noise suppression when compared with other norms. (paper)

  6. Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

    International Nuclear Information System (INIS)

    Samei, Ehsan; Richard, Samuel

    2015-01-01

    indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks

  7. Assessment of the dose reduction potential of a model-based iterative reconstruction algorithm using a task-based performance metrology

    Energy Technology Data Exchange (ETDEWEB)

    Samei, Ehsan, E-mail: samei@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Clinical Imaging Physics Group, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Medical Physics Graduate Program, Duke University, Durham, North Carolina 27710 (United States); Richard, Samuel [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, Durham, North Carolina 27710 (United States)

    2015-01-15

    indicated a 46%–84% dose reduction potential, depending on task, without compromising the modeled detection performance. Conclusions: The presented methodology based on ACR phantom measurements extends current possibilities for the assessment of CT image quality under the complex resolution and noise characteristics exhibited with statistical and iterative reconstruction algorithms. The findings further suggest that MBIR can potentially make better use of the projections data to reduce CT dose by approximately a factor of 2. Alternatively, if the dose held unchanged, it can improve image quality by different levels for different tasks.

  8. Designing on ICT reconstruction software based on DSP techniques

    International Nuclear Information System (INIS)

    Liu Jinhui; Xiang Xincheng

    2006-01-01

    The convolution back project (CBP) algorithm is used to realize the CT image's reconstruction in ICT generally, which is finished by using PC or workstation. In order to add the ability of multi-platform operation of CT reconstruction software, a CT reconstruction method based on modern digital signal processor (DSP) technique is proposed and realized in this paper. The hardware system based on TI's C6701 DSP processor is selected to support the CT software construction. The CT reconstruction software is compiled only using assembly language related to the DSP hardware. The CT software can be run on TI's C6701 EVM board by inputting the CT data, and can get the CT Images that satisfy the real demands. (authors)

  9. Applicability of a set of tomographic reconstruction algorithms for quantitative SPECT on irradiated nuclear fuel assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Jacobsson Svärd, Staffan, E-mail: staffan.jacobsson_svard@physics.uu.se; Holcombe, Scott; Grape, Sophie

    2015-05-21

    A fuel assembly operated in a nuclear power plant typically contains 100–300 fuel rods, depending on fuel type, which become strongly radioactive during irradiation in the reactor core. For operational and security reasons, it is of interest to experimentally deduce rod-wise information from the fuel, preferably by means of non-destructive measurements. The tomographic SPECT technique offers such possibilities through its two-step application; (1) recording the gamma-ray flux distribution around the fuel assembly, and (2) reconstructing the assembly's internal source distribution, based on the recorded radiation field. In this paper, algorithms for performing the latter step and extracting quantitative relative rod-by-rod data are accounted for. As compared to application of SPECT in nuclear medicine, nuclear fuel assemblies present a much more heterogeneous distribution of internal attenuation to gamma radiation than the human body, typically with rods containing pellets of heavy uranium dioxide surrounded by cladding of a zirconium alloy placed in water or air. This inhomogeneity severely complicates the tomographic quantification of the rod-wise relative source content, and the deduction of conclusive data requires detailed modelling of the attenuation to be introduced in the reconstructions. However, as shown in this paper, simplified models may still produce valuable information about the fuel. Here, a set of reconstruction algorithms for SPECT on nuclear fuel assemblies are described and discussed in terms of their quantitative performance for two applications; verification of fuel assemblies' completeness in nuclear safeguards, and rod-wise fuel characterization. It is argued that a request not to base the former assessment on any a priori information brings constraints to which reconstruction methods that may be used in that case, whereas the use of a priori information on geometry and material content enables highly accurate quantitative

  10. Implementation and evaluation of an ordered subsets reconstruction algorithm for transmission PET studies using median root prior and inter-update median filtering

    International Nuclear Information System (INIS)

    Bettinardi, V.; Gilardi, M.C.; Fazio, F.; Alenius, S.; Ruotsalainen, U.; Numminen, P.; Teraes, M.

    2003-01-01

    An ordered subsets (OS) reconstruction algorithm based on the median root prior (MRP) and inter-update median filtering was implemented for the reconstruction of low count statistics transmission (TR) scans. The OS-MRP-TR algorithm was evaluated using an experimental phantom, simulating positron emission tomography (PET) whole-body (WB) studies, as well as patient data. Various experimental conditions, in terms of TR scan time (from 1 h to 1 min), covering a wide range of TR count statistics were evaluated. The performance of the algorithm was assessed by comparing the mean value of the attenuation coefficient (MVAC) of known tissue types and the coefficient of variation (CV) for low-count TR images, reconstructed with the OS-MRP-TR algorithm, with reference values obtained from high-count TR images reconstructed with a filtered back-projection (FBP) algorithm. The reconstructed OS-MRP-TR images were then used for attenuation correction of the corresponding emission (EM) data. EM images reconstructed with attenuation correction generated by OS-MRP-TR images, of low count statistics, were compared with the EM images corrected for attenuation using reference (high statistics) TR data. In all the experimental situations considered, the OS-MRP-TR algorithm showed: (1) a tendency towards a stable solution in terms of MVAC; (2) a difference in the MVAC of within 5% for a TR scan of 1 min reconstructed with the OS-MRP-TR and a TR scan of 1 h reconstructed with the FBP algorithm; (3) effectiveness in noise reduction, particularly for low count statistics data [using a specific parameter configuration the TR images reconstructed with OS-MRP-TR(1 min) had a lower CV than the corresponding TR images of a 1-h scan reconstructed with the FBP algorithm]; (4) a difference of within 3% between the mean counts in the EM images attenuation corrected using the OS-MRP-TR images of 1 min and the mean counts in the EM images attenuation corrected using the OS-MRP-TR images of 1 h; (5

  11. A Practical Algorithm for Reconstructing Level-1 Phylogenetic Networks

    NARCIS (Netherlands)

    K.T. Huber; L.J.J. van Iersel (Leo); S.M. Kelk (Steven); R. Suchecki

    2010-01-01

    htmlabstractRecently much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks - a type of

  12. A practical algorithm for reconstructing level-1 phylogenetic networks

    NARCIS (Netherlands)

    Huber, K.T.; Iersel, van L.J.J.; Kelk, S.M.; Suchecki, R.

    2011-01-01

    Recently, much attention has been devoted to the construction of phylogenetic networks which generalize phylogenetic trees in order to accommodate complex evolutionary processes. Here, we present an efficient, practical algorithm for reconstructing level-1 phylogenetic networks-a type of network

  13. Hybrid light transport model based bioluminescence tomography reconstruction for early gastric cancer detection

    Science.gov (United States)

    Chen, Xueli; Liang, Jimin; Hu, Hao; Qu, Xiaochao; Yang, Defu; Chen, Duofang; Zhu, Shouping; Tian, Jie

    2012-03-01

    Gastric cancer is the second cause of cancer-related death in the world, and it remains difficult to cure because it has been in late-stage once that is found. Early gastric cancer detection becomes an effective approach to decrease the gastric cancer mortality. Bioluminescence tomography (BLT) has been applied to detect early liver cancer and prostate cancer metastasis. However, the gastric cancer commonly originates from the gastric mucosa and grows outwards. The bioluminescent light will pass through a non-scattering region constructed by gastric pouch when it transports in tissues. Thus, the current BLT reconstruction algorithms based on the approximation model of radiative transfer equation are not optimal to handle this problem. To address the gastric cancer specific problem, this paper presents a novel reconstruction algorithm that uses a hybrid light transport model to describe the bioluminescent light propagation in tissues. The radiosity theory integrated with the diffusion equation to form the hybrid light transport model is utilized to describe light propagation in the non-scattering region. After the finite element discretization, the hybrid light transport model is converted into a minimization problem which fuses an l1 norm based regularization term to reveal the sparsity of bioluminescent source distribution. The performance of the reconstruction algorithm is first demonstrated with a digital mouse based simulation with the reconstruction error less than 1mm. An in situ gastric cancer-bearing nude mouse based experiment is then conducted. The primary result reveals the ability of the novel BLT reconstruction algorithm in early gastric cancer detection.

  14. Fast reconstruction of off-axis digital holograms based on digital spatial multiplexing.

    Science.gov (United States)

    Sha, Bei; Liu, Xuan; Ge, Xiao-Lu; Guo, Cheng-Shan

    2014-09-22

    A method for fast reconstruction of off-axis digital holograms based on digital multiplexing algorithm is proposed. Instead of the existed angular multiplexing (AM), the new method utilizes a spatial multiplexing (SM) algorithm, in which four off-axis holograms recorded in sequence are synthesized into one SM function through multiplying each hologram with a tilted plane wave and then adding them up. In comparison with the conventional methods, the SM algorithm simplifies two-dimensional (2-D) Fourier transforms (FTs) of four N*N arrays into a 1.25-D FTs of one N*N arrays. Experimental results demonstrate that, using the SM algorithm, the computational efficiency can be improved and the reconstructed wavefronts keep the same quality as those retrieved based on the existed AM method. This algorithm may be useful in design of a fast preview system of dynamic wavefront imaging in digital holography.

  15. Variance-based Salt Body Reconstruction

    KAUST Repository

    Ovcharenko, Oleg

    2017-05-26

    Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.

  16. Algorithm Development for Multi-Energy SXR based Electron Temperature Profile Reconstruction

    Science.gov (United States)

    Clayton, D. J.; Tritz, K.; Finkenthal, M.; Kumar, D.; Stutman, D.

    2012-10-01

    New techniques utilizing computational tools such as neural networks and genetic algorithms are being developed to infer plasma electron temperature profiles on fast time scales (> 10 kHz) from multi-energy soft-x-ray (ME-SXR) diagnostics. Traditionally, a two-foil SXR technique, using the ratio of filtered continuum emission measured by two SXR detectors, has been employed on fusion devices as an indirect method of measuring electron temperature. However, these measurements can be susceptible to large errors due to uncertainties in time-evolving impurity density profiles, leading to unreliable temperature measurements. To correct this problem, measurements using ME-SXR diagnostics, which use three or more filtered SXR arrays to distinguish line and continuum emission from various impurities, in conjunction with constraints from spectroscopic diagnostics, can be used to account for unknown or time evolving impurity profiles [K. Tritz et al, Bull. Am. Phys. Soc. Vol. 56, No. 12 (2011), PP9.00067]. On NSTX, ME-SXR diagnostics can be used for fast (10-100 kHz) temperature profile measurements, using a Thomson scattering diagnostic (60 Hz) for periodic normalization. The use of more advanced algorithms, such as neural network processing, can decouple the reconstruction of the temperature profile from spectral modeling.

  17. A general algorithm for the reconstruction of jet events in e+e- annihilation

    International Nuclear Information System (INIS)

    Goddard, M.C.

    1981-01-01

    A general method is described to reconstruct a predetermined number of jets. It can reconstruct the jet axes as accurately as any existing algorithm and is up to one hundred times faster. Results are shown from the reconstruction of 2-jet, 3-jet and 4-jet Monte Carlo events. (author)

  18. Practical algorithms for simulation and reconstruction of digital in-line holograms.

    Science.gov (United States)

    Latychevskaia, Tatiana; Fink, Hans-Werner

    2015-03-20

    Here we present practical methods for simulation and reconstruction of in-line digital holograms recorded with plane and spherical waves. The algorithms described here are applicable to holographic imaging of an object exhibiting absorption as well as phase-shifting properties. Optimal parameters, related to distances, sampling rate, and other factors for successful simulation and reconstruction of holograms are evaluated and criteria for the achievable resolution are worked out. Moreover, we show that the numerical procedures for the reconstruction of holograms recorded with plane and spherical waves are identical under certain conditions. Experimental examples of holograms and their reconstructions are also discussed.

  19. Exact fan-beam image reconstruction algorithm for truncated projection data acquired from an asymmetric half-size detector

    International Nuclear Information System (INIS)

    Leng Shuai; Zhuang Tingliang; Nett, Brian E; Chen Guanghong

    2005-01-01

    In this paper, we present a new algorithm designed for a specific data truncation problem in fan-beam CT. We consider a scanning configuration in which the fan-beam projection data are acquired from an asymmetrically positioned half-sized detector. Namely, the asymmetric detector only covers one half of the scanning field of view. Thus, the acquired fan-beam projection data are truncated at every view angle. If an explicit data rebinning process is not invoked, this data acquisition configuration will reek havoc on many known fan-beam image reconstruction schemes including the standard filtered backprojection (FBP) algorithm and the super-short-scan FBP reconstruction algorithms. However, we demonstrate that a recently developed fan-beam image reconstruction algorithm which reconstructs an image via filtering a backprojection image of differentiated projection data (FBPD) survives the above fan-beam data truncation problem. Namely, we may exactly reconstruct the whole image object using the truncated data acquired in a full scan mode (2π angular range). We may also exactly reconstruct a small region of interest (ROI) using the truncated projection data acquired in a short-scan mode (less than 2π angular range). The most important characteristic of the proposed reconstruction scheme is that an explicit data rebinning process is not introduced. Numerical simulations were conducted to validate the new reconstruction algorithm

  20. A Fourier reconstruction algorithm with constant attenuation compensation using 1800 acquisition data for SPECT

    International Nuclear Information System (INIS)

    Tang Qiulin; Zeng, Gengsheng L; Gullberg, Grant T

    2007-01-01

    In this paper, we develop an approximate analytical reconstruction algorithm that compensates for uniform attenuation in 2D parallel-beam SPECT with a 180 0 acquisition. This new algorithm is in the form of a direct Fourier reconstruction. The complex variable central slice theorem is used to derive this algorithm. The image is reconstructed with the following steps: first, the attenuated projection data acquired over 180 deg. are extended to 360 deg. and the value for the uniform attenuator is changed to a negative value. The Fourier transform (FT) of the image in polar coordinates is obtained from the Fourier transform of an analytic function interpolated from an extension of the projection data according to the complex central slice theorem. Finally, the image is obtained by performing a 2D inverse Fourier transform. Computer simulations and comparison studies with a 360 deg. full-scan algorithm are provided

  1. GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration

    International Nuclear Information System (INIS)

    Sharp, G C; Kandasamy, N; Singh, H; Folkert, M

    2007-01-01

    This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup-up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration

  2. Development of Image Reconstruction Algorithms in electrical Capacitance Tomography

    International Nuclear Information System (INIS)

    Fernandez Marron, J. L.; Alberdi Primicia, J.; Barcala Riveira, J. M.

    2007-01-01

    The Electrical Capacitance Tomography (ECT) has not obtained a good development in order to be used at industrial level. That is due first to difficulties in the measurement of very little capacitances (in the range of femto farads) and second to the problem of reconstruction on- line of the images. This problem is due also to the small numbers of electrodes (maximum 16), that made the usual algorithms of reconstruction has many errors. In this work it is described a new purely geometrical method that could be used for this purpose. (Author) 4 refs

  3. New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers.

    Science.gov (United States)

    Rodriguez-Ruiz, Alejandro; Teuwen, Jonas; Vreemann, Suzan; Bouwman, Ramona W; van Engen, Ruben E; Karssemeijer, Nico; Mann, Ritse M; Gubern-Merida, Albert; Sechopoulos, Ioannis

    2017-01-01

    Background The image quality of digital breast tomosynthesis (DBT) volumes depends greatly on the reconstruction algorithm. Purpose To compare two DBT reconstruction algorithms used by the Siemens Mammomat Inspiration system, filtered back projection (FBP), and FBP with iterative optimizations (EMPIRE), using qualitative analysis by human readers and detection performance of machine learning algorithms. Material and Methods Visual grading analysis was performed by four readers specialized in breast imaging who scored 100 cases reconstructed with both algorithms (70 lesions). Scoring (5-point scale: 1 = poor to 5 = excellent quality) was performed on presence of noise and artifacts, visualization of skin-line and Cooper's ligaments, contrast, and image quality, and, when present, lesion visibility. In parallel, a three-dimensional deep-learning convolutional neural network (3D-CNN) was trained (n = 259 patients, 51 positives with BI-RADS 3, 4, or 5 calcifications) and tested (n = 46 patients, nine positives), separately with FBP and EMPIRE volumes, to discriminate between samples with and without calcifications. The partial area under the receiver operating characteristic curve (pAUC) of each 3D-CNN was used for comparison. Results EMPIRE reconstructions showed better contrast (3.23 vs. 3.10, P = 0.010), image quality (3.22 vs. 3.03, P algorithm provides DBT volumes with better contrast and image quality, fewer artifacts, and improved visibility of calcifications for human observers, as well as improved detection performance with deep-learning algorithms.

  4. A regularized relaxed ordered subset list-mode reconstruction algorithm and its preliminary application to undersampling PET imaging

    International Nuclear Information System (INIS)

    Cao, Xiaoqing; Xie, Qingguo; Xiao, Peng

    2015-01-01

    List mode format is commonly used in modern positron emission tomography (PET) for image reconstruction due to certain special advantages. In this work, we proposed a list mode based regularized relaxed ordered subset (LMROS) algorithm for static PET imaging. LMROS is able to work with regularization terms which can be formulated as twice differentiable convex functions. Such a versatility would make LMROS a convenient and general framework for fulfilling different regularized list mode reconstruction methods. LMROS was applied to two simulated undersampling PET imaging scenarios to verify its effectiveness. Convex quadratic function, total variation constraint, non-local means and dictionary learning based regularization methods were successfully realized for different cases. The results showed that the LMROS algorithm was effective and some regularization methods greatly reduced the distortions and artifacts caused by undersampling. (paper)

  5. Research of beam hardening correction method for CL system based on SART algorithm

    International Nuclear Information System (INIS)

    Cao Daquan; Wang Yaxiao; Que Jiemin; Sun Cuili; Wei Cunfeng; Wei Long

    2014-01-01

    Computed laminography (CL) is a non-destructive testing technique for large objects, especially for planar objects. Beam hardening artifacts were wildly observed in the CL system and significantly reduce the image quality. This study proposed a novel simultaneous algebraic reconstruction technique (SART) based beam hardening correction (BHC) method for the CL system, namely the SART-BHC algorithm in short. The SART-BHC algorithm took the polychromatic attenuation process in account to formulate the iterative reconstruction update. A novel projection matrix calculation method which was different from the conventional cone-beam or fan-beam geometry was also studied for the CL system. The proposed method was evaluated with simulation data and experimental data, which was generated using the Monte Carlo simulation toolkit Geant4 and a bench-top CL system, respectively. All projection data were reconstructed with SART-BHC algorithm and the standard filtered back projection (FBP) algorithm. The reconstructed images show that beam hardening artifacts are greatly reduced with the SART-BHC algorithm compared to the FBP algorithm. The SART-BHC algorithm doesn't need any prior know-ledge about the object or the X-ray spectrum and it can also mitigate the interlayer aliasing. (authors)

  6. Rapidly 3D Texture Reconstruction Based on Oblique Photography

    Directory of Open Access Journals (Sweden)

    ZHANG Chunsen

    2015-07-01

    Full Text Available This paper proposes a city texture fast reconstruction method based on aerial tilt image for reconstruction of three-dimensional city model. Based on the photogrammetry and computer vision theory and using the city building digital surface model obtained by prior treatment, through collinear equation calculation geometric projection of object and image space, to obtain the three-dimensional information and texture information of the structure and through certain the optimal algorithm selecting the optimal texture on the surface of the object, realize automatic extraction of the building side texture and occlusion handling of the dense building texture. The real image texture reconstruction results show that: the method to the 3D city model texture reconstruction has the characteristics of high degree of automation, vivid effect and low cost and provides a means of effective implementation for rapid and widespread real texture rapid reconstruction of city 3D model.

  7. Pediatric 320-row cardiac computed tomography using electrocardiogram-gated model-based full iterative reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Shirota, Go; Maeda, Eriko; Namiki, Yoko; Bari, Razibul; Abe, Osamu [The University of Tokyo, Department of Radiology, Graduate School of Medicine, Tokyo (Japan); Ino, Kenji [The University of Tokyo Hospital, Imaging Center, Tokyo (Japan); Torigoe, Rumiko [Toshiba Medical Systems, Tokyo (Japan)

    2017-10-15

    Full iterative reconstruction algorithm is available, but its diagnostic quality in pediatric cardiac CT is unknown. To compare the imaging quality of two algorithms, full and hybrid iterative reconstruction, in pediatric cardiac CT. We included 49 children with congenital cardiac anomalies who underwent cardiac CT. We compared quality of images reconstructed using the two algorithms (full and hybrid iterative reconstruction) based on a 3-point scale for the delineation of the following anatomical structures: atrial septum, ventricular septum, right atrium, right ventricle, left atrium, left ventricle, main pulmonary artery, ascending aorta, aortic arch including the patent ductus arteriosus, descending aorta, right coronary artery and left main trunk. We evaluated beam-hardening artifacts from contrast-enhancement material using a 3-point scale, and we evaluated the overall image quality using a 5-point scale. We also compared image noise, signal-to-noise ratio and contrast-to-noise ratio between the algorithms. The overall image quality was significantly higher with full iterative reconstruction than with hybrid iterative reconstruction (3.67±0.79 vs. 3.31±0.89, P=0.0072). The evaluation scores for most of the gross structures were higher with full iterative reconstruction than with hybrid iterative reconstruction. There was no significant difference between full and hybrid iterative reconstruction for the presence of beam-hardening artifacts. Image noise was significantly lower in full iterative reconstruction, while signal-to-noise ratio and contrast-to-noise ratio were significantly higher in full iterative reconstruction. The diagnostic quality was superior in images with cardiac CT reconstructed with electrocardiogram-gated full iterative reconstruction. (orig.)

  8. Pediatric 320-row cardiac computed tomography using electrocardiogram-gated model-based full iterative reconstruction

    International Nuclear Information System (INIS)

    Shirota, Go; Maeda, Eriko; Namiki, Yoko; Bari, Razibul; Abe, Osamu; Ino, Kenji; Torigoe, Rumiko

    2017-01-01

    Full iterative reconstruction algorithm is available, but its diagnostic quality in pediatric cardiac CT is unknown. To compare the imaging quality of two algorithms, full and hybrid iterative reconstruction, in pediatric cardiac CT. We included 49 children with congenital cardiac anomalies who underwent cardiac CT. We compared quality of images reconstructed using the two algorithms (full and hybrid iterative reconstruction) based on a 3-point scale for the delineation of the following anatomical structures: atrial septum, ventricular septum, right atrium, right ventricle, left atrium, left ventricle, main pulmonary artery, ascending aorta, aortic arch including the patent ductus arteriosus, descending aorta, right coronary artery and left main trunk. We evaluated beam-hardening artifacts from contrast-enhancement material using a 3-point scale, and we evaluated the overall image quality using a 5-point scale. We also compared image noise, signal-to-noise ratio and contrast-to-noise ratio between the algorithms. The overall image quality was significantly higher with full iterative reconstruction than with hybrid iterative reconstruction (3.67±0.79 vs. 3.31±0.89, P=0.0072). The evaluation scores for most of the gross structures were higher with full iterative reconstruction than with hybrid iterative reconstruction. There was no significant difference between full and hybrid iterative reconstruction for the presence of beam-hardening artifacts. Image noise was significantly lower in full iterative reconstruction, while signal-to-noise ratio and contrast-to-noise ratio were significantly higher in full iterative reconstruction. The diagnostic quality was superior in images with cardiac CT reconstructed with electrocardiogram-gated full iterative reconstruction. (orig.)

  9. Incorporation of local dependent reliability information into the Prior Image Constrained Compressed Sensing (PICCS) reconstruction algorithm

    International Nuclear Information System (INIS)

    Vaegler, Sven; Sauer, Otto; Stsepankou, Dzmitry; Hesser, Juergen

    2015-01-01

    The reduction of dose in cone beam computer tomography (CBCT) arises from the decrease of the tube current for each projection as well as from the reduction of the number of projections. In order to maintain good image quality, sophisticated image reconstruction techniques are required. The Prior Image Constrained Compressed Sensing (PICCS) incorporates prior images into the reconstruction algorithm and outperforms the widespread used Feldkamp-Davis-Kress-algorithm (FDK) when the number of projections is reduced. However, prior images that contain major variations are not appropriately considered so far in PICCS. We therefore propose the partial-PICCS (pPICCS) algorithm. This framework is a problem-specific extension of PICCS and enables the incorporation of the reliability of the prior images additionally. We assumed that the prior images are composed of areas with large and small deviations. Accordingly, a weighting matrix considered the assigned areas in the objective function. We applied our algorithm to the problem of image reconstruction from few views by simulations with a computer phantom as well as on clinical CBCT projections from a head-and-neck case. All prior images contained large local variations. The reconstructed images were compared to the reconstruction results by the FDK-algorithm, by Compressed Sensing (CS) and by PICCS. To show the gain of image quality we compared image details with the reference image and used quantitative metrics (root-mean-square error (RMSE), contrast-to-noise-ratio (CNR)). The pPICCS reconstruction framework yield images with substantially improved quality even when the number of projections was very small. The images contained less streaking, blurring and inaccurately reconstructed structures compared to the images reconstructed by FDK, CS and conventional PICCS. The increased image quality is also reflected in large RMSE differences. We proposed a modification of the original PICCS algorithm. The pPICCS algorithm

  10. GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation

    International Nuclear Information System (INIS)

    Jia Xun; Lou Yifei; Li Ruijiang; Song, William Y.; Jiang, Steve B.

    2010-01-01

    Purpose: Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersampled and noisy projection data so as to lower the imaging dose. Methods: The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. The authors developed a GPU-friendly version of the forward-backward splitting algorithm to solve this model. A multigrid technique is also employed. Results: It is found that 20-40 x-ray projections are sufficient to reconstruct images with satisfactory quality for IGRT. The reconstruction time ranges from 77 to 130 s on an NVIDIA Tesla C1060 (NVIDIA, Santa Clara, CA) GPU card, depending on the number of projections used, which is estimated about 100 times faster than similar iterative reconstruction approaches. Moreover, phantom studies indicate that the algorithm enables the CBCT to be reconstructed under a scanning protocol with as low as 0.1 mA s/projection. Comparing with currently widely used full-fan head and neck scanning protocol of ∼360 projections with 0.4 mA s/projection, it is estimated that an overall 36-72 times dose reduction has been achieved in our fast CBCT reconstruction algorithm. Conclusions: This work indicates that the developed GPU-based CBCT reconstruction algorithm is capable of lowering imaging dose considerably. The high computation efficiency in this algorithm makes the iterative CBCT reconstruction approach applicable in real clinical environments.

  11. GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation.

    Science.gov (United States)

    Jia, Xun; Lou, Yifei; Li, Ruijiang; Song, William Y; Jiang, Steve B

    2010-04-01

    Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersampled and noisy projection data so as to lower the imaging dose. The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. The authors developed a GPU-friendly version of the forward-backward splitting algorithm to solve this model. A multigrid technique is also employed. It is found that 20-40 x-ray projections are sufficient to reconstruct images with satisfactory quality for IGRT. The reconstruction time ranges from 77 to 130 s on an NVIDIA Tesla C1060 (NVIDIA, Santa Clara, CA) GPU card, depending on the number of projections used, which is estimated about 100 times faster than similar iterative reconstruction approaches. Moreover, phantom studies indicate that the algorithm enables the CBCT to be reconstructed under a scanning protocol with as low as 0.1 mA s/projection. Comparing with currently widely used full-fan head and neck scanning protocol of approximately 360 projections with 0.4 mA s/projection, it is estimated that an overall 36-72 times dose reduction has been achieved in our fast CBCT reconstruction algorithm. This work indicates that the developed GPU-based CBCT reconstruction algorithm is capable of lowering imaging dose considerably. The high computation efficiency in this algorithm makes the iterative CBCT reconstruction approach applicable in real clinical environments.

  12. 3D noise power spectrum applied on clinical MDCT scanners: effects of reconstruction algorithms and reconstruction filters

    Science.gov (United States)

    Miéville, Frédéric A.; Bolard, Gregory; Benkreira, Mohamed; Ayestaran, Paul; Gudinchet, François; Bochud, François; Verdun, Francis R.

    2011-03-01

    The noise power spectrum (NPS) is the reference metric for understanding the noise content in computed tomography (CT) images. To evaluate the noise properties of clinical multidetector (MDCT) scanners, local 2D and 3D NPSs were computed for different acquisition reconstruction parameters. A 64- and a 128-MDCT scanners were employed. Measurements were performed on a water phantom in axial and helical acquisition modes. CT dose index was identical for both installations. Influence of parameters such as the pitch, the reconstruction filter (soft, standard and bone) and the reconstruction algorithm (filtered-back projection (FBP), adaptive statistical iterative reconstruction (ASIR)) were investigated. Images were also reconstructed in the coronal plane using a reformat process. Then 2D and 3D NPS methods were computed. In axial acquisition mode, the 2D axial NPS showed an important magnitude variation as a function of the z-direction when measured at the phantom center. In helical mode, a directional dependency with lobular shape was observed while the magnitude of the NPS was kept constant. Important effects of the reconstruction filter, pitch and reconstruction algorithm were observed on 3D NPS results for both MDCTs. With ASIR, a reduction of the NPS magnitude and a shift of the NPS peak to the low frequency range were visible. 2D coronal NPS obtained from the reformat images was impacted by the interpolation when compared to 2D coronal NPS obtained from 3D measurements. The noise properties of volume measured in last generation MDCTs was studied using local 3D NPS metric. However, impact of the non-stationarity noise effect may need further investigations.

  13. Improved iterative image reconstruction algorithm for the exterior problem of computed tomography

    International Nuclear Information System (INIS)

    Guo, Yumeng; Zeng, Li

    2017-01-01

    In industrial applications that are limited by the angle of a fan-beam and the length of a detector, the exterior problem of computed tomography (CT) uses only the projection data that correspond to the external annulus of the objects to reconstruct an image. Because the reconstructions are not affected by the projection data that correspond to the interior of the objects, the exterior problem is widely applied to detect cracks in the outer wall of large-sized objects, such as in-service pipelines. However, image reconstruction in the exterior problem is still a challenging problem due to truncated projection data and beam-hardening, both of which can lead to distortions and artifacts. Thus, developing an effective algorithm and adopting a scanning trajectory suited for the exterior problem may be valuable. In this study, an improved iterative algorithm that combines total variation minimization (TVM) with a region scalable fitting (RSF) model was developed for a unilateral off-centered scanning trajectory and can be utilized to inspect large-sized objects for defects. Experiments involving simulated phantoms and real projection data were conducted to validate the practicality of our algorithm. Furthermore, comparative experiments show that our algorithm outperforms others in suppressing the artifacts caused by truncated projection data and beam-hardening.

  14. Improved iterative image reconstruction algorithm for the exterior problem of computed tomography

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Yumeng [Chongqing University, College of Mathematics and Statistics, Chongqing 401331 (China); Chongqing University, ICT Research Center, Key Laboratory of Optoelectronic Technology and System of the Education Ministry of China, Chongqing 400044 (China); Zeng, Li, E-mail: drlizeng@cqu.edu.cn [Chongqing University, College of Mathematics and Statistics, Chongqing 401331 (China); Chongqing University, ICT Research Center, Key Laboratory of Optoelectronic Technology and System of the Education Ministry of China, Chongqing 400044 (China)

    2017-01-11

    In industrial applications that are limited by the angle of a fan-beam and the length of a detector, the exterior problem of computed tomography (CT) uses only the projection data that correspond to the external annulus of the objects to reconstruct an image. Because the reconstructions are not affected by the projection data that correspond to the interior of the objects, the exterior problem is widely applied to detect cracks in the outer wall of large-sized objects, such as in-service pipelines. However, image reconstruction in the exterior problem is still a challenging problem due to truncated projection data and beam-hardening, both of which can lead to distortions and artifacts. Thus, developing an effective algorithm and adopting a scanning trajectory suited for the exterior problem may be valuable. In this study, an improved iterative algorithm that combines total variation minimization (TVM) with a region scalable fitting (RSF) model was developed for a unilateral off-centered scanning trajectory and can be utilized to inspect large-sized objects for defects. Experiments involving simulated phantoms and real projection data were conducted to validate the practicality of our algorithm. Furthermore, comparative experiments show that our algorithm outperforms others in suppressing the artifacts caused by truncated projection data and beam-hardening.

  15. PixTrig: a Level 2 track finding algorithm based on pixel detector

    CERN Document Server

    Baratella, A; Morettini, P; Parodi, F

    2000-01-01

    This note describes an algorithm for track search at Level 2 based on pixel detector. Using three pixel clusters we can produce a reconstruction of the track parameter in both z and R-phi plane. These track segments can be used as seed for more sophisticated track finding algorithms or used directly, especially when impact parameter resolution is crucial. The algorithm efficiency is close to 90% for pt > 1 GeV/c and the processing time is small enough to allow a complete detector reconstruction (non RoI guided) within the Level 2 processing.

  16. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    Energy Technology Data Exchange (ETDEWEB)

    Solomon, Justin, E-mail: justin.solomon@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Biomedical Engineering and Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina 27705 (United States)

    2014-09-15

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  17. An electron tomography algorithm for reconstructing 3D morphology using surface tangents of projected scattering interfaces

    Science.gov (United States)

    Petersen, T. C.; Ringer, S. P.

    2010-03-01

    Upon discerning the mere shape of an imaged object, as portrayed by projected perimeters, the full three-dimensional scattering density may not be of particular interest. In this situation considerable simplifications to the reconstruction problem are possible, allowing calculations based upon geometric principles. Here we describe and provide an algorithm which reconstructs the three-dimensional morphology of specimens from tilt series of images for application to electron tomography. Our algorithm uses a differential approach to infer the intersection of projected tangent lines with surfaces which define boundaries between regions of different scattering densities within and around the perimeters of specimens. Details of the algorithm implementation are given and explained using reconstruction calculations from simulations, which are built into the code. An experimental application of the algorithm to a nano-sized Aluminium tip is also presented to demonstrate practical analysis for a real specimen. Program summaryProgram title: STOMO version 1.0 Catalogue identifier: AEFS_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 2988 No. of bytes in distributed program, including test data, etc.: 191 605 Distribution format: tar.gz Programming language: C/C++ Computer: PC Operating system: Windows XP RAM: Depends upon the size of experimental data as input, ranging from 200 Mb to 1.5 Gb Supplementary material: Sample output files, for the test run provided, are available. Classification: 7.4, 14 External routines: Dev-C++ ( http://www.bloodshed.net/devcpp.html) Nature of problem: Electron tomography of specimens for which conventional back projection may fail and/or data for which there is a limited angular

  18. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    International Nuclear Information System (INIS)

    Solomon, Justin; Samei, Ehsan

    2014-01-01

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  19. An FDK-like cone-beam SPECT reconstruction algorithm for non-uniform attenuated projections acquired using a circular trajectory

    International Nuclear Information System (INIS)

    Huang, Q; Zeng, G L; You, J; Gullberg, G T

    2005-01-01

    In this paper, Novikov's inversion formula of the attenuated two-dimensional (2D) Radon transform is applied to the reconstruction of attenuated fan-beam projections acquired with equal detector spacing and of attenuated cone-beam projections acquired with a flat planar detector and circular trajectory. The derivation of the fan-beam algorithm is obtained by transformation from parallel-beam coordinates to fan-beam coordinates. The cone-beam reconstruction algorithm is an extension of the fan-beam reconstruction algorithm using Feldkamp-Davis-Kress's (FDK) method. Computer simulations indicate that the algorithm is efficient and is accurate in reconstructing slices close to the central slice of the cone-beam orbit plane. When the attenuation map is set to zero the implementation is equivalent to the FDK method. Reconstructed images are also shown for noise corrupted projections

  20. Comparison of the effects of model-based iterative reconstruction and filtered back projection algorithms on software measurements in pulmonary subsolid nodules

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, Julien G. [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea, Republic of); Centre Hospitalier Universitaire de Grenoble, Clinique Universitaire de Radiologie et Imagerie Medicale (CURIM), Universite Grenoble Alpes, Grenoble Cedex 9 (France); Kim, Hyungjin; Park, Su Bin [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea, Republic of); Ginneken, Bram van [Radboud University Nijmegen Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Ferretti, Gilbert R. [Centre Hospitalier Universitaire de Grenoble, Clinique Universitaire de Radiologie et Imagerie Medicale (CURIM), Universite Grenoble Alpes, Grenoble Cedex 9 (France); Institut A Bonniot, INSERM U 823, La Tronche (France); Lee, Chang Hyun [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Goo, Jin Mo; Park, Chang Min [Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea, Republic of); Seoul National University College of Medicine, Cancer Research Institute, Seoul (Korea, Republic of)

    2017-08-15

    To evaluate the differences between filtered back projection (FBP) and model-based iterative reconstruction (MBIR) algorithms on semi-automatic measurements in subsolid nodules (SSNs). Unenhanced CT scans of 73 SSNs obtained using the same protocol and reconstructed with both FBP and MBIR algorithms were evaluated by two radiologists. Diameter, mean attenuation, mass and volume of whole nodules and their solid components were measured. Intra- and interobserver variability and differences between FBP and MBIR were then evaluated using Bland-Altman method and Wilcoxon tests. Longest diameter, volume and mass of nodules and those of their solid components were significantly higher using MBIR (p < 0.05) with mean differences of 1.1% (limits of agreement, -6.4 to 8.5%), 3.2% (-20.9 to 27.3%) and 2.9% (-16.9 to 22.7%) and 3.2% (-20.5 to 27%), 6.3% (-51.9 to 64.6%), 6.6% (-50.1 to 63.3%), respectively. The limits of agreement between FBP and MBIR were within the range of intra- and interobserver variability for both algorithms with respect to the diameter, volume and mass of nodules and their solid components. There were no significant differences in intra- or interobserver variability between FBP and MBIR (p > 0.05). Semi-automatic measurements of SSNs significantly differed between FBP and MBIR; however, the differences were within the range of measurement variability. (orig.)

  1. WE-G-18A-04: 3D Dictionary Learning Based Statistical Iterative Reconstruction for Low-Dose Cone Beam CT Imaging

    International Nuclear Information System (INIS)

    Bai, T; Yan, H; Shi, F; Jia, X; Jiang, Steve B.; Lou, Y; Xu, Q; Mou, X

    2014-01-01

    Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential

  2. WE-G-18A-04: 3D Dictionary Learning Based Statistical Iterative Reconstruction for Low-Dose Cone Beam CT Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Bai, T [Xi' an Jiaotong University, Xi' an (China); UT Southwestern Medical Center, Dallas, TX (United States); Yan, H; Shi, F; Jia, X; Jiang, Steve B. [UT Southwestern Medical Center, Dallas, TX (United States); Lou, Y [University of California Irvine, Irvine, CA (United States); Xu, Q; Mou, X [Xi' an Jiaotong University, Xi' an (China)

    2014-06-15

    Purpose: To develop a 3D dictionary learning based statistical reconstruction algorithm on graphic processing units (GPU), to improve the quality of low-dose cone beam CT (CBCT) imaging with high efficiency. Methods: A 3D dictionary containing 256 small volumes (atoms) of 3x3x3 voxels was trained from a high quality volume image. During reconstruction, we utilized a Cholesky decomposition based orthogonal matching pursuit algorithm to find a sparse representation on this dictionary basis of each patch in the reconstructed image, in order to regularize the image quality. To accelerate the time-consuming sparse coding in the 3D case, we implemented our algorithm in a parallel fashion by taking advantage of the tremendous computational power of GPU. Evaluations are performed based on a head-neck patient case. FDK reconstruction with full dataset of 364 projections is used as the reference. We compared the proposed 3D dictionary learning based method with a tight frame (TF) based one using a subset data of 121 projections. The image qualities under different resolutions in z-direction, with or without statistical weighting are also studied. Results: Compared to the TF-based CBCT reconstruction, our experiments indicated that 3D dictionary learning based CBCT reconstruction is able to recover finer structures, to remove more streaking artifacts, and is less susceptible to blocky artifacts. It is also observed that statistical reconstruction approach is sensitive to inconsistency between the forward and backward projection operations in parallel computing. Using high a spatial resolution along z direction helps improving the algorithm robustness. Conclusion: 3D dictionary learning based CBCT reconstruction algorithm is able to sense the structural information while suppressing noise, and hence to achieve high quality reconstruction. The GPU realization of the whole algorithm offers a significant efficiency enhancement, making this algorithm more feasible for potential

  3. Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms

    International Nuclear Information System (INIS)

    Sidky, Emil Y.; Pan Xiaochuan; Reiser, Ingrid S.; Nishikawa, Robert M.; Moore, Richard H.; Kopans, Daniel B.

    2009-01-01

    Purpose: The authors develop a practical, iterative algorithm for image-reconstruction in undersampled tomographic systems, such as digital breast tomosynthesis (DBT). Methods: The algorithm controls image regularity by minimizing the image total p variation (TpV), a function that reduces to the total variation when p=1.0 or the image roughness when p=2.0. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets. The fact that the tomographic system is undersampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) Reduction in the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in undersampled tomography. Results: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. Conclusions: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.

  4. 3D reconstruction based on light field images

    Science.gov (United States)

    Zhu, Dong; Wu, Chunhong; Liu, Yunluo; Fu, Dongmei

    2018-04-01

    This paper proposed a method of reconstructing three-dimensional (3D) scene from two light field images capture by Lytro illium. The work was carried out by first extracting the sub-aperture images from light field images and using the scale-invariant feature transform (SIFT) for feature registration on the selected sub-aperture images. Structure from motion (SFM) algorithm is further used on the registration completed sub-aperture images to reconstruct the three-dimensional scene. 3D sparse point cloud was obtained in the end. The method shows that the 3D reconstruction can be implemented by only two light field camera captures, rather than at least a dozen times captures by traditional cameras. This can effectively solve the time-consuming, laborious issues for 3D reconstruction based on traditional digital cameras, to achieve a more rapid, convenient and accurate reconstruction.

  5. Model-based image reconstruction in X-ray computed tomography

    NARCIS (Netherlands)

    Zbijewski, Wojciech Bartosz

    2006-01-01

    The thesis investigates the applications of iterative, statistical reconstruction (SR) algorithms in X-ray Computed Tomography. Emphasis is put on various aspects of system modeling in statistical reconstruction. Fundamental issues such as effects of object discretization and algorithm

  6. Performance of 3DOSEM and MAP algorithms for reconstructing low count SPECT acquisitions

    Energy Technology Data Exchange (ETDEWEB)

    Grootjans, Willem [Radboud Univ. Medical Center, Nijmegen (Netherlands). Dept. of Radiology and Nuclear Medicine; Leiden Univ. Medical Center (Netherlands). Dept. of Radiology; Meeuwis, Antoi P.W.; Gotthardt, Martin; Visser, Eric P. [Radboud Univ. Medical Center, Nijmegen (Netherlands). Dept. of Radiology and Nuclear Medicine; Slump, Cornelis H. [Univ. Twente, Enschede (Netherlands). MIRA Inst. for Biomedical Technology and Technical Medicine; Geus-Oei, Lioe-Fee de [Radboud Univ. Medical Center, Nijmegen (Netherlands). Dept. of Radiology and Nuclear Medicine; Univ. Twente, Enschede (Netherlands). MIRA Inst. for Biomedical Technology and Technical Medicine; Leiden Univ. Medical Center (Netherlands). Dept. of Radiology

    2016-07-01

    Low count single photon emission computed tomography (SPECT) is becoming more important in view of whole body SPECT and reduction of radiation dose. In this study, we investigated the performance of several 3D ordered subset expectation maximization (3DOSEM) and maximum a posteriori (MAP) algorithms for reconstructing low count SPECT images. Phantom experiments were conducted using the National Electrical Manufacturers Association (NEMA) NU2 image quality (IQ) phantom. The background compartment of the phantom was filled with varying concentrations of pertechnetate and indiumchloride, simulating various clinical imaging conditions. Images were acquired using a hybrid SPECT/CT scanner and reconstructed with 3DOSEM and MAP reconstruction algorithms implemented in Siemens Syngo MI.SPECT (Flash3D) and Hermes Hybrid Recon Oncology (Hyrid Recon 3DOSEM and MAP). Image analysis was performed by calculating the contrast recovery coefficient (CRC),percentage background variability (N%), and contrast-to-noise ratio (CNR), defined as the ratio between CRC and N%. Furthermore, image distortion is characterized by calculating the aspect ratio (AR) of ellipses fitted to the hot spheres. Additionally, the performance of these algorithms to reconstruct clinical images was investigated. Images reconstructed with 3DOSEM algorithms demonstrated superior image quality in terms of contrast and resolution recovery when compared to images reconstructed with filtered-back-projection (FBP), OSEM and 2DOSEM. However, occurrence of correlated noise patterns and image distortions significantly deteriorated the quality of 3DOSEM reconstructed images. The mean AR for the 37, 28, 22, and 17 mm spheres was 1.3, 1.3, 1.6, and 1.7 respectively. The mean N% increase in high and low count Flash3D and Hybrid Recon 3DOSEM from 5.9% and 4.0% to 11.1% and 9.0%, respectively. Similarly, the mean CNR decreased in high and low count Flash3D and Hybrid Recon 3DOSEM from 8.7 and 8.8 to 3.6 and 4

  7. Low contrast detectability and spatial resolution with model-based iterative reconstructions of MDCT images: a phantom and cadaveric study

    Energy Technology Data Exchange (ETDEWEB)

    Millon, Domitille; Coche, Emmanuel E. [Universite Catholique de Louvain, Department of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Brussels (Belgium); Vlassenbroek, Alain [Philips Healthcare, Brussels (Belgium); Maanen, Aline G. van; Cambier, Samantha E. [Universite Catholique de Louvain, Statistics Unit, King Albert II Cancer Institute, Brussels (Belgium)

    2017-03-15

    To compare image quality [low contrast (LC) detectability, noise, contrast-to-noise (CNR) and spatial resolution (SR)] of MDCT images reconstructed with an iterative reconstruction (IR) algorithm and a filtered back projection (FBP) algorithm. The experimental study was performed on a 256-slice MDCT. LC detectability, noise, CNR and SR were measured on a Catphan phantom scanned with decreasing doses (48.8 down to 0.7 mGy) and parameters typical of a chest CT examination. Images were reconstructed with FBP and a model-based IR algorithm. Additionally, human chest cadavers were scanned and reconstructed using the same technical parameters. Images were analyzed to illustrate the phantom results. LC detectability and noise were statistically significantly different between the techniques, supporting model-based IR algorithm (p < 0.0001). At low doses, the noise in FBP images only enabled SR measurements of high contrast objects. The superior CNR of model-based IR algorithm enabled lower dose measurements, which showed that SR was dose and contrast dependent. Cadaver images reconstructed with model-based IR illustrated that visibility and delineation of anatomical structure edges could be deteriorated at low doses. Model-based IR improved LC detectability and enabled dose reduction. At low dose, SR became dose and contrast dependent. (orig.)

  8. Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT

    International Nuclear Information System (INIS)

    Barras, Heloise; Dunet, Vincent; Hachulla, Anne-Lise; Grimm, Jochen; Beigelman-Aubry, Catherine

    2016-01-01

    Model-based iterative reconstruction (MBIR) reduces image noise and improves image quality (IQ) but its influence on post-processing tools including maximal intensity projection (MIP) and minimal intensity projection (mIP) remains unknown. To evaluate the influence on IQ of MBIR on native, mIP, MIP axial and coronal reformats of reduced dose computed tomography (RD-CT) chest acquisition. Raw data of 50 patients, who underwent a standard dose CT (SD-CT) and a follow-up RD-CT with a CT dose index (CTDI) of 2–3 mGy, were reconstructed by MBIR and FBP. Native slices, 4-mm-thick MIP, and 3-mm-thick mIP axial and coronal reformats were generated. The relative IQ, subjective IQ, image noise, and number of artifacts were determined in order to compare different reconstructions of RD-CT with reference SD-CT. The lowest noise was observed with MBIR. RD-CT reconstructed by MBIR exhibited the best relative and subjective IQ on coronal view regardless of the post-processing tool. MBIR generated the lowest rate of artefacts on coronal mIP/MIP reformats and the highest one on axial reformats, mainly represented by distortions and stairsteps artifacts. The MBIR algorithm reduces image noise but generates more artifacts than FBP on axial mIP and MIP reformats of RD-CT. Conversely, it significantly improves IQ on coronal views, without increasing artifacts, regardless of the post-processing technique

  9. Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Hongyang Lu

    2016-06-01

    Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

  10. Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

    Science.gov (United States)

    McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

    2006-03-01

    To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the

  11. Photoacoustic image reconstruction via deep learning

    Science.gov (United States)

    Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes

    2018-02-01

    Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.

  12. Influence of radiation dose and reconstruction algorithm in MDCT assessment of airway wall thickness: A phantom study

    International Nuclear Information System (INIS)

    Gomez-Cardona, Daniel; Nagle, Scott K.; Li, Ke; Chen, Guang-Hong; Robinson, Terry E.

    2015-01-01

    Purpose: Wall thickness (WT) is an airway feature of great interest for the assessment of morphological changes in the lung parenchyma. Multidetector computed tomography (MDCT) has recently been used to evaluate airway WT, but the potential risk of radiation-induced carcinogenesis—particularly in younger patients—might limit a wider use of this imaging method in clinical practice. The recent commercial implementation of the statistical model-based iterative reconstruction (MBIR) algorithm, instead of the conventional filtered back projection (FBP) algorithm, has enabled considerable radiation dose reduction in many other clinical applications of MDCT. The purpose of this work was to study the impact of radiation dose and MBIR in the MDCT assessment of airway WT. Methods: An airway phantom was scanned using a clinical MDCT system (Discovery CT750 HD, GE Healthcare) at 4 kV levels and 5 mAs levels. Both FBP and a commercial implementation of MBIR (Veo TM , GE Healthcare) were used to reconstruct CT images of the airways. For each kV–mAs combination and each reconstruction algorithm, the contrast-to-noise ratio (CNR) of the airways was measured, and the WT of each airway was measured and compared with the nominal value; the relative bias and the angular standard deviation in the measured WT were calculated. For each airway and reconstruction algorithm, the overall performance of WT quantification across all of the 20 kV–mAs combinations was quantified by the sum of squares (SSQs) of the difference between the measured and nominal WT values. Finally, the particular kV–mAs combination and reconstruction algorithm that minimized radiation dose while still achieving a reference WT quantification accuracy level was chosen as the optimal acquisition and reconstruction settings. Results: The wall thicknesses of seven airways of different sizes were analyzed in the study. Compared with FBP, MBIR improved the CNR of the airways, particularly at low radiation dose

  13. Influence of radiation dose and reconstruction algorithm in MDCT assessment of airway wall thickness: A phantom study

    Energy Technology Data Exchange (ETDEWEB)

    Gomez-Cardona, Daniel [Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, Madison, Wisconsin 53705 (United States); Nagle, Scott K. [Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, Madison, Wisconsin 53705 (United States); Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, 600 Highland Avenue, Madison, Wisconsin 53792 (United States); Department of Pediatrics, University of Wisconsin-Madison School of Medicine and Public Health, 600 Highland Avenue, Madison, Wisconsin 53792 (United States); Li, Ke; Chen, Guang-Hong, E-mail: gchen7@wisc.edu [Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, 1111 Highland Avenue, Madison, Wisconsin 53705 (United States); Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, 600 Highland Avenue, Madison, Wisconsin 53792 (United States); Robinson, Terry E. [Department of Pediatrics, Stanford School of Medicine, 770 Welch Road, Palo Alto, California 94304 (United States)

    2015-10-15

    Purpose: Wall thickness (WT) is an airway feature of great interest for the assessment of morphological changes in the lung parenchyma. Multidetector computed tomography (MDCT) has recently been used to evaluate airway WT, but the potential risk of radiation-induced carcinogenesis—particularly in younger patients—might limit a wider use of this imaging method in clinical practice. The recent commercial implementation of the statistical model-based iterative reconstruction (MBIR) algorithm, instead of the conventional filtered back projection (FBP) algorithm, has enabled considerable radiation dose reduction in many other clinical applications of MDCT. The purpose of this work was to study the impact of radiation dose and MBIR in the MDCT assessment of airway WT. Methods: An airway phantom was scanned using a clinical MDCT system (Discovery CT750 HD, GE Healthcare) at 4 kV levels and 5 mAs levels. Both FBP and a commercial implementation of MBIR (Veo{sup TM}, GE Healthcare) were used to reconstruct CT images of the airways. For each kV–mAs combination and each reconstruction algorithm, the contrast-to-noise ratio (CNR) of the airways was measured, and the WT of each airway was measured and compared with the nominal value; the relative bias and the angular standard deviation in the measured WT were calculated. For each airway and reconstruction algorithm, the overall performance of WT quantification across all of the 20 kV–mAs combinations was quantified by the sum of squares (SSQs) of the difference between the measured and nominal WT values. Finally, the particular kV–mAs combination and reconstruction algorithm that minimized radiation dose while still achieving a reference WT quantification accuracy level was chosen as the optimal acquisition and reconstruction settings. Results: The wall thicknesses of seven airways of different sizes were analyzed in the study. Compared with FBP, MBIR improved the CNR of the airways, particularly at low radiation dose

  14. Effect of different reconstruction algorithms on computer-aided diagnosis (CAD) performance in ultra-low dose CT colonography

    International Nuclear Information System (INIS)

    Lee, Eun Sun; Kim, Se Hyung; Im, Jong Pil; Kim, Sang Gyun; Shin, Cheong-il; Han, Joon Koo; Choi, Byung Ihn

    2015-01-01

    Highlights: •We assessed the effect of reconstruction algorithms on CAD in ultra-low dose CTC. •30 patients underwent ultra-low dose CTC using 120 and 100 kVp with 10 mAs. •CT was reconstructed with FBP, ASiR and Veo and then, we applied a CAD system. •Per-polyp sensitivity of CAD in ULD CT can be improved with the IR algorithms. •Despite of an increase in the number of FPs with IR, it was still acceptable. -- Abstract: Purpose: To assess the effect of different reconstruction algorithms on computer-aided diagnosis (CAD) performance in ultra-low-dose CT colonography (ULD CTC). Materials and methods: IRB approval and informed consents were obtained. Thirty prospectively enrolled patients underwent non-contrast CTC at 120 kVp/10 mAs in supine and 100 kVp/10 mAs in prone positions, followed by same-day colonoscopy. Images were reconstructed with filtered back projection (FBP), 80% adaptive statistical iterative reconstruction (ASIR80), and model-based iterative reconstruction (MBIR). A commercial CAD system was applied and per-polyp sensitivities and numbers of false-positives (FPs) were compared among algorithms. Results: Mean effective radiation dose of CTC was 1.02 mSv. Of 101 polyps detected and removed by colonoscopy, 61 polyps were detected on supine and on prone CTC datasets on consensus unblinded review, resulting in 122 visible polyps (32 polyps <6 mm, 52 6–9.9 mm, and 38 ≥ 10 mm). Per-polyp sensitivity of CAD for all polyps was highest with MBIR (56/122, 45.9%), followed by ASIR80 (54/122, 44.3%) and FBP (43/122, 35.2%), with significant differences between FBP and IR algorithms (P < 0.017). Per-polyp sensitivity for polyps ≥ 10 mm was also higher with MBIR (25/38, 65.8%) and ASIR80 (24/38, 63.2%) than with FBP (20/38, 58.8%), albeit without statistical significance (P > 0.017). Mean number of FPs was significantly different among algorithms (FBP, 1.4; ASIR, 2.1; MBIR, 2.4) (P = 0.011). Conclusion: Although the performance of stand-alone CAD

  15. Effect of different reconstruction algorithms on computer-aided diagnosis (CAD) performance in ultra-low dose CT colonography

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Eun Sun [Department of Radiology, Seoul National University Hospital (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Hospital (Korea, Republic of); Kim, Se Hyung, E-mail: shkim7071@gmail.com [Department of Radiology, Seoul National University Hospital (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Hospital (Korea, Republic of); Im, Jong Pil; Kim, Sang Gyun [Department of Internal Medicine, Seoul National University Hospital (Korea, Republic of); Shin, Cheong-il; Han, Joon Koo; Choi, Byung Ihn [Department of Radiology, Seoul National University Hospital (Korea, Republic of); Institute of Radiation Medicine, Seoul National University Hospital (Korea, Republic of)

    2015-04-15

    Highlights: •We assessed the effect of reconstruction algorithms on CAD in ultra-low dose CTC. •30 patients underwent ultra-low dose CTC using 120 and 100 kVp with 10 mAs. •CT was reconstructed with FBP, ASiR and Veo and then, we applied a CAD system. •Per-polyp sensitivity of CAD in ULD CT can be improved with the IR algorithms. •Despite of an increase in the number of FPs with IR, it was still acceptable. -- Abstract: Purpose: To assess the effect of different reconstruction algorithms on computer-aided diagnosis (CAD) performance in ultra-low-dose CT colonography (ULD CTC). Materials and methods: IRB approval and informed consents were obtained. Thirty prospectively enrolled patients underwent non-contrast CTC at 120 kVp/10 mAs in supine and 100 kVp/10 mAs in prone positions, followed by same-day colonoscopy. Images were reconstructed with filtered back projection (FBP), 80% adaptive statistical iterative reconstruction (ASIR80), and model-based iterative reconstruction (MBIR). A commercial CAD system was applied and per-polyp sensitivities and numbers of false-positives (FPs) were compared among algorithms. Results: Mean effective radiation dose of CTC was 1.02 mSv. Of 101 polyps detected and removed by colonoscopy, 61 polyps were detected on supine and on prone CTC datasets on consensus unblinded review, resulting in 122 visible polyps (32 polyps <6 mm, 52 6–9.9 mm, and 38 ≥ 10 mm). Per-polyp sensitivity of CAD for all polyps was highest with MBIR (56/122, 45.9%), followed by ASIR80 (54/122, 44.3%) and FBP (43/122, 35.2%), with significant differences between FBP and IR algorithms (P < 0.017). Per-polyp sensitivity for polyps ≥ 10 mm was also higher with MBIR (25/38, 65.8%) and ASIR80 (24/38, 63.2%) than with FBP (20/38, 58.8%), albeit without statistical significance (P > 0.017). Mean number of FPs was significantly different among algorithms (FBP, 1.4; ASIR, 2.1; MBIR, 2.4) (P = 0.011). Conclusion: Although the performance of stand-alone CAD

  16. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  17. Structured Light-Based 3D Reconstruction System for Plants

    OpenAIRE

    Nguyen, Thuy Tuong; Slaughter, David C.; Max, Nelson; Maloof, Julin N.; Sinha, Neelima

    2015-01-01

    Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud regi...

  18. An efficient reconstruction algorithm for differential phase-contrast tomographic images from a limited number of views

    International Nuclear Information System (INIS)

    Sunaguchi, Naoki; Yuasa, Tetsuya; Gupta, Rajiv; Ando, Masami

    2015-01-01

    The main focus of this paper is reconstruction of tomographic phase-contrast image from a set of projections. We propose an efficient reconstruction algorithm for differential phase-contrast computed tomography that can considerably reduce the number of projections required for reconstruction. The key result underlying this research is a projection theorem that states that the second derivative of the projection set is linearly related to the Laplacian of the tomographic image. The proposed algorithm first reconstructs the Laplacian image of the phase-shift distribution from the second-derivative of the projections using total variation regularization. The second step is to obtain the phase-shift distribution by solving a Poisson equation whose source is the Laplacian image previously reconstructed under the Dirichlet condition. We demonstrate the efficacy of this algorithm using both synthetically generated simulation data and projection data acquired experimentally at a synchrotron. The experimental phase data were acquired from a human coronary artery specimen using dark-field-imaging optics pioneered by our group. Our results demonstrate that the proposed algorithm can reduce the number of projections to approximately 33% as compared with the conventional filtered backprojection method, without any detrimental effect on the image quality

  19. Acoustical source reconstruction from non-synchronous sequential measurements by Fast Iterative Shrinkage Thresholding Algorithm

    Science.gov (United States)

    Yu, Liang; Antoni, Jerome; Leclere, Quentin; Jiang, Weikang

    2017-11-01

    Acoustical source reconstruction is a typical inverse problem, whose minimum frequency of reconstruction hinges on the size of the array and maximum frequency depends on the spacing distance between the microphones. For the sake of enlarging the frequency of reconstruction and reducing the cost of an acquisition system, Cyclic Projection (CP), a method of sequential measurements without reference, was recently investigated (JSV,2016,372:31-49). In this paper, the Propagation based Fast Iterative Shrinkage Thresholding Algorithm (Propagation-FISTA) is introduced, which improves CP in two aspects: (1) the number of acoustic sources is no longer needed and the only making assumption is that of a "weakly sparse" eigenvalue spectrum; (2) the construction of the spatial basis is much easier and adaptive to practical scenarios of acoustical measurements benefiting from the introduction of propagation based spatial basis. The proposed Propagation-FISTA is first investigated with different simulations and experimental setups and is next illustrated with an industrial case.

  20. Fully 3D PET image reconstruction using a fourier preconditioned conjugate-gradient algorithm

    International Nuclear Information System (INIS)

    Fessler, J.A.; Ficaro, E.P.

    1996-01-01

    Since the data sizes in fully 3D PET imaging are very large, iterative image reconstruction algorithms must converge in very few iterations to be useful. One can improve the convergence rate of the conjugate-gradient (CG) algorithm by incorporating preconditioning operators that approximate the inverse of the Hessian of the objective function. If the 3D cylindrical PET geometry were not truncated at the ends, then the Hessian of the penalized least-squares objective function would be approximately shift-invariant, i.e. G'G would be nearly block-circulant, where G is the system matrix. We propose a Fourier preconditioner based on this shift-invariant approximation to the Hessian. Results show that this preconditioner significantly accelerates the convergence of the CG algorithm with only a small increase in computation

  1. Layer-oriented multigrid wavefront reconstruction algorithms for multi-conjugate adaptive optics

    Science.gov (United States)

    Gilles, Luc; Ellerbroek, Brent L.; Vogel, Curtis R.

    2003-02-01

    Multi-conjugate adaptive optics (MCAO) systems with 104-105 degrees of freedom have been proposed for future giant telescopes. Using standard matrix methods to compute, optimize, and implement wavefront control algorithms for these systems is impractical, since the number of calculations required to compute and apply the reconstruction matrix scales respectively with the cube and the square of the number of AO degrees of freedom. In this paper, we develop an iterative sparse matrix implementation of minimum variance wavefront reconstruction for telescope diameters up to 32m with more than 104 actuators. The basic approach is the preconditioned conjugate gradient method, using a multigrid preconditioner incorporating a layer-oriented (block) symmetric Gauss-Seidel iterative smoothing operator. We present open-loop numerical simulation results to illustrate algorithm convergence.

  2. A study of reconstruction artifacts in cone beam tomography using filtered backprojection and iterative EM algorithms

    International Nuclear Information System (INIS)

    Zeng, G.L.; Gullberg, G.T.

    1990-01-01

    Reconstruction artifacts in cone beam tomography are studied for filtered backprojection (Feldkamp) and iterative EM algorithms. The filtered backprojection algorithm uses a voxel-driven, interpolated backprojection to reconstruct the cone beam data; whereas, the iterative EM algorithm performs ray-driven projection and backprojection operations for each iteration. Two weight in schemes for the projection and backprojection operations in the EM algorithm are studied. One weights each voxel by the length of the ray through the voxel and the other equates the value of a voxel to the functional value of the midpoint of the line intersecting the voxel, which is obtained by interpolating between eight neighboring voxels. Cone beam reconstruction artifacts such as rings, bright vertical extremities, and slice-to slice cross talk are not found with parallel beam and fan beam geometries

  3. A volume of fluid method based on multidimensional advection and spline interface reconstruction

    International Nuclear Information System (INIS)

    Lopez, J.; Hernandez, J.; Gomez, P.; Faura, F.

    2004-01-01

    A new volume of fluid method for tracking two-dimensional interfaces is presented. The method involves a multidimensional advection algorithm based on the use of edge-matched flux polygons to integrate the volume fraction evolution equation, and a spline-based reconstruction algorithm. The accuracy and efficiency of the proposed method are analyzed using different tests, and the results are compared with those obtained recently by other authors. Despite its simplicity, the proposed method represents a significant improvement, and compares favorably with other volume of fluid methods as regards the accuracy and efficiency of both the advection and reconstruction steps

  4. A tracking algorithm for the reconstruction of the daughters of long-lived particles in LHCb

    CERN Document Server

    Dendek, Adam Mateusz

    2018-01-01

    A tracking algorithm for the reconstruction of the daughters of long-lived particles in LHCb 5 Jun 2018, 16:00 1h 30m Library, Centro San Domenico () LHC experiments Posters session Speaker Katharina Mueller (Universitaet Zuerich (CH)) Description The LHCb experiment at CERN operates a high precision and robust tracking system to reach its physics goals, including precise measurements of CP-violation phenomena in the heavy flavour quark sector and searches for New Physics beyond the Standard Model. The track reconstruction procedure is performed by a number of algorithms. One of these, PatLongLivedTracking, is optimised to reconstruct "downstream tracks", which are tracks originating from decays outside the LHCb vertex detector of long-lived particles, such as Ks or Λ0. After an overview of the LHCb tracking system, we provide a detailed description of the LHCb downstream track reconstruction algorithm. Its computational intelligence part is described in details, including the adaptation of the employed...

  5. An efficient algorithm for reconstruction of spect images in the presence of spatially varying attenuation

    International Nuclear Information System (INIS)

    Zeeberg, B.R.; Bacharach, S.; Carson, R.; Green, M.V.; Larson, S.M.; Soucaille, J.F.

    1985-01-01

    An algorithm is presented which permits the reconstruction of SPECT images in the presence of spatially varying attenuation. The algorithm considers the spatially variant attenuation as a perturbation of the constant attenuation case and computes a reconstructed image and a correction image to estimate the effects of this perturbation. The corrected image will be computed from these two images and is of comparable quality both visually and quantitatively to those simulated for zero or constant attenuation taken as standard reference images. In addition, the algorithm is time efficient, in that the time required is approximately 2.5 times that for a standard convolution-back projection algorithm

  6. Signal reconstruction in wireless sensor networks based on a cubature Kalman particle filter

    International Nuclear Information System (INIS)

    Huang Jin-Wang; Feng Jiu-Chao

    2014-01-01

    For solving the issues of the signal reconstruction of nonlinear non-Gaussian signals in wireless sensor networks (WSNs), a new signal reconstruction algorithm based on a cubature Kalman particle filter (CKPF) is proposed in this paper. We model the reconstruction signal first and then use the CKPF to estimate the signal. The CKPF uses a cubature Kalman filter (CKF) to generate the importance proposal distribution of the particle filter and integrates the latest observation, which can approximate the true posterior distribution better. It can improve the estimation accuracy. CKPF uses fewer cubature points than the unscented Kalman particle filter (UKPF) and has less computational overheads. Meanwhile, CKPF uses the square root of the error covariance for iterating and is more stable and accurate than the UKPF counterpart. Simulation results show that the algorithm can reconstruct the observed signals quickly and effectively, at the same time consuming less computational time and with more accuracy than the method based on UKPF. (general)

  7. Research on non-uniform strain profile reconstruction along fiber Bragg grating via genetic programming algorithm and interrelated experimental verification

    Science.gov (United States)

    Zheng, Shijie; Zhang, Nan; Xia, Yanjun; Wang, Hongtao

    2014-03-01

    A new heuristic strategy for the non-uniform strain profile reconstruction along Fiber Bragg Gratings is proposed in this paper, which is based on the modified transfer matrix and Genetic Programming(GP) algorithm. The present method uses Genetic Programming to determine the applied strain field as a function of position along the fiber length. The structures that undergo adaptation in genetic programming are hierarchical structures which are different from that of conventional genetic algorithm operating on strings. GP regress the strain profile function which matches the 'measured' spectrum best and makes space resolution of strain reconstruction arbitrarily high, or even infinite. This paper also presents an experimental verification of the reconstruction of non-homogeneous strain fields using GP. The results are compared with numerical calculations of finite element method. Both the simulation examples and experimental results demonstrate that Genetic Programming can effectively reconstruct continuous profile expression along the whole FBG, and greatly improves its computational efficiency and accuracy.

  8. A reconstruction algorithm for three-dimensional object-space data using spatial-spectral multiplexing

    Science.gov (United States)

    Wu, Zhejun; Kudenov, Michael W.

    2017-05-01

    This paper presents a reconstruction algorithm for the Spatial-Spectral Multiplexing (SSM) optical system. The goal of this algorithm is to recover the three-dimensional spatial and spectral information of a scene, given that a one-dimensional spectrometer array is used to sample the pupil of the spatial-spectral modulator. The challenge of the reconstruction is that the non-parametric representation of the three-dimensional spatial and spectral object requires a large number of variables, thus leading to an underdetermined linear system that is hard to uniquely recover. We propose to reparameterize the spectrum using B-spline functions to reduce the number of unknown variables. Our reconstruction algorithm then solves the improved linear system via a least- square optimization of such B-spline coefficients with additional spatial smoothness regularization. The ground truth object and the optical model for the measurement matrix are simulated with both spatial and spectral assumptions according to a realistic field of view. In order to test the robustness of the algorithm, we add Poisson noise to the measurement and test on both two-dimensional and three-dimensional spatial and spectral scenes. Our analysis shows that the root mean square error of the recovered results can be achieved within 5.15%.

  9. An improved muon reconstruction algorithm for INO-ICAL experiment

    International Nuclear Information System (INIS)

    Bhattacharya, Kolahal; MandaI, Naba K.

    2013-01-01

    The charge current interaction of neutrino in INO-ICAL detector will be identified with a muon (μ ± ) in the detector whose kinematics is related with the kinematics of the neutrino. So, muon reconstruction is a very important step in achieving INO physics goals. The existing muon reconstruction package for INO-ICAL has poor performance in specific regimes of experimental interest: (a) for larger zenith angle (θ > 50°), (b) for lower energies (E < 1 GeV); mainly due to poor error propagation scheme insensitive to energy E, angle (θ, φ) and inhomogeneous magnetic field along the muon track. Since, a significant fraction of muons from atmospheric neutrino interactions will have initial energy < 1 GeV and almost uniform distribution in cosθ a robust package for muon reconstruction is essential. We have implemented higher order correction terms in the propagation of the state and error covariance matrices of the Kalman Iter. The algorithm ensures track element merging in most cases and also increases reconstruction efficiency. The performance of this package will be presented in comparison with the previous one. (author)

  10. A unified analysis of FBP-based algorithms in helical cone-beam and circular cone- and fan-beam scans

    International Nuclear Information System (INIS)

    Pan Xiaochuan; Xia Dan; Zou Yu; Yu Lifeng

    2004-01-01

    A circular scanning trajectory is and will likely remain a popular choice of trajectory in computed tomography (CT) imaging because it is easy to implement and control. Filtered-backprojection (FBP)-based algorithms have been developed previously for approximate and exact reconstruction of the entire image or a region of interest within the image in circular cone-beam and fan-beam cases. Recently, we have developed a 3D FBP-based algorithm for image reconstruction on PI-line segments in a helical cone-beam scan. In this work, we demonstrated that the 3D FBP-based algorithm indeed provided a rather general formulation for image reconstruction from divergent projections (such as cone-beam and fan-beam projections). On the basis of this formulation we derived new approximate or exact algorithms for image reconstruction in circular cone-beam or fan-beam scans, which can be interpreted as special cases of the helical scan. Existing algorithms corresponding to the derived algorithms were identified. We also performed a preliminary numerical study to verify our theoretical results in each of the cases. The results in the work can readily be generalized to other non-circular trajectories

  11. a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

    Science.gov (United States)

    Ma, Xin; Xiang, Chengzhi; Gong, Wei

    2016-06-01

    Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

  12. Algorithm for three dimension reconstruction of magnetic resonance tomographs and X-ray images based on Fast Fourier Transform; Algoritmo para reconstrucao tridimensional de imagens de tomografos de ressonancia magnetica e de raio-X baseado no uso de Transformada Rapida de Fourier

    Energy Technology Data Exchange (ETDEWEB)

    Bueno, Josiane M.; Traina, Agma Juci M. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Inst. de Ciencias Matematicas; Cruvinel, Paulo E. [EMBRAPA, Sao Carlos, SP (Brazil). CNPDIA

    1995-12-31

    This work presents an algorithm for three-dimensional digital image reconstruction. Such algorithms based on the combination of both a Fast Fourier Transform method with Hamming Window and the use of a tri-linear interpolation function. The algorithm allows not only the generation of three-dimensional spatial spin distribution maps for Magnetic Resonance Tomography data but also X and Y-rays linear attenuation coefficient maps for CT scanners. Results demonstrates the usefulness of the algorithm in three-dimensional image reconstruction by doing first two-dimensional reconstruction and rather after interpolation. The algorithm was developed in C++ language, and there are two available versions: one under the DOS environment, and the other under the UNIX/Sun environment. (author) 10 refs., 5 figs.

  13. A new hybrid-FBP inversion algorithm with inverse distance backprojection weight for CT reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Narasimhadhan, A.V.; Rajgopal, Kasi

    2011-07-01

    This paper presents a new hybrid filtered backprojection (FBP) algorithm for fan-beam and cone-beam scan. The hybrid reconstruction kernel is the sum of the ramp and Hilbert filters. We modify the redundancy weighting function to reduce the inverse square distance weighting in the backprojection to inverse distance weight. The modified weight also eliminates the derivative associated with the Hilbert filter kernel. Thus, the proposed reconstruction algorithm has the advantages of the inverse distance weight in the backprojection. We evaluate the performance of the new algorithm in terms of the magnitude level and uniformity in noise for the fan-beam geometry. The computer simulations show that the spatial resolution is nearly identical to the standard fan-beam ramp filtered algorithm while the noise is spatially uniform and the noise variance is reduced. (orig.)

  14. A cone-beam reconstruction algorithm using shift-variant filtering and cone-beam backprojection

    International Nuclear Information System (INIS)

    Defrise, M.; Clack, R.

    1994-01-01

    An exact inversion formula written in the form of shift-variant filtered-backprojection (FBP) is given for reconstruction from cone-beam data taken from any orbit satisfying Tuy's sufficiency conditions. The method is based on a result of Grangeat, involving the derivative of the three-dimensional (3-D) Radon transform, but unlike Grangeat's algorithm, no 3D rebinning step is required. Data redundancy, which occurs when several cone-beam projections supply the same values in the Radon domain, is handled using an elegant weighting function and without discarding data. The algorithm is expressed in a convenient cone-beam detector reference frame, and a specific example for the case of a dual orthogonal circular orbit is presented. When the method is applied to a single circular orbit, it is shown to be equivalent to the well-known algorithm of Feldkamp et al

  15. NUFFT-Based Iterative Image Reconstruction via Alternating Direction Total Variation Minimization for Sparse-View CT

    Directory of Open Access Journals (Sweden)

    Bin Yan

    2015-01-01

    Full Text Available Sparse-view imaging is a promising scanning method which can reduce the radiation dose in X-ray computed tomography (CT. Reconstruction algorithm for sparse-view imaging system is of significant importance. The adoption of the spatial iterative algorithm for CT image reconstruction has a low operation efficiency and high computation requirement. A novel Fourier-based iterative reconstruction technique that utilizes nonuniform fast Fourier transform is presented in this study along with the advanced total variation (TV regularization for sparse-view CT. Combined with the alternating direction method, the proposed approach shows excellent efficiency and rapid convergence property. Numerical simulations and real data experiments are performed on a parallel beam CT. Experimental results validate that the proposed method has higher computational efficiency and better reconstruction quality than the conventional algorithms, such as simultaneous algebraic reconstruction technique using TV method and the alternating direction total variation minimization approach, with the same time duration. The proposed method appears to have extensive applications in X-ray CT imaging.

  16. Reconstructing Genetic Regulatory Networks Using Two-Step Algorithms with the Differential Equation Models of Neural Networks.

    Science.gov (United States)

    Chen, Chi-Kan

    2017-07-26

    The identification of genetic regulatory networks (GRNs) provides insights into complex cellular processes. A class of recurrent neural networks (RNNs) captures the dynamics of GRN. Algorithms combining the RNN and machine learning schemes were proposed to reconstruct small-scale GRNs using gene expression time series. We present new GRN reconstruction methods with neural networks. The RNN is extended to a class of recurrent multilayer perceptrons (RMLPs) with latent nodes. Our methods contain two steps: the edge rank assignment step and the network construction step. The former assigns ranks to all possible edges by a recursive procedure based on the estimated weights of wires of RNN/RMLP (RE RNN /RE RMLP ), and the latter constructs a network consisting of top-ranked edges under which the optimized RNN simulates the gene expression time series. The particle swarm optimization (PSO) is applied to optimize the parameters of RNNs and RMLPs in a two-step algorithm. The proposed RE RNN -RNN and RE RMLP -RNN algorithms are tested on synthetic and experimental gene expression time series of small GRNs of about 10 genes. The experimental time series are from the studies of yeast cell cycle regulated genes and E. coli DNA repair genes. The unstable estimation of RNN using experimental time series having limited data points can lead to fairly arbitrary predicted GRNs. Our methods incorporate RNN and RMLP into a two-step structure learning procedure. Results show that the RE RMLP using the RMLP with a suitable number of latent nodes to reduce the parameter dimension often result in more accurate edge ranks than the RE RNN using the regularized RNN on short simulated time series. Combining by a weighted majority voting rule the networks derived by the RE RMLP -RNN using different numbers of latent nodes in step one to infer the GRN, the method performs consistently and outperforms published algorithms for GRN reconstruction on most benchmark time series. The framework of two

  17. High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaoming, E-mail: mmayzy2008@126.com; Li, Tao, E-mail: litaofeivip@163.com; Li, Xin, E-mail: lx0803@sina.com.cn; Zhou, Weihua, E-mail: wangxue0606@gmail.com

    2015-05-15

    Highlights: • High-resolution scan mode is appropriate for imaging coronary stent. • HD-detail reconstruction algorithm is stent-dedicated kernel. • The intrastent lumen visibility also depends on stent diameter and material. - Abstract: Objective: The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Materials and methods: Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. Results: The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0 ± 8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Conclusions: Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement.

  18. Iterative image reconstruction algorithms in coronary CT angiography improve the detection of lipid-core plaque - a comparison with histology

    International Nuclear Information System (INIS)

    Puchner, Stefan B.; Ferencik, Maros; Maurovich-Horvat, Pal; Nakano, Masataka; Otsuka, Fumiyuki; Virmani, Renu; Kauczor, Hans-Ulrich; Hoffmann, Udo; Schlett, Christopher L.

    2015-01-01

    To evaluate whether iterative reconstruction algorithms improve the diagnostic accuracy of coronary CT angiography (CCTA) for detection of lipid-core plaque (LCP) compared to histology. CCTA and histological data were acquired from three ex vivo hearts. CCTA images were reconstructed using filtered back projection (FBP), adaptive-statistical (ASIR) and model-based (MBIR) iterative algorithms. Vessel cross-sections were co-registered between FBP/ASIR/MBIR and histology. Plaque area 2 : 5.78 ± 2.29 vs. 3.39 ± 1.68 FBP; 5.92 ± 1.87 vs. 3.43 ± 1.62 ASIR; 6.40 ± 1.55 vs. 3.49 ± 1.50 MBIR; all p < 0.0001). AUC for detecting LCP was 0.803/0.850/0.903 for FBP/ASIR/MBIR and was significantly higher for MBIR compared to FBP (p = 0.01). MBIR increased sensitivity for detection of LCP by CCTA. Plaque area <60 HU in CCTA was associated with LCP in histology regardless of the reconstruction algorithm. However, MBIR demonstrated higher accuracy for detecting LCP, which may improve vulnerable plaque detection by CCTA. (orig.)

  19. SU-E-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

    Energy Technology Data Exchange (ETDEWEB)

    Niemkiewicz, J; Palmiotti, A; Miner, M; Stunja, L; Bergene, J [Lehigh Valley Health Network, Allentown, PA (United States)

    2014-06-01

    Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU values were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation

  20. SU-E-J-218: Evaluation of CT Images Created Using a New Metal Artifact Reduction Reconstruction Algorithm for Radiation Therapy Treatment Planning

    International Nuclear Information System (INIS)

    Niemkiewicz, J; Palmiotti, A; Miner, M; Stunja, L; Bergene, J

    2014-01-01

    Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU values were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation

  1. Vascular diameter measurement in CT angiography: comparison of model-based iterative reconstruction and standard filtered back projection algorithms in vitro.

    Science.gov (United States)

    Suzuki, Shigeru; Machida, Haruhiko; Tanaka, Isao; Ueno, Eiko

    2013-03-01

    The purpose of this study was to evaluate the performance of model-based iterative reconstruction (MBIR) in measurement of the inner diameter of models of blood vessels and compare performance between MBIR and a standard filtered back projection (FBP) algorithm. Vascular models with wall thicknesses of 0.5, 1.0, and 1.5 mm were scanned with a 64-MDCT unit and densities of contrast material yielding 275, 396, and 542 HU. Images were reconstructed images by MBIR and FBP, and the mean diameter of each model vessel was measured by software automation. Twenty separate measurements were repeated for each vessel, and variance among the repeated measures was analyzed for determination of measurement error. For all nine model vessels, CT attenuation profiles were compared along a line passing through the luminal center on axial images reconstructed with FBP and MBIR, and the 10-90% edge rise distances at the boundary between the vascular wall and the lumen were evaluated. For images reconstructed with FBP, measurement errors were smallest for models with 1.5-mm wall thickness, except those filled with 275-HU contrast material, and errors grew as the density of the contrast material decreased. Measurement errors with MBIR were comparable to or less than those with FBP. In CT attenuation profiles of images reconstructed with MBIR, the 10-90% edge rise distances at the boundary between the lumen and vascular wall were relatively short for each vascular model compared with those of the profile curves of FBP images. MBIR is better than standard FBP for reducing reconstruction blur and improving the accuracy of diameter measurement at CT angiography.

  2. Metal-induced streak artifact reduction using iterative reconstruction algorithms in x-ray computed tomography image of the dentoalveolar region.

    Science.gov (United States)

    Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia

    2013-02-01

    The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Reconstruction Algorithms in Undersampled AFM Imaging

    DEFF Research Database (Denmark)

    Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen

    2016-01-01

    This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby...... the scanning time as well as the amount of interaction between the AFM probe and the specimen. It can easily be applied on conventional AFM hardware. Due to undersampling, it is then necessary to further process the acquired image in order to reconstruct an approximation of the image. Based on real AFM cell...... images, our simulations reveal that using a simple raster scanning pattern in combination with conventional image interpolation performs very well. Moreover, this combination enables a reduction by a factor 10 of the scanning time while retaining an average reconstruction quality around 36 dB PSNR...

  4. Structure-based bayesian sparse reconstruction

    KAUST Repository

    Quadeer, Ahmed Abdul; Al-Naffouri, Tareq Y.

    2012-01-01

    Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical

  5. Reconstruction algorithms in the Super-Kamiokande large water Cherenkov detector

    CERN Document Server

    Shiozawa, M

    1999-01-01

    The Super-Kamiokande experiment, using a large underground water Cherenkov detector, has started its operation since first April, 1996. One of the main physics goals of this experiment is to measure the atmospheric neutrinos. Proton decay search is also an important topic. For these analyses, all measurement of physical quantities of an event such as vertex position, the number of Cherenkov rings, momentum, particle type and the number of decay electrons, is automatically performed by reconstruction algorithms. We attain enough quality of the analyses using these algorithms and several impressive results have been addressed.

  6. Reconstruction algorithms in the Super-Kamiokande large water Cherenkov detector

    International Nuclear Information System (INIS)

    Shiozawa, M.

    1999-01-01

    The Super-Kamiokande experiment, using a large underground water Cherenkov detector, has started its operation since first April, 1996. One of the main physics goals of this experiment is to measure the atmospheric neutrinos. Proton decay search is also an important topic. For these analyses, all measurement of physical quantities of an event such as vertex position, the number of Cherenkov rings, momentum, particle type and the number of decay electrons, is automatically performed by reconstruction algorithms. We attain enough quality of the analyses using these algorithms and several impressive results have been addressed

  7. An Algorithmic Approach for the Reconstruction of Nasal Skin Defects: Retrospective Analysis of 130 Cases

    Directory of Open Access Journals (Sweden)

    Berrak Akşam

    2016-06-01

    Full Text Available Objective: Most of the malignant cutaneous carcinomas are seen in the nasal region. Reconstruction of nasal defects is challenging because of the unique anatomic properties and complex structure of this region. In this study, we present our algorithm for the nasal skin defects that occurred after malignant skin tumor excisions. Material and Methods: Patients whose nasal skin was reconstructed after malignant skin tumor excision were included in the study. These patients were evaluated by their age, gender, comorbities, tumor location, tumor size, reconstruction type, histopathological diagnosis, and tumor recurrence. Results: A total of 130 patients (70 female, 60 male were evaluated. The average age of the patients was 67.8 years. Tumors were located mostly at the dorsum, alar region, and tip of the nose. When reconstruction methods were evaluated, primary closure was preferred in 14.6% patients, full thickness skin grafts were used in 25.3% patients, and reconstruction with flaps were the choice in 60% patients. Different flaps were used according to the subunits. Mostly, dorsal nasal flaps, bilobed flaps, nasolabial flaps, and forehead flaps were used. Conclusion: The defect-only reconstruction principle was accepted in this study. Previously described subunits, such as the dorsum, tip, alar region, lateral wall, columella, and soft triangles, of the nose were further divided into subregions by their anatomical relations. An algorithm was planned with these sub regions. In nasal skin reconstruction, this algorithm helps in selection the methods for the best results and minimize the complications.

  8. Performance Comparison of Reconstruction Algorithms in Discrete Blind Multi-Coset Sampling

    DEFF Research Database (Denmark)

    Grigoryan, Ruben; Arildsen, Thomas; Tandur, Deepaknath

    2012-01-01

    This paper investigates the performance of different reconstruction algorithms in discrete blind multi-coset sampling. Multi-coset scheme is a promising compressed sensing architecture that can replace traditional Nyquist-rate sampling in the applications with multi-band frequency sparse signals...

  9. The Retina Algorithm

    CERN Multimedia

    CERN. Geneva; PUNZI, Giovanni

    2015-01-01

    Charge particle reconstruction is one of the most demanding computational tasks found in HEP, and it becomes increasingly important to perform it in real time. We envision that HEP would greatly benefit from achieving a long-term goal of making track reconstruction happen transparently as part of the detector readout ("detector-embedded tracking"). We describe here a track-reconstruction approach based on a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature ('RETINA algorithm'). It turns out that high-quality tracking in large HEP detectors is possible with very small latencies, when this algorithm is implemented in specialized processors, based on current state-of-the-art, high-speed/high-bandwidth digital devices.

  10. Structure-Based Algorithms for Microvessel Classification

    KAUST Repository

    Smith, Amy F.

    2015-02-01

    © 2014 The Authors. Microcirculation published by John Wiley & Sons Ltd. Objective: Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods: Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results: The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions: The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries, and venules.

  11. Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography.

    Science.gov (United States)

    Benz, Dominik C; Fuchs, Tobias A; Gräni, Christoph; Studer Bruengger, Annina A; Clerc, Olivier F; Mikulicic, Fran; Messerli, Michael; Stehli, Julia; Possner, Mathias; Pazhenkottil, Aju P; Gaemperli, Oliver; Kaufmann, Philipp A; Buechel, Ronny R

    2018-02-01

    Iterative reconstruction (IR) algorithms allow for a significant reduction in radiation dose of coronary computed tomography angiography (CCTA). We performed a head-to-head comparison of adaptive statistical IR (ASiR) and model-based IR (MBIR) algorithms to assess their impact on quantitative image parameters and diagnostic accuracy for submillisievert CCTA. CCTA datasets of 91 patients were reconstructed using filtered back projection (FBP), increasing contributions of ASiR (20, 40, 60, 80, and 100%), and MBIR. Signal and noise were measured in the aortic root to calculate signal-to-noise ratio (SNR). In a subgroup of 36 patients, diagnostic accuracy of ASiR 40%, ASiR 100%, and MBIR for diagnosis of coronary artery disease (CAD) was compared with invasive coronary angiography. Median radiation dose was 0.21 mSv for CCTA. While increasing levels of ASiR gradually reduced image noise compared with FBP (up to - 48%, P ASiR (-59% compared with ASiR 100%; P ASiR 40% and ASiR 100% resulted in substantially lower diagnostic accuracy to detect CAD as diagnosed by invasive coronary angiography compared with MBIR: sensitivity and specificity were 100 and 37%, 100 and 57%, and 100 and 74% for ASiR 40%, ASiR 100%, and MBIR, respectively. MBIR offers substantial noise reduction with increased SNR, paving the way for implementation of submillisievert CCTA protocols in clinical routine. In contrast, inferior noise reduction by ASiR negatively affects diagnostic accuracy of submillisievert CCTA for CAD detection. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

  12. Strategies of reconstruction algorithms for computerized tomography

    International Nuclear Information System (INIS)

    Garderet, P.

    1984-10-01

    Image reconstruction from projections has progressively spread out over all fields of medical imaging. As the mathematical aspects of the problem become more and more comprehensively explored a great variety of numerical solutions have been developed best suited to such-and-such imaging medical application and taking into account the physical phenomena related to data collection (a priori properties for signal and noise). The purpose of that survey is to present the general mathematical frame and the fundamental assumptions of various strategies; Fourier methods approximate explicit deterministic inversion formula for the Radon transform. Algebraic reconstruction techniques set up an a priori discrete model through a series expansion approach of the solution. The numerical system to be solved is huge when a fine grid of pixels is to be reconstructed; iterative solutions may then be found. Recently some least square procedures have been shown to be tractable which avoid the use of iterative methods. Finally maximum like hood approach incorporates accurately the Poisson nature of photon noise and are well adapted to emission computed tomography. The various strategies will be analysed from both aspects of theoretical assumptions needed for suitable use and of computing facilities, actual performance and cost. In the end we take a glimpse of the extension of the algorithms from two dimensional imaging to fully three dimensional volume analysis in preparation of the future medical imaging technologies

  13. Autocorrelation based reconstruction of two-dimensional binary objects

    International Nuclear Information System (INIS)

    Mejia-Barbosa, Y.; Castaneda, R.

    2005-10-01

    A method for reconstructing two-dimensional binary objects from its autocorrelation function is discussed. The objects consist of a finite set of identical elements. The reconstruction algorithm is based on the concept of class of element pairs, defined as the set of element pairs with the same separation vector. This concept allows to solve the redundancy introduced by the element pairs of each class. It is also shown that different objects, consisting of an equal number of elements and the same classes of pairs, provide Fraunhofer diffraction patterns with identical intensity distributions. However, the method predicts all the possible objects that produce the same Fraunhofer pattern. (author)

  14. Tomographic reconstruction of binary fields

    International Nuclear Information System (INIS)

    Roux, Stéphane; Leclerc, Hugo; Hild, François

    2012-01-01

    A novel algorithm is proposed for reconstructing binary images from their projection along a set of different orientations. Based on a nonlinear transformation of the projection data, classical back-projection procedures can be used iteratively to converge to the sought image. A multiscale implementation allows for a faster convergence. The algorithm is tested on images up to 1 Mb definition, and an error free reconstruction is achieved with a very limited number of projection data, saving a factor of about 100 on the number of projections required for classical reconstruction algorithms.

  15. A multicenter evaluation of seven commercial ML-EM algorithms for SPECT image reconstruction using simulation data

    International Nuclear Information System (INIS)

    Matsumoto, Keiichi; Ohnishi, Hideo; Niida, Hideharu; Nishimura, Yoshihiro; Wada, Yasuhiro; Kida, Tetsuo

    2003-01-01

    The maximum likelihood expectation maximization (ML-EM) algorithm has become available as an alternative to filtered back projection in SPECT. The actual physical performance may be different depending on the manufacturer and model, because of differences in computational details. The purpose of this study was to investigate the characteristics of seven different types of ML-EM algorithms using simple simulation data. Seven ML-EM algorithm programs were used: Genie (GE), esoft (Siemens), HARP-III (Hitachi), GMS-5500UI (Toshiba), Pegasys (ADAC), ODYSSEY-FX (Marconi), and Windows-PC (original software). Projection data of a 2-pixel-wide line source in the center of the field of view were simulated without attenuation or scatter. Images were reconstructed with ML-EM by changing the number of iterations from 1 to 45 for each algorithm. Image quality was evaluated after a reconstruction using full width at half maximum (FWHM), full width at tenth maximum (FWTM), and the total counts of the reconstructed images. In the maximum number of iterations, the difference in the FWHM value was up to 1.5 pixels, and that of FWTM, no less than 2.0 pixels. The total counts of the reconstructed images in the initial few iterations were larger or smaller than the converged value depending on the initial values. Our results for the simplest simulation data suggest that each ML-EM algorithm itself provides a simulation image. We should keep in mind which algorithm is being used and its computational details, when physical and clinical usefulness are compared. (author)

  16. Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM☆

    Science.gov (United States)

    López, J.D.; Litvak, V.; Espinosa, J.J.; Friston, K.; Barnes, G.R.

    2014-01-01

    The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy—an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. PMID:24041874

  17. High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm.

    Science.gov (United States)

    Cui, Xiaoming; Li, Tao; Li, Xin; Zhou, Weihua

    2015-05-01

    The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0±8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  18. Structure-based bayesian sparse reconstruction

    KAUST Repository

    Quadeer, Ahmed Abdul

    2012-12-01

    Sparse signal reconstruction algorithms have attracted research attention due to their wide applications in various fields. In this paper, we present a simple Bayesian approach that utilizes the sparsity constraint and a priori statistical information (Gaussian or otherwise) to obtain near optimal estimates. In addition, we make use of the rich structure of the sensing matrix encountered in many signal processing applications to develop a fast sparse recovery algorithm. The computational complexity of the proposed algorithm is very low compared with the widely used convex relaxation methods as well as greedy matching pursuit techniques, especially at high sparsity. © 1991-2012 IEEE.

  19. A comparison of semiglobal and local dense matching algorithms for surface reconstruction

    Directory of Open Access Journals (Sweden)

    E. Dall'Asta

    2014-06-01

    Full Text Available Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision. The paper is focused on the comparison of some stereo matching algorithms (local and global which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM, which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed. The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

  20. A comparison of semiglobal and local dense matching algorithms for surface reconstruction

    Science.gov (United States)

    Dall'Asta, E.; Roncella, R.

    2014-06-01

    Encouraged by the growing interest in automatic 3D image-based reconstruction, the development and improvement of robust stereo matching techniques is one of the most investigated research topic of the last years in photogrammetry and computer vision. The paper is focused on the comparison of some stereo matching algorithms (local and global) which are very popular both in photogrammetry and computer vision. In particular, the Semi-Global Matching (SGM), which realizes a pixel-wise matching and relies on the application of consistency constraints during the matching cost aggregation, will be discussed. The results of some tests performed on real and simulated stereo image datasets, evaluating in particular the accuracy of the obtained digital surface models, will be presented. Several algorithms and different implementation are considered in the comparison, using freeware software codes like MICMAC and OpenCV, commercial software (e.g. Agisoft PhotoScan) and proprietary codes implementing Least Square e Semi-Global Matching algorithms. The comparisons will also consider the completeness and the level of detail within fine structures, and the reliability and repeatability of the obtainable data.

  1. Array diagnostics, spatial resolution, and filtering of undesired radiation with the 3D reconstruction algorithm

    DEFF Research Database (Denmark)

    Cappellin, C.; Pivnenko, Sergey; Jørgensen, E.

    2013-01-01

    This paper focuses on three important features of the 3D reconstruction algorithm of DIATOOL: the identification of array elements improper functioning and failure, the obtainable spatial resolution of the reconstructed fields and currents, and the filtering of undesired radiation and scattering...

  2. Performance of the reconstruction algorithms of the FIRST experiment pixel sensors vertex detector

    Energy Technology Data Exchange (ETDEWEB)

    Rescigno, R., E-mail: regina.rescigno@iphc.cnrs.fr [Institut Pluridisciplinaire Hubert Curien, 23 rue du Loess, 67037 Strasbourg Cedex 2 (France); Finck, Ch.; Juliani, D. [Institut Pluridisciplinaire Hubert Curien, 23 rue du Loess, 67037 Strasbourg Cedex 2 (France); Spiriti, E. [Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali di Frascati (Italy); Istituto Nazionale di Fisica Nucleare - Sezione di Roma 3 (Italy); Baudot, J. [Institut Pluridisciplinaire Hubert Curien, 23 rue du Loess, 67037 Strasbourg Cedex 2 (France); Abou-Haidar, Z. [CNA, Sevilla (Spain); Agodi, C. [Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali del Sud (Italy); Alvarez, M.A.G. [CNA, Sevilla (Spain); Aumann, T. [GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt (Germany); Battistoni, G. [Istituto Nazionale di Fisica Nucleare - Sezione di Milano (Italy); Bocci, A. [CNA, Sevilla (Spain); Böhlen, T.T. [European Organization for Nuclear Research CERN, Geneva (Switzerland); Medical Radiation Physics, Karolinska Institutet and Stockholm University, Stockholm (Sweden); Boudard, A. [CEA-Saclay, IRFU/SPhN, Gif sur Yvette Cedex (France); Brunetti, A.; Carpinelli, M. [Istituto Nazionale di Fisica Nucleare - Sezione di Cagliari (Italy); Università di Sassari (Italy); Cirrone, G.A.P. [Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali del Sud (Italy); Cortes-Giraldo, M.A. [Departamento de Fisica Atomica, Molecular y Nuclear, University of Sevilla, 41080-Sevilla (Spain); Cuttone, G.; De Napoli, M. [Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali del Sud (Italy); Durante, M. [GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt (Germany); and others

    2014-12-11

    Hadrontherapy treatments use charged particles (e.g. protons and carbon ions) to treat tumors. During a therapeutic treatment with carbon ions, the beam undergoes nuclear fragmentation processes giving rise to significant yields of secondary charged particles. An accurate prediction of these production rates is necessary to estimate precisely the dose deposited into the tumours and the surrounding healthy tissues. Nowadays, a limited set of double differential carbon fragmentation cross-section is available. Experimental data are necessary to benchmark Monte Carlo simulations for their use in hadrontherapy. The purpose of the FIRST experiment is to study nuclear fragmentation processes of ions with kinetic energy in the range from 100 to 1000 MeV/u. Tracks are reconstructed using information from a pixel silicon detector based on the CMOS technology. The performances achieved using this device for hadrontherapy purpose are discussed. For each reconstruction step (clustering, tracking and vertexing), different methods are implemented. The algorithm performances and the accuracy on reconstructed observables are evaluated on the basis of simulated and experimental data.

  3. A stand-alone track reconstruction algorithm for the scintillating fibre tracker at the LHCb upgrade

    CERN Multimedia

    Quagliani, Renato

    2017-01-01

    The LHCb upgrade detector project foresees the presence of a scintillating fiber tracker (SciFi) to be used during the LHC Run III, starting in 2020. The instantaneous luminosity will be increased up to $2\\times10^{33}$, five times larger than in Run II and a full software event reconstruction will be performed at the full bunch crossing rate by the trigger. The new running conditions, and the tighter timing constraints in the software trigger, represent a big challenge for track reconstruction. This poster presents the design and performance of a novel algorithm that has been developed to reconstruct track segments using solely hits from the SciFi. This algorithm is crucial for the reconstruction of tracks originating from long-lived particles such as $K_{S}^{0}$ and $\\Lambda$ and allows to greatly enhance the physics potential and capabilities of the LHCb upgrade when compared to its previous implementation.

  4. Comparison of adaptive statistical iterative reconstruction (ASiRTM) and model-based iterative reconstruction (VeoTM) for paediatric abdominal CT examinations: an observer performance study of diagnostic image quality

    International Nuclear Information System (INIS)

    Hultenmo, Maria; Caisander, Haakan; Mack, Karsten; Thilander-Klang, Anne

    2016-01-01

    The diagnostic image quality of 75 paediatric abdominal computed tomography (CT) examinations reconstructed with two different iterative reconstruction (IR) algorithms-adaptive statistical IR (ASiR TM ) and model-based IR (Veo TM )-was compared. Axial and coronal images were reconstructed with 70 % ASiR with the Soft TM convolution kernel and with the Veo algorithm. The thickness of the reconstructed images was 2.5 or 5 mm depending on the scanning protocol used. Four radiologists graded the delineation of six abdominal structures and the diagnostic usefulness of the image quality. The Veo reconstruction significantly improved the visibility of most of the structures compared with ASiR in all subgroups of images. For coronal images, the Veo reconstruction resulted in significantly improved ratings of the diagnostic use of the image quality compared with the ASiR reconstruction. This was not seen for the axial images. The greatest improvement using Veo reconstruction was observed for the 2.5 mm coronal slices. (authors)

  5. Parallel Algorithm for Reconstruction of TAC Images

    International Nuclear Information System (INIS)

    Vidal Gimeno, V.

    2012-01-01

    The algebraic reconstruction methods are based on solving a system of linear equations. In a previous study, was used and showed as the PETSc library, was and is a scientific computing tool, which facilitates and enables the optimal use of a computer system in the image reconstruction process.

  6. Shape reconstruction from apparent contours theory and algorithms

    CERN Document Server

    Bellettini, Giovanni; Paolini, Maurizio

    2015-01-01

    Motivated by a variational model concerning the depth of the objects in a picture and the problem of hidden and illusory contours, this book investigates one of the central problems of computer vision: the topological and algorithmic reconstruction of a smooth three dimensional scene starting from the visible part of an apparent contour. The authors focus their attention on the manipulation of apparent contours using a finite set of elementary moves, which correspond to diffeomorphic deformations of three dimensional scenes. A large part of the book is devoted to the algorithmic part, with implementations, experiments, and computed examples. The book is intended also as a user's guide to the software code appcontour, written for the manipulation of apparent contours and their invariants. This book is addressed to theoretical and applied scientists working in the field of mathematical models of image segmentation.

  7. Real time equilibrium reconstruction algorithm in EAST tokamak

    International Nuclear Information System (INIS)

    Wang Huazhong; Luo Jiarong; Huang Qinchao

    2004-01-01

    The EAST (HT-7U) superconducting tokamak is a national project of China on fusion research, with a capability of long-pulse (∼1000 s) operation. In order to realize a long-duration steady-state operation of EAST, some significant capability of real-time control is required. It would be very crucial to obtain the current profile parameters and the plasma shapes in real time by a flexible control system. As those discharge parameters cannot be directly measured, so a current profile consistent with the magnetohydrodynamic equilibrium should be evaluated from external magnetic measurements, based on a linearized iterative least square method, which can meet the requirements of the measurements. The arithmetic that the EFIT (equilibrium fitting code) is used for reference will be given in this paper and the computational efforts are reduced by parameterizing the current profile linearly in terms of a number of physical parameters. In order to introduce this reconstruction algorithm clearly, the main hardware design will be listed also. (authors)

  8. A computationally efficient OMP-based compressed sensing reconstruction for dynamic MRI

    International Nuclear Information System (INIS)

    Usman, M; Prieto, C; Schaeffter, T; Batchelor, P G; Odille, F; Atkinson, D

    2011-01-01

    Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved. (note)

  9. Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms.

    Science.gov (United States)

    Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng

    2017-08-21

    Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

  10. Reconstruction of convex bodies from surface tensors

    DEFF Research Database (Denmark)

    Kousholt, Astrid; Kiderlen, Markus

    2016-01-01

    We present two algorithms for reconstruction of the shape of convex bodies in the two-dimensional Euclidean space. The first reconstruction algorithm requires knowledge of the exact surface tensors of a convex body up to rank s for some natural number s. When only measurements subject to noise...... of surface tensors are available for reconstruction, we recommend to use certain values of the surface tensors, namely harmonic intrinsic volumes instead of the surface tensors evaluated at the standard basis. The second algorithm we present is based on harmonic intrinsic volumes and allows for noisy...... measurements. From a generalized version of Wirtinger's inequality, we derive stability results that are utilized to ensure consistency of both reconstruction procedures. Consistency of the reconstruction procedure based on measurements subject to noise is established under certain assumptions on the noise...

  11. Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

    International Nuclear Information System (INIS)

    Viana, R.S.; Yoriyaz, H.; Santos, A.

    2011-01-01

    The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)

  12. Conditional probability distribution associated to the E-M image reconstruction algorithm for neutron stimulated emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Viana, R.S.; Yoriyaz, H.; Santos, A., E-mail: rodrigossviana@gmail.com, E-mail: hyoriyaz@ipen.br, E-mail: asantos@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2011-07-01

    The Expectation-Maximization (E-M) algorithm is an iterative computational method for maximum likelihood (M-L) estimates, useful in a variety of incomplete-data problems. Due to its stochastic nature, one of the most relevant applications of E-M algorithm is the reconstruction of emission tomography images. In this paper, the statistical formulation of the E-M algorithm was applied to the in vivo spectrographic imaging of stable isotopes called Neutron Stimulated Emission Computed Tomography (NSECT). In the process of E-M algorithm iteration, the conditional probability distribution plays a very important role to achieve high quality image. This present work proposes an alternative methodology for the generation of the conditional probability distribution associated to the E-M reconstruction algorithm, using the Monte Carlo code MCNP5 and with the application of the reciprocity theorem. (author)

  13. Reconstruction of convex bodies from surface tensors

    DEFF Research Database (Denmark)

    Kousholt, Astrid; Kiderlen, Markus

    We present two algorithms for reconstruction of the shape of convex bodies in the two-dimensional Euclidean space. The first reconstruction algorithm requires knowledge of the exact surface tensors of a convex body up to rank s for some natural number s. The second algorithm uses harmonic intrinsic...... volumes which are certain values of the surface tensors and allows for noisy measurements. From a generalized version of Wirtinger's inequality, we derive stability results that are utilized to ensure consistency of both reconstruction procedures. Consistency of the reconstruction procedure based...

  14. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    International Nuclear Information System (INIS)

    Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka

    2014-01-01

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

  15. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    Energy Technology Data Exchange (ETDEWEB)

    Shieh, Chun-Chien [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006, Australia and Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia); Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J., E-mail: paul.keall@sydney.edu.au [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006 (Australia); Kuncic, Zdenka [Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia)

    2014-04-15

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

  16. Application aspects of advanced antenna diagnostics with the 3D reconstruction algorithm

    DEFF Research Database (Denmark)

    Cappellin, Cecilia; Pivnenko, Sergey

    2015-01-01

    This paper focuses on two important applications of the 3D reconstruction algorithm of the commercial software DIATOOL for antenna diagnostics. The first one is the accurate and detailed identification of array malfunctioning, thanks to the available enhanced spatial resolution of the reconstruct...... fields and currents. The second one is the filtering of the scattering from support structures and feed network leakage. Representative experimental results are presented and guidelines on the recommended measurement parameters for obtaining the best diagnostics results are provided....

  17. Virtual patient 3D dose reconstruction using in air EPID measurements and a back-projection algorithm for IMRT and VMAT treatments.

    Science.gov (United States)

    Olaciregui-Ruiz, Igor; Rozendaal, Roel; van Oers, René F M; Mijnheer, Ben; Mans, Anton

    2017-05-01

    At our institute, a transit back-projection algorithm is used clinically to reconstruct in vivo patient and in phantom 3D dose distributions using EPID measurements behind a patient or a polystyrene slab phantom, respectively. In this study, an extension to this algorithm is presented whereby in air EPID measurements are used in combination with CT data to reconstruct 'virtual' 3D dose distributions. By combining virtual and in vivo patient verification data for the same treatment, patient-related errors can be separated from machine, planning and model errors. The virtual back-projection algorithm is described and verified against the transit algorithm with measurements made behind a slab phantom, against dose measurements made with an ionization chamber and with the OCTAVIUS 4D system, as well as against TPS patient data. Virtual and in vivo patient dose verification results are also compared. Virtual dose reconstructions agree within 1% with ionization chamber measurements. The average γ-pass rate values (3% global dose/3mm) in the 3D dose comparison with the OCTAVIUS 4D system and the TPS patient data are 98.5±1.9%(1SD) and 97.1±2.9%(1SD), respectively. For virtual patient dose reconstructions, the differences with the TPS in median dose to the PTV remain within 4%. Virtual patient dose reconstruction makes pre-treatment verification based on deviations of DVH parameters feasible and eliminates the need for phantom positioning and re-planning. Virtual patient dose reconstructions have additional value in the inspection of in vivo deviations, particularly in situations where CBCT data is not available (or not conclusive). Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  18. MAP-MRF-Based Super-Resolution Reconstruction Approach for Coded Aperture Compressive Temporal Imaging

    Directory of Open Access Journals (Sweden)

    Tinghua Zhang

    2018-02-01

    Full Text Available Coded Aperture Compressive Temporal Imaging (CACTI can afford low-cost temporal super-resolution (SR, but limits are imposed by noise and compression ratio on reconstruction quality. To utilize inter-frame redundant information from multiple observations and sparsity in multi-transform domains, a robust reconstruction approach based on maximum a posteriori probability and Markov random field (MAP-MRF model for CACTI is proposed. The proposed approach adopts a weighted 3D neighbor system (WNS and the coordinate descent method to perform joint estimation of model parameters, to achieve the robust super-resolution reconstruction. The proposed multi-reconstruction algorithm considers both total variation (TV and ℓ 2 , 1 norm in wavelet domain to address the minimization problem for compressive sensing, and solves it using an accelerated generalized alternating projection algorithm. The weighting coefficient for different regularizations and frames is resolved by the motion characteristics of pixels. The proposed approach can provide high visual quality in the foreground and background of a scene simultaneously and enhance the fidelity of the reconstruction results. Simulation results have verified the efficacy of our new optimization framework and the proposed reconstruction approach.

  19. Analytical algorithm for the generation of polygonal projection data for tomographic reconstruction

    International Nuclear Information System (INIS)

    Davis, G.R.

    1996-01-01

    Tomographic reconstruction algorithms and filters can be tested using a mathematical phantom, that is, a computer program which takes numerical data as its input and outputs derived projection data. The input data is usually in the form of pixel ''densities'' over a regular grid, or position and dimensions of simple, geometrical objects. The former technique allows a greater variety of objects to be simulated, but is less suitable in the case when very small (relative to the ray-spacing) features are to be simulated. The second technique is normally used to simulate biological specimens, typically a human skull, modelled as a number of ellipses. This is not suitable for simulating non-biological specimens with features such as straight edges and fine cracks. We have therefore devised an algorithm for simulating objects described as a series of polygons. These polygons, or parts of them, may be smaller than the ray-spacing and there is no limit, except that imposed by computing resources, on the complexity, number or superposition of polygons. A simple test of such a phantom, reconstructed using the filtered back-projection method, revealed reconstruction artefacts not normally seen with ''biological'' phantoms. (orig.)

  20. Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis

    International Nuclear Information System (INIS)

    Kim, Kyungsang; Ye, Jong Chul; Son, Young Don; Cho, Zang Hee; Bresler, Yoram; Ra, Jong Beom

    2015-01-01

    Dynamic positron emission tomography (PET) is widely used to measure changes in the bio-distribution of radiopharmaceuticals within particular organs of interest over time. However, to retain sufficient temporal resolution, the number of photon counts in each time frame must be limited. Therefore, conventional reconstruction algorithms such as the ordered subset expectation maximization (OSEM) produce noisy reconstruction images, thus degrading the quality of the extracted time activity curves (TACs). To address this issue, many advanced reconstruction algorithms have been developed using various spatio-temporal regularizations. In this paper, we extend earlier results and develop a novel temporal regularization, which exploits the self-similarity of patches that are collected in dynamic images. The main contribution of this paper is to demonstrate that the correlation of patches can be exploited using a low-rank constraint that is insensitive to global intensity variations. The resulting optimization framework is, however, non-Lipschitz and non-convex due to the Poisson log-likelihood and low-rank penalty terms. Direct application of the conventional Poisson image deconvolution by an augmented Lagrangian (PIDAL) algorithm is, however, problematic due to its large memory requirements, which prevents its parallelization. Thus, we propose a novel optimization framework using the concave-convex procedure (CCCP) by exploiting the Legendre–Fenchel transform, which is computationally efficient and parallelizable. In computer simulation and a real in vivo experiment using a high-resolution research tomograph (HRRT) scanner, we confirm that the proposed algorithm can improve image quality while also extracting more accurate region of interests (ROI) based kinetic parameters. Furthermore, we show that the total reconstruction time for HRRT PET is significantly accelerated using our GPU implementation, which makes the algorithm very practical in clinical environments

  1. SU-F-T-261: Reconstruction of Initial Photon Fluence Based On EPID Images

    Energy Technology Data Exchange (ETDEWEB)

    Seliger, T; Engenhart-Cabillic, R [Philipp University of Marburg, Marburg (Germany); Czarnecki, D; Maeder, U; Zink, K [Technische Hochschule Mittelhessen - University of Applied Sciences, Giessen (Germany); Kussaether, R [MedCom GmbH, Darmstadt (Germany); Poppe, B [University Hospital for Medical Radiation Physics, Pius-Hospital, Medical Campus, Carl von Ossietzky University of Oldenburg (Germany)

    2016-06-15

    Purpose: Verifying an algorithm to reconstruct relative initial photon fluence for clinical use. Clinical EPID and CT images were acquired to reconstruct an external photon radiation treatment field. The reconstructed initial photon fluence could be used to verify the treatment or calculate the applied dose to the patient. Methods: The acquired EPID images were corrected for scatter caused by the patient and the EPID with an iterative reconstruction algorithm. The transmitted photon fluence behind the patient was calculated subsequently. Based on the transmitted fluence the initial photon fluence was calculated using a back-projection algorithm which takes the patient geometry and its energy dependent linear attenuation into account. This attenuation was gained from the acquired cone-beam CT or the planning CT by calculating a water-equivalent radiological thickness for each irradiation direction. To verify the algorithm an inhomogeneous phantom consisting of three inhomogeneities was irradiated by a static 6 MV photon field and compared to a reference flood field image. Results: The mean deviation between the reconstructed relative photon fluence for the inhomogeneous phantom and the flood field EPID image was 3% rising up to 7% for off-axis fluence. This was probably caused by the used clinical EPID calibration, which flattens the inhomogeneous fluence profile of the beam. Conclusion: In this clinical experiment the algorithm achieved good results in the center of the field while it showed high deviation of the lateral fluence. This could be reduced by optimizing the EPID calibration, considering the off-axis differential energy response. In further progress this and other aspects of the EPID, eg. field size dependency, CT and dose calibration have to be studied to realize a clinical acceptable accuracy of 2%.

  2. Evaluation of noise and blur effects with SIRT-FISTA-TV reconstruction algorithm: Application to fast environmental transmission electron tomography.

    Science.gov (United States)

    Banjak, Hussein; Grenier, Thomas; Epicier, Thierry; Koneti, Siddardha; Roiban, Lucian; Gay, Anne-Sophie; Magnin, Isabelle; Peyrin, Françoise; Maxim, Voichita

    2018-06-01

    Fast tomography in Environmental Transmission Electron Microscopy (ETEM) is of a great interest for in situ experiments where it allows to observe 3D real-time evolution of nanomaterials under operating conditions. In this context, we are working on speeding up the acquisition step to a few seconds mainly with applications on nanocatalysts. In order to accomplish such rapid acquisitions of the required tilt series of projections, a modern 4K high-speed camera is used, that can capture up to 100 images per second in a 2K binning mode. However, due to the fast rotation of the sample during the tilt procedure, noise and blur effects may occur in many projections which in turn would lead to poor quality reconstructions. Blurred projections make classical reconstruction algorithms inappropriate and require the use of prior information. In this work, a regularized algebraic reconstruction algorithm named SIRT-FISTA-TV is proposed. The performance of this algorithm using blurred data is studied by means of a numerical blur introduced into simulated images series to mimic possible mechanical instabilities/drifts during fast acquisitions. We also present reconstruction results from noisy data to show the robustness of the algorithm to noise. Finally, we show reconstructions with experimental datasets and we demonstrate the interest of fast tomography with an ultra-fast acquisition performed under environmental conditions, i.e. gas and temperature, in the ETEM. Compared to classically used SIRT and SART approaches, our proposed SIRT-FISTA-TV reconstruction algorithm provides higher quality tomograms allowing easier segmentation of the reconstructed volume for a better final processing and analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Energy reconstruction and calibration algorithms for the ATLAS electromagnetic calorimeter

    CERN Document Server

    Delmastro, M

    2003-01-01

    The work of this thesis is devoted to the study, development and optimization of the algorithms of energy reconstruction and calibration for the electromagnetic calorimeter (EMC) of the ATLAS experiment, presently under installation and commissioning at the CERN Large Hadron Collider in Geneva (Switzerland). A deep study of the electrical characteristics of the detector and of the signals formation and propagation is conduced: an electrical model of the detector is developed and analyzed through simulations; a hardware model (mock-up) of a group of the EMC readout cells has been built, allowing the direct collection and properties study of the signals emerging from the EMC cells. We analyze the existing multiple-sampled signal reconstruction strategy, showing the need of an improvement in order to reach the advertised performances of the detector. The optimal filtering reconstruction technique is studied and implemented, taking into account the differences between the ionization and calibration waveforms as e...

  4. Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers

    International Nuclear Information System (INIS)

    Tseng, Hsin-Wu; Kupinski, Matthew A.; Fan, Jiahua; Sainath, Paavana; Hsieh, Jiang

    2014-01-01

    Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors’ task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the

  5. Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

    Science.gov (United States)

    López, J D; Litvak, V; Espinosa, J J; Friston, K; Barnes, G R

    2014-01-01

    The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy-an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. © 2013. Published by Elsevier Inc. All rights reserved.

  6. WE-D-18A-04: How Iterative Reconstruction Algorithms Affect the MTFs of Variable-Contrast Targets in CT Images

    Energy Technology Data Exchange (ETDEWEB)

    Dodge, C.T.; Rong, J. [MD Anderson Cancer Center, Houston, TX (United States); Dodge, C.W. [Methodist Hospital, Houston, TX (United States)

    2014-06-15

    Purpose: To determine how filtered back-projection (FBP), adaptive statistical (ASiR), and model based (MBIR) iterative reconstruction algorithms affect the measured modulation transfer functions (MTFs) of variable-contrast targets over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP401 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 24 mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 2.5mm thickness, 0.984 pitch. The images were reconstructed using GE's Standard kernel with FBP; 20%, 40% and 70% ASiR; and MBIR. A task-based MTF (MTFtask) was computed for six cylindrical targets: 2 low-contrast (Polystyrene, LDPE), 2 medium-contrast (Delrin, PMP), and 2 high-contrast (Teflon, air). MTFtask was used to compare the performance of reconstruction algorithms with decreasing CTDIvol from 24mGy, which is currently used in the clinic. Results: For the air target and 75% dose savings (6 mGy), MBIR MTFtask at 5 lp/cm measured 0.24, compared to 0.20 for 70% ASiR and 0.11 for FBP. Overall, for both high-contrast targets, MBIR MTFtask improved with increasing CTDIvol and consistently outperformed ASiR and FBP near the system's Nyquist frequency. Conversely, for Polystyrene at 6 mGy, MBIR (0.10) and 70% ASiR (0.07) MTFtask was lower than for FBP (0.18). For medium and low-contrast targets, FBP remains the best overall algorithm for improved resolution at low CTDIvol (1–6 mGy) levels, whereas MBIR is comparable at higher dose levels (12–24 mGy). Conclusion: MBIR improved the MTF of small, high-contrast targets compared to FBP and ASiR at doses of 50%–12.5% of those currently used in the clinic. However, for imaging low- and mediumcontrast targets, FBP performed the best across all dose levels. For assessing MTF from different reconstruction algorithms, task-based MTF measurements are necessary.

  7. WE-D-18A-04: How Iterative Reconstruction Algorithms Affect the MTFs of Variable-Contrast Targets in CT Images

    International Nuclear Information System (INIS)

    Dodge, C.T.; Rong, J.; Dodge, C.W.

    2014-01-01

    Purpose: To determine how filtered back-projection (FBP), adaptive statistical (ASiR), and model based (MBIR) iterative reconstruction algorithms affect the measured modulation transfer functions (MTFs) of variable-contrast targets over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP401 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 24 mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 2.5mm thickness, 0.984 pitch. The images were reconstructed using GE's Standard kernel with FBP; 20%, 40% and 70% ASiR; and MBIR. A task-based MTF (MTFtask) was computed for six cylindrical targets: 2 low-contrast (Polystyrene, LDPE), 2 medium-contrast (Delrin, PMP), and 2 high-contrast (Teflon, air). MTFtask was used to compare the performance of reconstruction algorithms with decreasing CTDIvol from 24mGy, which is currently used in the clinic. Results: For the air target and 75% dose savings (6 mGy), MBIR MTFtask at 5 lp/cm measured 0.24, compared to 0.20 for 70% ASiR and 0.11 for FBP. Overall, for both high-contrast targets, MBIR MTFtask improved with increasing CTDIvol and consistently outperformed ASiR and FBP near the system's Nyquist frequency. Conversely, for Polystyrene at 6 mGy, MBIR (0.10) and 70% ASiR (0.07) MTFtask was lower than for FBP (0.18). For medium and low-contrast targets, FBP remains the best overall algorithm for improved resolution at low CTDIvol (1–6 mGy) levels, whereas MBIR is comparable at higher dose levels (12–24 mGy). Conclusion: MBIR improved the MTF of small, high-contrast targets compared to FBP and ASiR at doses of 50%–12.5% of those currently used in the clinic. However, for imaging low- and mediumcontrast targets, FBP performed the best across all dose levels. For assessing MTF from different reconstruction algorithms, task-based MTF measurements are necessary

  8. Quantitative analysis of emphysema in 3D using MDCT: Influence of different reconstruction algorithms

    International Nuclear Information System (INIS)

    Ley-Zaporozhan, Julia; Ley, Sebastian; Weinheimer, Oliver; Iliyushenko, Svitlana; Erdugan, Serap; Eberhardt, Ralf; Fuxa, Adelheid; Mews, Juergen; Kauczor, Hans-Ulrich

    2008-01-01

    Purpose: The aim of the study was to compare the influence of different reconstruction algorithms on quantitative emphysema analysis in patients with severe emphysema. Material and methods: Twenty-five patients suffering from severe emphysema were included in the study. All patients underwent inspiratory MDCT (Aquilion-16, slice thickness 1/0.8 mm). The raw data were reconstructed using six different algorithms: bone kernel with beam hardening correction (BHC), soft tissue kernel with BHC; standard soft tissue kernel, smooth soft tissue kernel (internal reference standard), standard lung kernel, and high-convolution kernel. The only difference between image data sets was the algorithm employed to reconstruct the raw data, no additional radiation was required. CT data were analysed using self-written emphysema detection and quantification software providing lung volume, emphysema volume (EV), emphysema index (EI) and mean lung density (MLD). Results: The use of kernels with BHC led to a significant decrease in MLD (5%) and EI (61-79%) in comparison with kernels without BHC. The absolute difference (from smooth soft tissue kernel) in MLD ranged from -0.6 to -6.1 HU and were significant different for all kernels. The EV showed absolute differences between -0.05 and -0.4 L and was significantly different for all kernels. The EI showed absolute differences between -0.8 and -5.1 and was significantly different for all kernels. Conclusion: The use of kernels with BHC led to a significant decrease in MLD and EI. The absolute differences between different kernels without BHC were small but they were larger than the known interscan variation in patients. Thus, for follow-up examinations the same reconstruction algorithm has to be used and use of BHC has to be avoided

  9. Implementation of a cone-beam reconstruction algorithm for the single-circle source orbit with embedded misalignment correction using homogeneous coordinates

    International Nuclear Information System (INIS)

    Karolczak, Marek; Schaller, Stefan; Engelke, Klaus; Lutz, Andreas; Taubenreuther, Ulrike; Wiesent, Karl; Kalender, Willi

    2001-01-01

    We present an efficient implementation of an approximate cone-beam image reconstruction algorithm for application in tomography, which accounts for scanner mechanical misalignment. The implementation is based on the algorithm proposed by Feldkamp et al. [J. Opt. Soc. Am. A 6, 612-619 (1984)] and is directed at circular scan paths. The algorithm has been developed for the purpose of reconstructing volume data from projections acquired in an experimental x-ray microtomography (μCT) scanner [Engelke et al., Der Radiologe 39, 203-212 (1999)]. To mathematically model misalignment we use matrix notation with homogeneous coordinates to describe the scanner geometry, its misalignment, and the acquisition process. For convenience analysis is carried out for x-ray CT scanners, but it is applicable to any tomographic modality, where two-dimensional projection acquisition in cone beam geometry takes place, e.g., single photon emission computerized tomography. We derive an algorithm assuming misalignment errors to be small enough to weight and filter original projections and to embed compensation for misalignment in the backprojection. We verify the algorithm on simulations of virtual phantoms and scans of a physical multidisk (Defrise) phantom

  10. Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.

    Science.gov (United States)

    Altazi, Baderaldeen A; Zhang, Geoffrey G; Fernandez, Daniel C; Montejo, Michael E; Hunt, Dylan; Werner, Joan; Biagioli, Matthew C; Moros, Eduardo G

    2017-11-01

    Site-specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18 Flourine-fluorodeoxyglucose ( 18 F-FDG) PET images for three parameters: manual versus computer-aided segmentation methods, gray-level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board-certified radiation oncologists manually segmented the metabolic tumor volume (MTV 1 and MTV 2 ) for each patient. For comparison, we used a graphical-based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down-sampled the tumor volumes into three gray-levels: 32, 64, and 128 from the original gray-level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D-reconstruction algorithms: maximum likelihood-ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning-ML-OSEM (FOREIR), FORE-filtered back projection (FOREFBP), and 3D-Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray-levels of down-sampled volumes, and PET reconstruction algorithms. The features were extracted using gray-level co-occurrence matrices (GLCM), gray-level size zone matrices (GLSZM), gray-level run-length matrices (GLRLM), neighborhood gray-tone difference matrices (NGTDM), shape-based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV

  11. Dendroclimatic transfer functions revisited: Little Ice Age and Medieval Warm Period summer temperatures reconstructed using artificial neural networks and linear algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Helama, S.; Holopainen, J.; Eronen, M. [Department of Geology, University of Helsinki, (Finland); Makarenko, N.G. [Russian Academy of Sciences, St. Petersburg (Russian Federation). Pulkovo Astronomical Observatory; Karimova, L.M.; Kruglun, O.A. [Institute of Mathematics, Almaty (Kazakhstan); Timonen, M. [Finnish Forest Research Institute, Rovaniemi Research Unit (Finland); Merilaeinen, J. [SAIMA Unit of the Savonlinna Department of Teacher Education, University of Joensuu (Finland)

    2009-07-01

    Tree-rings tell of past climates. To do so, tree-ring chronologies comprising numerous climate-sensitive living-tree and subfossil time-series need to be 'transferred' into palaeoclimate estimates using transfer functions. The purpose of this study is to compare different types of transfer functions, especially linear and nonlinear algorithms. Accordingly, multiple linear regression (MLR), linear scaling (LSC) and artificial neural networks (ANN, nonlinear algorithm) were compared. Transfer functions were built using a regional tree-ring chronology and instrumental temperature observations from Lapland (northern Finland and Sweden). In addition, conventional MLR was compared with a hybrid model whereby climate was reconstructed separately for short- and long-period timescales prior to combining the bands of timescales into a single hybrid model. The fidelity of the different reconstructions was validated against instrumental climate data. The reconstructions by MLR and ANN showed reliable reconstruction capabilities over the instrumental period (AD 1802-1998). LCS failed to reach reasonable verification statistics and did not qualify as a reliable reconstruction: this was due mainly to exaggeration of the low-frequency climatic variance. Over this instrumental period, the reconstructed low-frequency amplitudes of climate variability were rather similar by MLR and ANN. Notably greater differences between the models were found over the actual reconstruction period (AD 802-1801). A marked temperature decline, as reconstructed by MLR, from the Medieval Warm Period (AD 931-1180) to the Little Ice Age (AD 1601-1850), was evident in all the models. This decline was approx. 0.5 C as reconstructed by MLR. Different ANN based palaeotemperatures showed simultaneous cooling of 0.2 to 0.5 C, depending on algorithm. The hybrid MLR did not seem to provide further benefit above conventional MLR in our sample. The robustness of the conventional MLR over the calibration

  12. Improved image quality with simultaneously reduced radiation exposure: Knowledge-based iterative model reconstruction algorithms for coronary CT angiography in a clinical setting.

    Science.gov (United States)

    André, Florian; Fortner, Philipp; Vembar, Mani; Mueller, Dirk; Stiller, Wolfram; Buss, Sebastian J; Kauczor, Hans-Ulrich; Katus, Hugo A; Korosoglou, Grigorios

    The aim of this study was to assess the potential for radiation dose reduction using knowledge-based iterative model reconstruction (K-IMR) algorithms in combination with ultra-low dose body mass index (BMI)-adapted protocols in coronary CT angiography (coronary CTA). Forty patients undergoing clinically indicated coronary CTA were randomly assigned to two groups with BMI-adapted (I: quality was significantly better in the ULD group using K-IMR CR 1 compared to FBP, iD 2 and iD 5 in the LD group, resulting in fewer non-diagnostic coronary segments (2.4% vs. 11.6%, 9.2% and 6.1%; p quality compared to LD protocols with FBP or hybrid iterative algorithms. Therefore, K-IMR allows for coronary CTA examinations with high diagnostic value and very low radiation exposure in clinical routine. Copyright © 2017 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

  13. Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

    Science.gov (United States)

    O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin

    2017-12-06

    Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

  14. Radiation dose reduction in medical x-ray CT via Fourier-based iterative reconstruction.

    Science.gov (United States)

    Fahimian, Benjamin P; Zhao, Yunzhe; Huang, Zhifeng; Fung, Russell; Mao, Yu; Zhu, Chun; Khatonabadi, Maryam; DeMarco, John J; Osher, Stanley J; McNitt-Gray, Michael F; Miao, Jianwei

    2013-03-01

    A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry. EST is a Fourier based iterative algorithm, which iterates back and forth between real and Fourier space utilizing the algebraically exact pseudopolar fast Fourier transform (PPFFT). In each iteration, physical constraints and mathematical regularization are applied in real space, while the measured data are enforced in Fourier space. The algorithm is automatically terminated when a proposed termination criterion is met. Experimentally, fan-beam projections were acquired by the Siemens z-flying focal spot technology, and subsequently interleaved and rebinned to a pseudopolar grid. Image quality phantoms were scanned at systematically varied mAs settings, reconstructed by EST and conventional reconstruction methods such as filtered back projection (FBP), and quantified using metrics including resolution, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs). Pediatric data sets were reconstructed at their original acquisition settings and additionally simulated to lower dose settings for comparison and evaluation of the potential for radiation dose reduction. Numerical experiments were conducted to quantify EST and other iterative methods in terms of image quality and computation time. The extension of EST to helical cone-beam CT was implemented by using the advanced single-slice rebinning (ASSR) method. Based on the phantom and pediatric patient fan-beam CT data, it is demonstrated that EST reconstructions with the lowest scanner flux setting of 39 m

  15. Radiation dose reduction in medical x-ray CT via Fourier-based iterative reconstruction

    International Nuclear Information System (INIS)

    Fahimian, Benjamin P.; Zhao Yunzhe; Huang Zhifeng; Fung, Russell; Zhu Chun; Miao Jianwei; Mao Yu; Khatonabadi, Maryam; DeMarco, John J.; McNitt-Gray, Michael F.; Osher, Stanley J.

    2013-01-01

    Purpose: A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry. Methods: EST is a Fourier based iterative algorithm, which iterates back and forth between real and Fourier space utilizing the algebraically exact pseudopolar fast Fourier transform (PPFFT). In each iteration, physical constraints and mathematical regularization are applied in real space, while the measured data are enforced in Fourier space. The algorithm is automatically terminated when a proposed termination criterion is met. Experimentally, fan-beam projections were acquired by the Siemens z-flying focal spot technology, and subsequently interleaved and rebinned to a pseudopolar grid. Image quality phantoms were scanned at systematically varied mAs settings, reconstructed by EST and conventional reconstruction methods such as filtered back projection (FBP), and quantified using metrics including resolution, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs). Pediatric data sets were reconstructed at their original acquisition settings and additionally simulated to lower dose settings for comparison and evaluation of the potential for radiation dose reduction. Numerical experiments were conducted to quantify EST and other iterative methods in terms of image quality and computation time. The extension of EST to helical cone-beam CT was implemented by using the advanced single-slice rebinning (ASSR) method. Results: Based on the phantom and pediatric patient fan-beam CT data, it is demonstrated that EST reconstructions with the lowest

  16. Compositional-prior-guided image reconstruction algorithm for multi-modality imaging

    Science.gov (United States)

    Fang, Qianqian; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

    2010-01-01

    The development of effective multi-modality imaging methods typically requires an efficient information fusion model, particularly when combining structural images with a complementary imaging modality that provides functional information. We propose a composition-based image segmentation method for X-ray digital breast tomosynthesis (DBT) and a structural-prior-guided image reconstruction for a combined DBT and diffuse optical tomography (DOT) breast imaging system. Using the 3D DBT images from 31 clinically measured healthy breasts, we create an empirical relationship between the X-ray intensities for adipose and fibroglandular tissue. We use this relationship to then segment another 58 healthy breast DBT images from 29 subjects into compositional maps of different tissue types. For each breast, we build a weighted-graph in the compositional space and construct a regularization matrix to incorporate the structural priors into a finite-element-based DOT image reconstruction. Use of the compositional priors enables us to fuse tissue anatomy into optical images with less restriction than when using a binary segmentation. This allows us to recover the image contrast captured by DOT but not by DBT. We show that it is possible to fine-tune the strength of the structural priors by changing a single regularization parameter. By estimating the optical properties for adipose and fibroglandular tissue using the proposed algorithm, we found the results are comparable or superior to those estimated with expert-segmentations, but does not involve the time-consuming manual selection of regions-of-interest. PMID:21258460

  17. Two-dimensional Tissue Image Reconstruction Based on Magnetic Field Data

    Directory of Open Access Journals (Sweden)

    J. Dedkova

    2012-09-01

    Full Text Available This paper introduces new possibilities within two-dimensional reconstruction of internal conductivity distribution. In addition to the electric field inside the given object, the injected current causes a magnetic field which can be measured either outside the object by means of a Hall probe or inside the object through magnetic resonance imaging. The Magnetic Resonance method, together with Electrical impedance tomography (MREIT, is well known as a bio-imaging modality providing cross-sectional conductivity images with a good spatial resolution from the measurements of internal magnetic flux density produced by externally injected currents. A new algorithm for the conductivity reconstruction, which utilizes the internal current information with respect to corresponding boundary conditions and the external magnetic field, was developed. A series of computer simulations has been conducted to assess the performance of the proposed algorithm within the process of estimating electrical conductivity changes in the lungs, heart, and brain tissues captured in two-dimensional piecewise homogeneous chest and head models. The reconstructed conductivity distribution using the proposed method is compared with that using a conventional method based on Electrical Impedance Tomography (EIT. The acquired experience is discussed and the direction of further research is proposed.

  18. Development of acoustic model-based iterative reconstruction technique for thick-concrete imaging

    Science.gov (United States)

    Almansouri, Hani; Clayton, Dwight; Kisner, Roger; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

    2016-02-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.1

  19. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL

    2016-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  20. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL

    2015-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well s health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  1. The reconstruction algorithm used for ["6"8Ga]PSMA-HBED-CC PET/CT reconstruction significantly influences the number of detected lymph node metastases and coeliac ganglia

    International Nuclear Information System (INIS)

    Krohn, Thomas; Birmes, Anita; Winz, Oliver H.; Drude, Natascha I.; Mottaghy, Felix M.; Behrendt, Florian F.; Verburg, Frederik A.

    2017-01-01

    To investigate whether the numbers of lymph node metastases and coeliac ganglia delineated on ["6"8Ga]PSMA-HBED-CC PET/CT scans differ among datasets generated using different reconstruction algorithms. Data were constructed using the BLOB-OS-TF, BLOB-OS and 3D-RAMLA algorithms. All reconstructions were assessed by two nuclear medicine physicians for the number of pelvic/paraaortal lymph node metastases as well the number of coeliac ganglia. Standardized uptake values (SUV) were also calculated in different regions. At least one ["6"8Ga]PSMA-HBED-CC PET/CT-positive pelvic or paraaortal lymph node metastasis was found in 49 and 35 patients using the BLOB-OS-TF algorithm, in 42 and 33 patients using the BLOB-OS algorithm, and in 41 and 31 patients using the 3D-RAMLA algorithm, respectively, and a positive ganglion was found in 92, 59 and 24 of 100 patients using the three algorithms, respectively. Quantitatively, the SUVmean and SUVmax were significantly higher with the BLOB-OS algorithm than with either the BLOB-OS-TF or the 3D-RAMLA algorithm in all measured regions (p < 0.001 for all comparisons). The differences between the SUVs with the BLOB-OS-TF- and 3D-RAMLA algorithms were not significant in the aorta (SUVmean, p = 0.93; SUVmax, p = 0.97) but were significant in all other regions (p < 0.001 in all cases). The SUVmean ganglion/gluteus ratio was significantly higher with the BLOB-OS-TF algorithm than with either the BLOB-OS or the 3D-RAMLA algorithm and was significantly higher with the BLOB-OS than with the 3D-RAMLA algorithm (p < 0.001 in all cases). The results of ["6"8Ga]PSMA-HBED-CC PET/CT are affected by the reconstruction algorithm used. The highest number of lesions and physiological structures will be visualized using a modern algorithm employing time-of-flight information. (orig.)

  2. The reconstruction algorithm used for [{sup 68}Ga]PSMA-HBED-CC PET/CT reconstruction significantly influences the number of detected lymph node metastases and coeliac ganglia

    Energy Technology Data Exchange (ETDEWEB)

    Krohn, Thomas [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Ulm University, Department of Nuclear Medicine, Ulm (Germany); Birmes, Anita; Winz, Oliver H.; Drude, Natascha I. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Mottaghy, Felix M. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Maastricht UMC+, Department of Nuclear Medicine, Maastricht (Netherlands); Behrendt, Florian F. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Radiology Institute ' ' Aachen Land' ' , Wuerselen (Germany); Verburg, Frederik A. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); University Hospital Giessen and Marburg, Department of Nuclear Medicine, Marburg (Germany)

    2017-04-15

    To investigate whether the numbers of lymph node metastases and coeliac ganglia delineated on [{sup 68}Ga]PSMA-HBED-CC PET/CT scans differ among datasets generated using different reconstruction algorithms. Data were constructed using the BLOB-OS-TF, BLOB-OS and 3D-RAMLA algorithms. All reconstructions were assessed by two nuclear medicine physicians for the number of pelvic/paraaortal lymph node metastases as well the number of coeliac ganglia. Standardized uptake values (SUV) were also calculated in different regions. At least one [{sup 68}Ga]PSMA-HBED-CC PET/CT-positive pelvic or paraaortal lymph node metastasis was found in 49 and 35 patients using the BLOB-OS-TF algorithm, in 42 and 33 patients using the BLOB-OS algorithm, and in 41 and 31 patients using the 3D-RAMLA algorithm, respectively, and a positive ganglion was found in 92, 59 and 24 of 100 patients using the three algorithms, respectively. Quantitatively, the SUVmean and SUVmax were significantly higher with the BLOB-OS algorithm than with either the BLOB-OS-TF or the 3D-RAMLA algorithm in all measured regions (p < 0.001 for all comparisons). The differences between the SUVs with the BLOB-OS-TF- and 3D-RAMLA algorithms were not significant in the aorta (SUVmean, p = 0.93; SUVmax, p = 0.97) but were significant in all other regions (p < 0.001 in all cases). The SUVmean ganglion/gluteus ratio was significantly higher with the BLOB-OS-TF algorithm than with either the BLOB-OS or the 3D-RAMLA algorithm and was significantly higher with the BLOB-OS than with the 3D-RAMLA algorithm (p < 0.001 in all cases). The results of [{sup 68}Ga]PSMA-HBED-CC PET/CT are affected by the reconstruction algorithm used. The highest number of lesions and physiological structures will be visualized using a modern algorithm employing time-of-flight information. (orig.)

  3. Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction

    Science.gov (United States)

    Fang, Shiting; Wang, Huafeng; Liu, Yueliang; Zhang, Minghui; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

    2017-10-01

    Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al’s algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al’s method, thus indicating the effectivity and competitiveness of the proposed algorithm.

  4. Fast volume reconstruction in positron emission tomography: Implementation of four algorithms on a high-performance scalable parallel platform

    International Nuclear Information System (INIS)

    Egger, M.L.; Scheurer, A.H.; Joseph, C.

    1996-01-01

    The issue of long reconstruction times in PET has been addressed from several points of view, resulting in an affordable dedicated system capable of handling routine 3D reconstruction in a few minutes per frame: on the hardware side using fast processors and a parallel architecture, and on the software side, using efficient implementations of computationally less intensive algorithms. Execution times obtained for the PRT-1 data set on a parallel system of five hybrid nodes, each combining an Alpha processor for computation and a transputer for communication, are the following (256 sinograms of 96 views by 128 radial samples): Ramp algorithm 56 s, Favor 81 s and reprojection algorithm of Kinahan and Rogers 187 s. The implementation of fast rebinning algorithms has shown our hardware platform to become communications-limited; they execute faster on a conventional single-processor Alpha workstation: single-slice rebinning 7 s, Fourier rebinning 22 s, 2D filtered backprojection 5 s. The scalability of the system has been demonstrated, and a saturation effect at network sizes above ten nodes has become visible; new T9000-based products lifting most of the constraints on network topology and link throughput are expected to result in improved parallel efficiency and scalability properties

  5. Reconstruction of convex bodies from surface tensors

    DEFF Research Database (Denmark)

    Kousholt, Astrid; Kiderlen, Markus

    . The output of the reconstruction algorithm is a polytope P, where the surface tensors of P and K are identical up to rank s. We establish a stability result based on a generalization of Wirtinger’s inequality that shows that for large s, two convex bodies are close in shape when they have identical surface...... that are translates of each other. An algorithm for reconstructing an unknown convex body in R 2 from its surface tensors up to a certain rank is presented. Using the reconstruction algorithm, the shape of an unknown convex body can be approximated when only a finite number s of surface tensors are available...... tensors up to rank s. This is used to establish consistency of the developed reconstruction algorithm....

  6. A Support-Based Reconstruction for SENSE MRI

    Directory of Open Access Journals (Sweden)

    Bradley S. Peterson

    2013-03-01

    Full Text Available A novel, rapid algorithm to speed up and improve the reconstruction of sensitivity encoding (SENSE MRI was proposed in this paper. The essence of the algorithm was that it iteratively solved the model of simple SENSE on a pixel-by-pixel basis in the region of support (ROS. The ROS was obtained from scout images of eight channels by morphological operations such as opening and filling. All the pixels in the FOV were paired and classified into four types, according to their spatial locations with respect to the ROS, and each with corresponding procedures of solving the inverse problem for image reconstruction. The sensitivity maps, used for the image reconstruction and covering only the ROS, were obtained by a polynomial regression model without extrapolation to keep the estimation errors small. The experiments demonstrate that the proposed method improves the reconstruction of SENSE in terms of speed and accuracy. The mean square errors (MSE of our reconstruction is reduced by 16.05% for a 2D brain MR image and the mean MSE over the whole slices in a 3D brain MRI is reduced by 30.44% compared to those of the traditional methods. The computation time is only 25%, 45%, and 70% of the traditional method for images with numbers of pixels in the orders of 103, 104, and 105–107, respectively.

  7. The effect of 18F-FDG-PET image reconstruction algorithms on the expression of characteristic metabolic brain network in Parkinson's disease.

    Science.gov (United States)

    Tomše, Petra; Jensterle, Luka; Rep, Sebastijan; Grmek, Marko; Zaletel, Katja; Eidelberg, David; Dhawan, Vijay; Ma, Yilong; Trošt, Maja

    2017-09-01

    To evaluate the reproducibility of the expression of Parkinson's Disease Related Pattern (PDRP) across multiple sets of 18F-FDG-PET brain images reconstructed with different reconstruction algorithms. 18F-FDG-PET brain imaging was performed in two independent cohorts of Parkinson's disease (PD) patients and normal controls (NC). Slovenian cohort (20 PD patients, 20 NC) was scanned with Siemens Biograph mCT camera and reconstructed using FBP, FBP+TOF, OSEM, OSEM+TOF, OSEM+PSF and OSEM+PSF+TOF. American Cohort (20 PD patients, 7 NC) was scanned with GE Advance camera and reconstructed using 3DRP, FORE-FBP and FORE-Iterative. Expressions of two previously-validated PDRP patterns (PDRP-Slovenia and PDRP-USA) were calculated. We compared the ability of PDRP to discriminate PD patients from NC, differences and correlation between the corresponding subject scores and ROC analysis results across the different reconstruction algorithms. The expression of PDRP-Slovenia and PDRP-USA networks was significantly elevated in PD patients compared to NC (palgorithms. PDRP expression strongly correlated between all studied algorithms and the reference algorithm (r⩾0.993, palgorithms varied within 0.73 and 0.08 of the reference value for PDRP-Slovenia and PDRP-USA, respectively. ROC analysis confirmed high similarity in sensitivity, specificity and AUC among all studied reconstruction algorithms. These results show that the expression of PDRP is reproducible across a variety of reconstruction algorithms of 18F-FDG-PET brain images. PDRP is capable of providing a robust metabolic biomarker of PD for multicenter 18F-FDG-PET images acquired in the context of differential diagnosis or clinical trials. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  8. Algorithmic aspects for the reconstruction of spatio-spectral data cubes in the perspective of the SKA

    Science.gov (United States)

    Mary, D.; Ferrari, A.; Ferrari, C.; Deguignet, J.; Vannier, M.

    2016-12-01

    With millions of receivers leading to TerraByte data cubes, the story of the giant SKA telescope is also that of collaborative efforts from radioastronomy, signal processing, optimization and computer sciences. Reconstructing SKA cubes poses two challenges. First, the majority of existing algorithms work in 2D and cannot be directly translated into 3D. Second, the reconstruction implies solving an inverse problem and it is not clear what ultimate limit we can expect on the error of this solution. This study addresses (of course partially) both challenges. We consider an extremely simple data acquisition model, and we focus on strategies making it possible to implement 3D reconstruction algorithms that use state-of-the-art image/spectral regularization. The proposed approach has two main features: (i) reduced memory storage with respect to a previous approach; (ii) efficient parallelization and ventilation of the computational load over the spectral bands. This work will allow to implement and compare various 3D reconstruction approaches in a large scale framework.

  9. Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Koc, Gonca; Courtier, Jesse L.; Phelps, Andrew; Marcovici, Peter A.; MacKenzie, John D. [UCSF Benioff Children' s Hospital, Department of Radiology and Biomedical Imaging, San Francisco, CA (United States)

    2014-07-15

    Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model-based

  10. Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

    International Nuclear Information System (INIS)

    Koc, Gonca; Courtier, Jesse L.; Phelps, Andrew; Marcovici, Peter A.; MacKenzie, John D.

    2014-01-01

    Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model-based

  11. l1- and l2-Norm Joint Regularization Based Sparse Signal Reconstruction Scheme

    Directory of Open Access Journals (Sweden)

    Chanzi Liu

    2016-01-01

    Full Text Available Many problems in signal processing and statistical inference involve finding sparse solution to some underdetermined linear system of equations. This is also the application condition of compressive sensing (CS which can find the sparse solution from the measurements far less than the original signal. In this paper, we propose l1- and l2-norm joint regularization based reconstruction framework to approach the original l0-norm based sparseness-inducing constrained sparse signal reconstruction problem. Firstly, it is shown that, by employing the simple conjugate gradient algorithm, the new formulation provides an effective framework to deduce the solution as the original sparse signal reconstruction problem with l0-norm regularization item. Secondly, the upper reconstruction error limit is presented for the proposed sparse signal reconstruction framework, and it is unveiled that a smaller reconstruction error than l1-norm relaxation approaches can be realized by using the proposed scheme in most cases. Finally, simulation results are presented to validate the proposed sparse signal reconstruction approach.

  12. Three-dimension reconstruction based on spatial light modulator

    International Nuclear Information System (INIS)

    Deng Xuejiao; Zhang Nanyang; Zeng Yanan; Yin Shiliang; Wang Weiyu

    2011-01-01

    Three-dimension reconstruction, known as an important research direction of computer graphics, is widely used in the related field such as industrial design and manufacture, construction, aerospace, biology and so on. Via such technology we can obtain three-dimension digital point cloud from a two-dimension image, and then simulate the three-dimensional structure of the physical object for further study. At present, the obtaining of three-dimension digital point cloud data is mainly based on the adaptive optics system with Shack-Hartmann sensor and phase-shifting digital holography. Referring to surface fitting, there are also many available methods such as iterated discrete fourier transform, convolution and image interpolation, linear phase retrieval. The main problems we came across in three-dimension reconstruction are the extraction of feature points and arithmetic of curve fitting. To solve such problems, we can, first of all, calculate the relevant surface normal vector information of each pixel in the light source coordinate system, then these vectors are to be converted to the coordinates of image through the coordinate conversion, so the expectant 3D point cloud get arise. Secondly, after the following procedures of de-noising, repairing, the feature points can later be selected and fitted to get the fitting function of the surface topography by means of Zernike polynomial, so as to reconstruct the determinand's three-dimensional topography. In this paper, a new kind of three-dimension reconstruction algorithm is proposed, with the assistance of which, the topography can be estimated from its grayscale at different sample points. Moreover, the previous stimulation and the experimental results prove that the new algorithm has a strong capability to fit, especially for large-scale objects .

  13. Three-dimension reconstruction based on spatial light modulator

    Science.gov (United States)

    Deng, Xuejiao; Zhang, Nanyang; Zeng, Yanan; Yin, Shiliang; Wang, Weiyu

    2011-02-01

    Three-dimension reconstruction, known as an important research direction of computer graphics, is widely used in the related field such as industrial design and manufacture, construction, aerospace, biology and so on. Via such technology we can obtain three-dimension digital point cloud from a two-dimension image, and then simulate the three-dimensional structure of the physical object for further study. At present, the obtaining of three-dimension digital point cloud data is mainly based on the adaptive optics system with Shack-Hartmann sensor and phase-shifting digital holography. Referring to surface fitting, there are also many available methods such as iterated discrete fourier transform, convolution and image interpolation, linear phase retrieval. The main problems we came across in three-dimension reconstruction are the extraction of feature points and arithmetic of curve fitting. To solve such problems, we can, first of all, calculate the relevant surface normal vector information of each pixel in the light source coordinate system, then these vectors are to be converted to the coordinates of image through the coordinate conversion, so the expectant 3D point cloud get arise. Secondly, after the following procedures of de-noising, repairing, the feature points can later be selected and fitted to get the fitting function of the surface topography by means of Zernike polynomial, so as to reconstruct the determinand's three-dimensional topography. In this paper, a new kind of three-dimension reconstruction algorithm is proposed, with the assistance of which, the topography can be estimated from its grayscale at different sample points. Moreover, the previous stimulation and the experimental results prove that the new algorithm has a strong capability to fit, especially for large-scale objects .

  14. Image reconstruction from limited angle Compton camera data

    International Nuclear Information System (INIS)

    Tomitani, T.; Hirasawa, M.

    2002-01-01

    The Compton camera is used for imaging the distributions of γ ray direction in a γ ray telescope for astrophysics and for imaging radioisotope distributions in nuclear medicine without the need for collimators. The integration of γ rays on a cone is measured with the camera, so that some sort of inversion method is needed. Parra found an analytical inversion algorithm based on spherical harmonics expansion of projection data. His algorithm is applicable to the full set of projection data. In this paper, six possible reconstruction algorithms that allow image reconstruction from projections with a finite range of scattering angles are investigated. Four algorithms have instability problems and two others are practical. However, the variance of the reconstructed image diverges in these two cases, so that window functions are introduced with which the variance becomes finite at a cost of spatial resolution. These two algorithms are compared in terms of variance. The algorithm based on the inversion of the summed back-projection is superior to the algorithm based on the inversion of the summed projection. (author)

  15. Development of imaging and reconstructions algorithms on parallel processing architectures for applications in non-destructive testing

    International Nuclear Information System (INIS)

    Pedron, Antoine

    2013-01-01

    This thesis work is placed between the scientific domain of ultrasound non-destructive testing and algorithm-architecture adequation. Ultrasound non-destructive testing includes a group of analysis techniques used in science and industry to evaluate the properties of a material, component, or system without causing damage. In order to characterise possible defects, determining their position, size and shape, imaging and reconstruction tools have been developed at CEA-LIST, within the CIVA software platform. Evolution of acquisition sensors implies a continuous growth of datasets and consequently more and more computing power is needed to maintain interactive reconstructions. General purpose processors (GPP) evolving towards parallelism and emerging architectures such as GPU allow large acceleration possibilities than can be applied to these algorithms. The main goal of the thesis is to evaluate the acceleration than can be obtained for two reconstruction algorithms on these architectures. These two algorithms differ in their parallelization scheme. The first one can be properly parallelized on GPP whereas on GPU, an intensive use of atomic instructions is required. Within the second algorithm, parallelism is easier to express, but loop ordering on GPP, as well as thread scheduling and a good use of shared memory on GPU are necessary in order to obtain efficient results. Different API or libraries, such as OpenMP, CUDA and OpenCL are evaluated through chosen benchmarks. An integration of both algorithms in the CIVA software platform is proposed and different issues related to code maintenance and durability are discussed. (author) [fr

  16. Image super-resolution reconstruction based on regularization technique and guided filter

    Science.gov (United States)

    Huang, De-tian; Huang, Wei-qin; Gu, Pei-ting; Liu, Pei-zhong; Luo, Yan-min

    2017-06-01

    In order to improve the accuracy of sparse representation coefficients and the quality of reconstructed images, an improved image super-resolution algorithm based on sparse representation is presented. In the sparse coding stage, the autoregressive (AR) regularization and the non-local (NL) similarity regularization are introduced to improve the sparse coding objective function. A group of AR models which describe the image local structures are pre-learned from the training samples, and one or several suitable AR models can be adaptively selected for each image patch to regularize the solution space. Then, the image non-local redundancy is obtained by the NL similarity regularization to preserve edges. In the process of computing the sparse representation coefficients, the feature-sign search algorithm is utilized instead of the conventional orthogonal matching pursuit algorithm to improve the accuracy of the sparse coefficients. To restore image details further, a global error compensation model based on weighted guided filter is proposed to realize error compensation for the reconstructed images. Experimental results demonstrate that compared with Bicubic, L1SR, SISR, GR, ANR, NE + LS, NE + NNLS, NE + LLE and A + (16 atoms) methods, the proposed approach has remarkable improvement in peak signal-to-noise ratio, structural similarity and subjective visual perception.

  17. Handling data redundancy in helical cone beam reconstruction with a cone-angle-based window function and its asymptotic approximation

    International Nuclear Information System (INIS)

    Tang Xiangyang; Hsieh Jiang

    2007-01-01

    A cone-angle-based window function is defined in this manuscript for image reconstruction using helical cone beam filtered backprojection (CB-FBP) algorithms. Rather than defining the window boundaries in a two-dimensional detector acquiring projection data for computed tomographic imaging, the cone-angle-based window function deals with data redundancy by selecting rays with the smallest cone angle relative to the reconstruction plane. To be computationally efficient, an asymptotic approximation of the cone-angle-based window function is also given and analyzed in this paper. The benefit of using such an asymptotic approximation also includes the avoidance of functional discontinuities that cause artifacts in reconstructed tomographic images. The cone-angle-based window function and its asymptotic approximation provide a way, equivalent to the Tam-Danielsson-window, for helical CB-FBP reconstruction algorithms to deal with data redundancy, regardless of where the helical pitch is constant or dynamically variable during a scan. By taking the cone-parallel geometry as an example, a computer simulation study is conducted to evaluate the proposed window function and its asymptotic approximation for helical CB-FBP reconstruction algorithm to handle data redundancy. The computer simulated Forbild head and thorax phantoms are utilized in the performance evaluation, showing that the proposed cone-angle-based window function and its asymptotic approximation can deal with data redundancy very well in cone beam image reconstruction from projection data acquired along helical source trajectories. Moreover, a numerical study carried out in this paper reveals that the proposed cone-angle-based window function is actually equivalent to the Tam-Danielsson-window, and rigorous mathematical proofs are being investigated

  18. Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study.

    Science.gov (United States)

    Kim, Hyungjin; Park, Chang Min; Song, Yong Sub; Lee, Sang Min; Goo, Jin Mo

    2014-05-01

    To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. CT scans were performed on a chest phantom containing various nodules (10 and 12mm; +100, -630 and -800HU) at 120kVp with tube current-time settings of 10, 20, 50, and 100mAs. Each CT was reconstructed using filtered back projection (FBP), iDose(4) and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p>0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose(4) at all radiation dose settings (pvolumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  19. A Novel Pairwise Comparison-Based Method to Determine Radiation Dose Reduction Potentials of Iterative Reconstruction Algorithms, Exemplified Through Circle of Willis Computed Tomography Angiography.

    Science.gov (United States)

    Ellmann, Stephan; Kammerer, Ferdinand; Brand, Michael; Allmendinger, Thomas; May, Matthias S; Uder, Michael; Lell, Michael M; Kramer, Manuel

    2016-05-01

    The aim of this study was to determine the dose reduction potential of iterative reconstruction (IR) algorithms in computed tomography angiography (CTA) of the circle of Willis using a novel method of evaluating the quality of radiation dose-reduced images. This study relied on ReconCT, a proprietary reconstruction software that allows simulating CT scans acquired with reduced radiation dose based on the raw data of true scans. To evaluate the performance of ReconCT in this regard, a phantom study was performed to compare the image noise of true and simulated scans within simulated vessels of a head phantom. That followed, 10 patients scheduled for CTA of the circle of Willis were scanned according to our institute's standard protocol (100 kV, 145 reference mAs). Subsequently, CTA images of these patients were reconstructed as either a full-dose weighted filtered back projection or with radiation dose reductions down to 10% of the full-dose level and Sinogram-Affirmed Iterative Reconstruction (SAFIRE) with either strength 3 or 5. Images were marked with arrows pointing on vessels of different sizes, and image pairs were presented to observers. Five readers assessed image quality with 2-alternative forced choice comparisons. In the phantom study, no significant differences were observed between the noise levels of simulated and true scans in filtered back projection, SAFIRE 3, and SAFIRE 5 reconstructions.The dose reduction potential for patient scans showed a strong dependence on IR strength as well as on the size of the vessel of interest. Thus, the potential radiation dose reductions ranged from 84.4% for the evaluation of great vessels reconstructed with SAFIRE 5 to 40.9% for the evaluation of small vessels reconstructed with SAFIRE 3. This study provides a novel image quality evaluation method based on 2-alternative forced choice comparisons. In CTA of the circle of Willis, higher IR strengths and greater vessel sizes allowed higher degrees of radiation dose

  20. Pinhole single-photon emission tomography reconstruction based on median root prior

    International Nuclear Information System (INIS)

    Sohlberg, Antti; Kuikka, Jyrki T.; Ruotsalainen, Ulla

    2003-01-01

    The maximum likelihood expectation maximisation (ML-EM) algorithm can be used to reduce reconstruction artefacts produced by filtered backprojection (FBP) methods in pinhole single-photon emission tomography (SPET). However, ML-EM suffers from noise propagation along iterations, which leads to quantitatively unpleasant reconstruction results. To avoid this increase in noise, the median root prior (MRP) algorithm for pinhole SPET was implemented. Projection data of a line source and Picker's thyroid phantom were collected using a single-head gamma camera with a pinhole collimator. MRP was added to existing pinhole ML-EM reconstruction algorithm and the phantom studies were reconstructed using MRP, ML-EM and FBP for comparison. Coefficients of variation, contrasts and full-widths at half-maximum were calculated and showed a clear reduction in noise without significant loss of resolution or decrease in contrast when MRP was applied. MRP also produced visually pleasing images even with high iteration numbers, free of the checkerboard-type noise patterns which are typical of ML-EM images. (orig.)

  1. A spectral image processing algorithm for evaluating the influence of the illuminants on the reconstructed reflectance

    Science.gov (United States)

    Toadere, Florin

    2017-12-01

    A spectral image processing algorithm that allows the illumination of the scene with different illuminants together with the reconstruction of the scene's reflectance is presented. Color checker spectral image and CIE A (warm light 2700 K), D65 (cold light 6500 K) and Cree TW Series LED T8 (4000 K) are employed for scene illumination. Illuminants used in the simulations have different spectra and, as a result of their illumination, the colors of the scene change. The influence of the illuminants on the reconstruction of the scene's reflectance is estimated. Demonstrative images and reflectance showing the operation of the algorithm are illustrated.

  2. Regional MLEM reconstruction strategy for PET-based treatment verification in ion beam radiotherapy

    International Nuclear Information System (INIS)

    Gianoli, Chiara; Riboldi, Marco; Fattori, Giovanni; Baselli, Giuseppe; Baroni, Guido; Bauer, Julia; Debus, Jürgen; Parodi, Katia; De Bernardi, Elisabetta

    2014-01-01

    In ion beam radiotherapy, PET-based treatment verification provides a consistency check of the delivered treatment with respect to a simulation based on the treatment planning. In this work the region-based MLEM reconstruction algorithm is proposed as a new evaluation strategy in PET-based treatment verification. The comparative evaluation is based on reconstructed PET images in selected regions, which are automatically identified on the expected PET images according to homogeneity in activity values. The strategy was tested on numerical and physical phantoms, simulating mismatches between the planned and measured β + activity distributions. The region-based MLEM reconstruction was demonstrated to be robust against noise and the sensitivity of the strategy results were comparable to three voxel units, corresponding to 6 mm in numerical phantoms. The robustness of the region-based MLEM evaluation outperformed the voxel-based strategies. The potential of the proposed strategy was also retrospectively assessed on patient data and further clinical validation is envisioned. (paper)

  3. Electron dose map inversion based on several algorithms

    International Nuclear Information System (INIS)

    Li Gui; Zheng Huaqing; Wu Yican; Fds Team

    2010-01-01

    The reconstruction to the electron dose map in radiation therapy was investigated by constructing the inversion model of electron dose map with different algorithms. The inversion model of electron dose map based on nonlinear programming was used, and this model was applied the penetration dose map to invert the total space one. The realization of this inversion model was by several inversion algorithms. The test results with seven samples show that except the NMinimize algorithm, which worked for just one sample, with great error,though,all the inversion algorithms could be realized to our inversion model rapidly and accurately. The Levenberg-Marquardt algorithm, having the greatest accuracy and speed, could be considered as the first choice in electron dose map inversion.Further tests show that more error would be created when the data close to the electron range was used (tail error). The tail error might be caused by the approximation of mean energy spectra, and this should be considered to improve the method. The time-saving and accurate algorithms could be used to achieve real-time dose map inversion. By selecting the best inversion algorithm, the clinical need in real-time dose verification can be satisfied. (authors)

  4. Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images

    International Nuclear Information System (INIS)

    Mumcuglu, E.U.; Leahy, R.; Zhou, Z.; Cherry, S.R.

    1994-01-01

    The authors describe conjugate gradient algorithms for reconstruction of transmission and emission PET images. The reconstructions are based on a Bayesian formulation, where the data are modeled as a collection of independent Poisson random variables and the image is modeled using a Markov random field. A conjugate gradient algorithm is used to compute a maximum a posteriori (MAP) estimate of the image by maximizing over the posterior density. To ensure nonnegativity of the solution, a penalty function is used to convert the problem to one of unconstrained optimization. Preconditioners are used to enhance convergence rates. These methods generally achieve effective convergence in 15--25 iterations. Reconstructions are presented of an 18 FDG whole body scan from data collected using a Siemens/CTI ECAT931 whole body system. These results indicate significant improvements in emission image quality using the Bayesian approach, in comparison to filtered backprojection, particularly when reprojections of the MAP transmission image are used in place of the standard attenuation correction factors

  5. MR fingerprinting reconstruction with Kalman filter.

    Science.gov (United States)

    Zhang, Xiaodi; Zhou, Zechen; Chen, Shiyang; Chen, Shuo; Li, Rui; Hu, Xiaoping

    2017-09-01

    Magnetic resonance fingerprinting (MR fingerprinting or MRF) is a newly introduced quantitative magnetic resonance imaging technique, which enables simultaneous multi-parameter mapping in a single acquisition with improved time efficiency. The current MRF reconstruction method is based on dictionary matching, which may be limited by the discrete and finite nature of the dictionary and the computational cost associated with dictionary construction, storage and matching. In this paper, we describe a reconstruction method based on Kalman filter for MRF, which avoids the use of dictionary to obtain continuous MR parameter measurements. With this Kalman filter framework, the Bloch equation of inversion-recovery balanced steady state free-precession (IR-bSSFP) MRF sequence was derived to predict signal evolution, and acquired signal was entered to update the prediction. The algorithm can gradually estimate the accurate MR parameters during the recursive calculation. Single pixel and numeric brain phantom simulation were implemented with Kalman filter and the results were compared with those from dictionary matching reconstruction algorithm to demonstrate the feasibility and assess the performance of Kalman filter algorithm. The results demonstrated that Kalman filter algorithm is applicable for MRF reconstruction, eliminating the need for a pre-define dictionary and obtaining continuous MR parameter in contrast to the dictionary matching algorithm. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Multirate-based fast parallel algorithms for 2-D DHT-based real-valued discrete Gabor transform.

    Science.gov (United States)

    Tao, Liang; Kwan, Hon Keung

    2012-07-01

    Novel algorithms for the multirate and fast parallel implementation of the 2-D discrete Hartley transform (DHT)-based real-valued discrete Gabor transform (RDGT) and its inverse transform are presented in this paper. A 2-D multirate-based analysis convolver bank is designed for the 2-D RDGT, and a 2-D multirate-based synthesis convolver bank is designed for the 2-D inverse RDGT. The parallel channels in each of the two convolver banks have a unified structure and can apply the 2-D fast DHT algorithm to speed up their computations. The computational complexity of each parallel channel is low and is independent of the Gabor oversampling rate. All the 2-D RDGT coefficients of an image are computed in parallel during the analysis process and can be reconstructed in parallel during the synthesis process. The computational complexity and time of the proposed parallel algorithms are analyzed and compared with those of the existing fastest algorithms for 2-D discrete Gabor transforms. The results indicate that the proposed algorithms are the fastest, which make them attractive for real-time image processing.

  7. Dynamic Error Analysis Method for Vibration Shape Reconstruction of Smart FBG Plate Structure

    Directory of Open Access Journals (Sweden)

    Hesheng Zhang

    2016-01-01

    Full Text Available Shape reconstruction of aerospace plate structure is an important issue for safe operation of aerospace vehicles. One way to achieve such reconstruction is by constructing smart fiber Bragg grating (FBG plate structure with discrete distributed FBG sensor arrays using reconstruction algorithms in which error analysis of reconstruction algorithm is a key link. Considering that traditional error analysis methods can only deal with static data, a new dynamic data error analysis method are proposed based on LMS algorithm for shape reconstruction of smart FBG plate structure. Firstly, smart FBG structure and orthogonal curved network based reconstruction method is introduced. Then, a dynamic error analysis model is proposed for dynamic reconstruction error analysis. Thirdly, the parameter identification is done for the proposed dynamic error analysis model based on least mean square (LMS algorithm. Finally, an experimental verification platform is constructed and experimental dynamic reconstruction analysis is done. Experimental results show that the dynamic characteristics of the reconstruction performance for plate structure can be obtained accurately based on the proposed dynamic error analysis method. The proposed method can also be used for other data acquisition systems and data processing systems as a general error analysis method.

  8. Contrast improvement of continuous wave diffuse optical tomography reconstruction by hybrid approach using least square and genetic algorithm

    Science.gov (United States)

    Patra, Rusha; Dutta, Pranab K.

    2015-07-01

    Reconstruction of the absorption coefficient of tissue with good contrast is of key importance in functional diffuse optical imaging. A hybrid approach using model-based iterative image reconstruction and a genetic algorithm is proposed to enhance the contrast of the reconstructed image. The proposed method yields an observed contrast of 98.4%, mean square error of 0.638×10-3, and object centroid error of (0.001 to 0.22) mm. Experimental validation of the proposed method has also been provided with tissue-like phantoms which shows a significant improvement in image quality and thus establishes the potential of the method for functional diffuse optical tomography reconstruction with continuous wave setup. A case study of finger joint imaging is illustrated as well to show the prospect of the proposed method in clinical diagnosis. The method can also be applied to the concentration measurement of a region of interest in a turbid medium.

  9. Comparison between different tomographic reconstruction algorithms in nuclear medicine imaging; Comparacion entre distintos algoritmos de reconstruccion tomografica en imagenes de medicina nuclear

    Energy Technology Data Exchange (ETDEWEB)

    Llacer Martos, S.; Herraiz Lablanca, M. D.; Puchal Ane, R.

    2011-07-01

    This paper compares the image quality obtained with each of the algorithms is evaluated and its running time, to optimize the choice of algorithm to use taking into account both the quality of the reconstructed image as the time spent on the reconstruction.

  10. A deblocking algorithm based on color psychology for display quality enhancement

    Science.gov (United States)

    Yeh, Chia-Hung; Tseng, Wen-Yu; Huang, Kai-Lin

    2012-12-01

    This article proposes a post-processing deblocking filter to reduce blocking effects. The proposed algorithm detects blocking effects by fusing the results of Sobel edge detector and wavelet-based edge detector. The filtering stage provides four filter modes to eliminate blocking effects at different color regions according to human color vision and color psychology analysis. Experimental results show that the proposed algorithm has better subjective and objective qualities for H.264/AVC reconstructed videos when compared to several existing methods.

  11. Three-dimension reconstruction based on spatial light modulator

    Energy Technology Data Exchange (ETDEWEB)

    Deng Xuejiao; Zhang Nanyang; Zeng Yanan; Yin Shiliang; Wang Weiyu, E-mail: daisydelring@yahoo.com.cn [Huazhong University of Science and Technology (China)

    2011-02-01

    Three-dimension reconstruction, known as an important research direction of computer graphics, is widely used in the related field such as industrial design and manufacture, construction, aerospace, biology and so on. Via such technology we can obtain three-dimension digital point cloud from a two-dimension image, and then simulate the three-dimensional structure of the physical object for further study. At present, the obtaining of three-dimension digital point cloud data is mainly based on the adaptive optics system with Shack-Hartmann sensor and phase-shifting digital holography. Referring to surface fitting, there are also many available methods such as iterated discrete fourier transform, convolution and image interpolation, linear phase retrieval. The main problems we came across in three-dimension reconstruction are the extraction of feature points and arithmetic of curve fitting. To solve such problems, we can, first of all, calculate the relevant surface normal vector information of each pixel in the light source coordinate system, then these vectors are to be converted to the coordinates of image through the coordinate conversion, so the expectant 3D point cloud get arise. Secondly, after the following procedures of de-noising, repairing, the feature points can later be selected and fitted to get the fitting function of the surface topography by means of Zernike polynomial, so as to reconstruct the determinand's three-dimensional topography. In this paper, a new kind of three-dimension reconstruction algorithm is proposed, with the assistance of which, the topography can be estimated from its grayscale at different sample points. Moreover, the previous stimulation and the experimental results prove that the new algorithm has a strong capability to fit, especially for large-scale objects .

  12. Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study

    International Nuclear Information System (INIS)

    Kim, Hyungjin; Park, Chang Min; Song, Yong Sub; Lee, Sang Min; Goo, Jin Mo

    2014-01-01

    Purpose: To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. Materials and methods: CT scans were performed on a chest phantom containing various nodules (10 and 12 mm; +100, −630 and −800 HU) at 120 kVp with tube current–time settings of 10, 20, 50, and 100 mAs. Each CT was reconstructed using filtered back projection (FBP), iDose 4 and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Results: Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p > 0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose 4 at all radiation dose settings (p < 0.05). Conclusion: Semi-automated nodule volumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility

  13. Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyungjin, E-mail: khj.snuh@gmail.com [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Park, Chang Min, E-mail: cmpark@radiol.snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Cancer Research Institute, Seoul National University, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Song, Yong Sub, E-mail: terasong@gmail.com [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Lee, Sang Min, E-mail: sangmin.lee.md@gmail.com [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Goo, Jin Mo, E-mail: jmgoo@plaza.snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Cancer Research Institute, Seoul National University, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of)

    2014-05-15

    Purpose: To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. Materials and methods: CT scans were performed on a chest phantom containing various nodules (10 and 12 mm; +100, −630 and −800 HU) at 120 kVp with tube current–time settings of 10, 20, 50, and 100 mAs. Each CT was reconstructed using filtered back projection (FBP), iDose{sup 4} and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Results: Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p > 0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose{sup 4} at all radiation dose settings (p < 0.05). Conclusion: Semi-automated nodule volumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility.

  14. MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

    International Nuclear Information System (INIS)

    Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J

    2015-01-01

    Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features

  15. MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

    Energy Technology Data Exchange (ETDEWEB)

    Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J [UT MD Anderson Cancer Center, Houston, TX (United States)

    2015-06-15

    Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.

  16. A deep learning-based reconstruction of cosmic ray-induced air showers

    Science.gov (United States)

    Erdmann, M.; Glombitza, J.; Walz, D.

    2018-01-01

    We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detector's responses to traversing shower particles are signal amplitudes as a function of time, which provide information on transverse and longitudinal shower properties. In order to take advantage of convolutional network techniques specialized in local pattern recognition, we convert all information to the image-like grid of the detectors. In this way, multiple features, such as arrival times of the first particles and optimized characterizations of time traces, are processed by the network. The reconstruction quality of the cosmic ray arrival direction turns out to be competitive with an analytic reconstruction algorithm. The reconstructed shower direction, energy and shower depth show the expected improvement in resolution for higher cosmic ray energy.

  17. 3D reconstruction based on compressed-sensing (CS)-based framework by using a dental panoramic detector.

    Science.gov (United States)

    Je, U K; Cho, H M; Hong, D K; Cho, H S; Park, Y O; Park, C K; Kim, K S; Lim, H W; Kim, G A; Park, S Y; Woo, T H; Cho, S I

    2016-01-01

    In this work, we propose a practical method that can combine the two functionalities of dental panoramic and cone-beam CT (CBCT) features in one by using a single panoramic detector. We implemented a CS-based reconstruction algorithm for the proposed method and performed a systematic simulation to demonstrate its viability for 3D dental X-ray imaging. We successfully reconstructed volumetric images of considerably high accuracy by using a panoramic detector having an active area of 198.4 mm × 6.4 mm and evaluated the reconstruction quality as a function of the pitch (p) and the angle step (Δθ). Our simulation results indicate that the CS-based reconstruction almost completely recovered the phantom structures, as in CBCT, for p≤2.0 and θ≤6°, indicating that it seems very promising for accurate image reconstruction even for large-pitch and few-view data. We expect the proposed method to be applicable to developing a cost-effective, volumetric dental X-ray imaging system. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  18. A trial to reduce cardiac motion artifact on HR-CT images of the lung with the use of subsecond scan and special cine reconstruction algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Sakai, Fumikazu; Tsuuchi, Yasuhiko; Suzuki, Keiko; Ueno, Keiko; Yamada, Takayuki; Okawa, Tomohiko [Tokyo Women`s Medical Coll. (Japan); Yun, Shen; Horiuchi, Tetsuya; Kimura, Fumiko

    1998-05-01

    We describe our trial to reduce cardiac motion artifacts on HR-CT images caused by cardiac pulsation by combining use of subsecond CT (scan time 0.8 s) and a special cine reconstruction algorithm (cine reconstruction algorithm with 180-degree helical interpolation). Eleven to 51 HR-CT images were reconstructed with the special cine reconstruction algorithm at the pitch of 0.1 (0.08 s) from the data obtained by two to six contigious rotation scans at the same level. Images with the fewest cardiac motion artifacts were selected for evaluation. These images were compared with those reconstructed with a conventional cine reconstruction algorithm and step-by-step scan. In spite of its increased radiation exposure, technical complexity and slight degradation of spatial resolution, our method was useful in reducing cardiac motion artifacts on HR-CT images in regions adjacent to the heart. (author)

  19. Ray tracing reconstruction investigation for C-arm tomosynthesis

    Science.gov (United States)

    Malalla, Nuhad A. Y.; Chen, Ying

    2016-04-01

    C-arm tomosynthesis is a three dimensional imaging technique. Both x-ray source and the detector are mounted on a C-arm wheeled structure to provide wide variety of movement around the object. In this paper, C-arm tomosynthesis was introduced to provide three dimensional information over a limited view angle (less than 180o) to reduce radiation exposure and examination time. Reconstruction algorithms based on ray tracing method such as ray tracing back projection (BP), simultaneous algebraic reconstruction technique (SART) and maximum likelihood expectation maximization (MLEM) were developed for C-arm tomosynthesis. C-arm tomosynthesis projection images of simulated spherical object were simulated with a virtual geometric configuration with a total view angle of 40 degrees. This study demonstrated the sharpness of in-plane reconstructed structure and effectiveness of removing out-of-plane blur for each reconstruction algorithms. Results showed the ability of ray tracing based reconstruction algorithms to provide three dimensional information with limited angle C-arm tomosynthesis.

  20. Effect of reconstruction algorithm on image quality and identification of ground-glass opacities and partly solid nodules on low-dose thin-section CT: Experimental study using chest phantom

    International Nuclear Information System (INIS)

    Koyama, Hisanobu; Ohno, Yoshiharu; Kono, Atsushi A.; Kusaka, Akiko; Konishi, Minoru; Yoshii, Masaru; Sugimura, Kazuro

    2010-01-01

    Purpose: The purpose of this study was to assess the influence of reconstruction algorithm on identification and image quality of ground-glass opacities (GGOs) and partly solid nodules on low-dose thin-section CT. Materials and methods: A chest CT phantom including simulated GGOs and partly solid nodules was scanned with five different tube currents and reconstructed by using standard (A) and newly developed (B) high-resolution reconstruction algorithms, followed by visually assessment of identification and image quality of GGOs and partly solid nodules by two chest radiologists. Inter-observer agreement, ROC analysis and ANOVA were performed to compare identification and image quality of each data set with those of the standard reference. The standard reference used 120 mA s in conjunction with reconstruction algorithm A. Results: Kappa values (κ) of overall identification and image qualities were substantial or almost perfect (0.60 < κ). Assessment of identification showed that area under the curve of 25 mA reconstructed with reconstruction algorithm A was significantly lower than that of standard reference (p < 0.05), while assessment of image quality indicated that 50 mA s reconstructed with reconstruction algorithm A and 25 mA s reconstructed with both reconstruction algorithms were significantly lower than standard reference (p < 0.05). Conclusion: Reconstruction algorithm may be an important factor for identification and image quality of ground-glass opacities and partly solid nodules on low-dose CT examination.

  1. Regularized non-stationary morphological reconstruction algorithm for weak signal detection in microseismic monitoring: methodology

    Science.gov (United States)

    Huang, Weilin; Wang, Runqiu; Chen, Yangkang

    2018-05-01

    Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.

  2. First experiences with model based iterative reconstructions influence on quantitative plaque volume and intensity measurements in coronary computed tomography angiography

    DEFF Research Database (Denmark)

    Precht, Helle; Kitslaar, Pieter H.; Broersen, Alexander

    2017-01-01

    Purpose: Investigate the influence of adaptive statistical iterative reconstruction (ASIR) and the model- based IR (Veo) reconstruction algorithm in coronary computed tomography angiography (CCTA) im- ages on quantitative measurements in coronary arteries for plaque volumes and intensities. Methods...

  3. An accurate projection algorithm for array processor based SPECT systems

    International Nuclear Information System (INIS)

    King, M.A.; Schwinger, R.B.; Cool, S.L.

    1985-01-01

    A data re-projection algorithm has been developed for use in single photon emission computed tomography (SPECT) on an array processor based computer system. The algorithm makes use of an accurate representation of pixel activity (uniform square pixel model of intensity distribution), and is rapidly performed due to the efficient handling of an array based algorithm and the Fast Fourier Transform (FFT) on parallel processing hardware. The algorithm consists of using a pixel driven nearest neighbour projection operation to an array of subdivided projection bins. This result is then convolved with the projected uniform square pixel distribution before being compressed to original bin size. This distribution varies with projection angle and is explicitly calculated. The FFT combined with a frequency space multiplication is used instead of a spatial convolution for more rapid execution. The new algorithm was tested against other commonly used projection algorithms by comparing the accuracy of projections of a simulated transverse section of the abdomen against analytically determined projections of that transverse section. The new algorithm was found to yield comparable or better standard error and yet result in easier and more efficient implementation on parallel hardware. Applications of the algorithm include iterative reconstruction and attenuation correction schemes and evaluation of regions of interest in dynamic and gated SPECT

  4. Variability and accuracy of coronary CT angiography including use of iterative reconstruction algorithms for plaque burden assessment as compared with intravascular ultrasound - an ex vivo study

    Energy Technology Data Exchange (ETDEWEB)

    Stolzmann, Paul [Massachusetts General Hospital and Harvard Medical School, Cardiac MR PET CT Program, Boston, MA (United States); University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland); Schlett, Christopher L.; Maurovich-Horvat, Pal; Scheffel, Hans; Engel, Leif-Christopher; Karolyi, Mihaly; Hoffmann, Udo [Massachusetts General Hospital and Harvard Medical School, Cardiac MR PET CT Program, Boston, MA (United States); Maehara, Akiko; Ma, Shixin; Mintz, Gary S. [Columbia University Medical Center, Cardiovascular Research Foundation, New York, NY (United States)

    2012-10-15

    To systematically assess inter-technique and inter-/intra-reader variability of coronary CT angiography (CTA) to measure plaque burden compared with intravascular ultrasound (IVUS) and to determine whether iterative reconstruction algorithms affect variability. IVUS and CTA data were acquired from nine human coronary arteries ex vivo. CT images were reconstructed using filtered back projection (FBPR) and iterative reconstruction algorithms: adaptive-statistical (ASIR) and model-based (MBIR). After co-registration of 284 cross-sections between IVUS and CTA, two readers manually delineated the cross-sectional plaque area in all images presented in random order. Average plaque burden by IVUS was 63.7 {+-} 10.7% and correlated significantly with all CTA measurements (r = 0.45-0.52; P < 0.001), while CTA overestimated the burden by 10 {+-} 10%. There were no significant differences among FBPR, ASIR and MBIR (P > 0.05). Increased overestimation was associated with smaller plaques, eccentricity and calcification (P < 0.001). Reproducibility of plaque burden by CTA and IVUS datasets was excellent with a low mean intra-/inter-reader variability of <1/<4% for CTA and <0.5/<1% for IVUS respectively (P < 0.05) with no significant difference between CT reconstruction algorithms (P > 0.05). In ex vivo coronary arteries, plaque burden by coronary CTA had extremely low inter-/intra-reader variability and correlated significantly with IVUS measurements. Accuracy as well as reader reliability were independent of CT image reconstruction algorithm. (orig.)

  5. Mean-variance analysis of block-iterative reconstruction algorithms modeling 3D detector response in SPECT

    Science.gov (United States)

    Lalush, D. S.; Tsui, B. M. W.

    1998-06-01

    We study the statistical convergence properties of two fast iterative reconstruction algorithms, the rescaled block-iterative (RBI) and ordered subset (OS) EM algorithms, in the context of cardiac SPECT with 3D detector response modeling. The Monte Carlo method was used to generate nearly noise-free projection data modeling the effects of attenuation, detector response, and scatter from the MCAT phantom. One thousand noise realizations were generated with an average count level approximating a typical T1-201 cardiac study. Each noise realization was reconstructed using the RBI and OS algorithms for cases with and without detector response modeling. For each iteration up to twenty, we generated mean and variance images, as well as covariance images for six specific locations. Both OS and RBI converged in the mean to results that were close to the noise-free ML-EM result using the same projection model. When detector response was not modeled in the reconstruction, RBI exhibited considerably lower noise variance than OS for the same resolution. When 3D detector response was modeled, the RBI-EM provided a small improvement in the tradeoff between noise level and resolution recovery, primarily in the axial direction, while OS required about half the number of iterations of RBI to reach the same resolution. We conclude that OS is faster than RBI, but may be sensitive to errors in the projection model. Both OS-EM and RBI-EM are effective alternatives to the EVIL-EM algorithm, but noise level and speed of convergence depend on the projection model used.

  6. Image Reconstruction for Diffuse Optical Tomography Based on Radiative Transfer Equation

    Directory of Open Access Journals (Sweden)

    Bo Bi

    2015-01-01

    L2 regularization. Results also show the competitive performance of the split Bregman algorithm for the DOT image reconstruction with sparsity regularization compared with other existing L1 algorithms.

  7. MR image reconstruction via guided filter.

    Science.gov (United States)

    Huang, Heyan; Yang, Hang; Wang, Kang

    2018-04-01

    Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.

  8. Model-Based Photoacoustic Image Reconstruction using Compressed Sensing and Smoothed L0 Norm

    OpenAIRE

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-01-01

    Photoacoustic imaging (PAI) is a novel medical imaging modality that uses the advantages of the spatial resolution of ultrasound imaging and the high contrast of pure optical imaging. Analytical algorithms are usually employed to reconstruct the photoacoustic (PA) images as a result of their simple implementation. However, they provide a low accurate image. Model-based (MB) algorithms are used to improve the image quality and accuracy while a large number of transducers and data acquisition a...

  9. Plane-Based Sampling for Ray Casting Algorithm in Sequential Medical Images

    Science.gov (United States)

    Lin, Lili; Chen, Shengyong; Shao, Yan; Gu, Zichun

    2013-01-01

    This paper proposes a plane-based sampling method to improve the traditional Ray Casting Algorithm (RCA) for the fast reconstruction of a three-dimensional biomedical model from sequential images. In the novel method, the optical properties of all sampling points depend on the intersection points when a ray travels through an equidistant parallel plan cluster of the volume dataset. The results show that the method improves the rendering speed at over three times compared with the conventional algorithm and the image quality is well guaranteed. PMID:23424608

  10. GPU based Monte Carlo for PET image reconstruction: parameter optimization

    International Nuclear Information System (INIS)

    Cserkaszky, Á; Légrády, D.; Wirth, A.; Bükki, T.; Patay, G.

    2011-01-01

    This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)

  11. Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction.

    Science.gov (United States)

    Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide

    2018-06-01

    Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.

  12. Development of an image reconstruction algorithm for a few number of projection data

    International Nuclear Information System (INIS)

    Vieira, Wilson S.; Brandao, Luiz E.; Braz, Delson

    2007-01-01

    An image reconstruction algorithm was developed for specific cases of radiotracer applications in industry (rotating cylindrical mixers), involving a very few number of projection data. The algorithm was planned for imaging radioactive isotope distributions around the center of circular planes. The method consists of adapting the original expectation maximization algorithm (EM) to solve the ill-posed emission tomography inverse problem in order to reconstruct transversal 2D images of an object with only four projections. To achieve this aim, counts of photons emitted by selected radioactive sources in the plane, after they had been simulated using the commercial software MICROSHIELD 5.05, constitutes the projections and a computational code (SPECTEM) was developed to generate activity vectors or images related to those sources. SPECTEM is flexible to support simultaneous changes of the detectors's geometry, the medium under investigation and the properties of the gamma radiation. As a consequence of the code had been followed correctly the proposed method, good results were obtained and they encouraged us to continue the next step of the research: the validation of SPECTEM utilizing experimental data to check its real performance. We aim this code will improve considerably radiotracer methodology, making easier the diagnosis of fails in industrial processes. (author)

  13. Development of an image reconstruction algorithm for a few number of projection data

    Energy Technology Data Exchange (ETDEWEB)

    Vieira, Wilson S.; Brandao, Luiz E. [Instituto de Engenharia Nuclear (IEN-CNEN/RJ), Rio de Janeiro , RJ (Brazil)]. E-mails: wilson@ien.gov.br; brandao@ien.gov.br; Braz, Delson [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programa de Pos-graduacao de Engenharia (COPPE). Lab. de Instrumentacao Nuclear]. E-mail: delson@mailhost.lin.ufrj.br

    2007-07-01

    An image reconstruction algorithm was developed for specific cases of radiotracer applications in industry (rotating cylindrical mixers), involving a very few number of projection data. The algorithm was planned for imaging radioactive isotope distributions around the center of circular planes. The method consists of adapting the original expectation maximization algorithm (EM) to solve the ill-posed emission tomography inverse problem in order to reconstruct transversal 2D images of an object with only four projections. To achieve this aim, counts of photons emitted by selected radioactive sources in the plane, after they had been simulated using the commercial software MICROSHIELD 5.05, constitutes the projections and a computational code (SPECTEM) was developed to generate activity vectors or images related to those sources. SPECTEM is flexible to support simultaneous changes of the detectors's geometry, the medium under investigation and the properties of the gamma radiation. As a consequence of the code had been followed correctly the proposed method, good results were obtained and they encouraged us to continue the next step of the research: the validation of SPECTEM utilizing experimental data to check its real performance. We aim this code will improve considerably radiotracer methodology, making easier the diagnosis of fails in industrial processes. (author)

  14. The use of anatomical information for molecular image reconstruction algorithms: Attention/Scatter correction, motion compensation, and noise reduction

    Energy Technology Data Exchange (ETDEWEB)

    Chun, Se Young [School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan (Korea, Republic of)

    2016-03-15

    PET and SPECT are important tools for providing valuable molecular information about patients to clinicians. Advances in nuclear medicine hardware technologies and statistical image reconstruction algorithms enabled significantly improved image quality. Sequentially or simultaneously acquired anatomical images such as CT and MRI from hybrid scanners are also important ingredients for improving the image quality of PET or SPECT further. High-quality anatomical information has been used and investigated for attenuation and scatter corrections, motion compensation, and noise reduction via post-reconstruction filtering and regularization in inverse problems. In this article, we will review works using anatomical information for molecular image reconstruction algorithms for better image quality by describing mathematical models, discussing sources of anatomical information for different cases, and showing some examples.

  15. Distributed 3-D iterative reconstruction for quantitative SPECT

    International Nuclear Information System (INIS)

    Ju, Z.W.; Frey, E.C.; Tsui, B.M.W.

    1995-01-01

    The authors describe a distributed three dimensional (3-D) iterative reconstruction library for quantitative single-photon emission computed tomography (SPECT). This library includes 3-D projector-backprojector pairs (PBPs) and distributed 3-D iterative reconstruction algorithms. The 3-D PBPs accurately and efficiently model various combinations of the image degrading factors including attenuation, detector response and scatter response. These PBPs were validated by comparing projection data computed using the projectors with that from direct Monte Carlo (MC) simulations. The distributed 3-D iterative algorithms spread the projection-backprojection operations for all the projection angles over a heterogeneous network of single or multi-processor computers to reduce the reconstruction time. Based on a master/slave paradigm, these distributed algorithms provide dynamic load balancing and fault tolerance. The distributed algorithms were verified by comparing images reconstructed using both the distributed and non-distributed algorithms. Computation times for distributed 3-D reconstructions running on up to 4 identical processors were reduced by a factor approximately 80--90% times the number of the processors participating, compared to those for non-distributed 3-D reconstructions running on a single processor. When combined with faster affordable computers, this library provides an efficient means for implementing accurate reconstruction and compensation methods to improve quality and quantitative accuracy in SPECT images

  16. Limited angle CT reconstruction by simultaneous spatial and Radon domain regularization based on TV and data-driven tight frame

    Science.gov (United States)

    Zhang, Wenkun; Zhang, Hanming; Wang, Linyuan; Cai, Ailong; Li, Lei; Yan, Bin

    2018-02-01

    Limited angle computed tomography (CT) reconstruction is widely performed in medical diagnosis and industrial testing because of the size of objects, engine/armor inspection requirements, and limited scan flexibility. Limited angle reconstruction necessitates usage of optimization-based methods that utilize additional sparse priors. However, most of conventional methods solely exploit sparsity priors of spatial domains. When CT projection suffers from serious data deficiency or various noises, obtaining reconstruction images that meet the requirement of quality becomes difficult and challenging. To solve this problem, this paper developed an adaptive reconstruction method for limited angle CT problem. The proposed method simultaneously uses spatial and Radon domain regularization model based on total variation (TV) and data-driven tight frame. Data-driven tight frame being derived from wavelet transformation aims at exploiting sparsity priors of sinogram in Radon domain. Unlike existing works that utilize pre-constructed sparse transformation, the framelets of the data-driven regularization model can be adaptively learned from the latest projection data in the process of iterative reconstruction to provide optimal sparse approximations for given sinogram. At the same time, an effective alternating direction method is designed to solve the simultaneous spatial and Radon domain regularization model. The experiments for both simulation and real data demonstrate that the proposed algorithm shows better performance in artifacts depression and details preservation than the algorithms solely using regularization model of spatial domain. Quantitative evaluations for the results also indicate that the proposed algorithm applying learning strategy performs better than the dual domains algorithms without learning regularization model

  17. An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks.

    Science.gov (United States)

    Wang, Donghao; Wan, Jiangwen; Chen, Junying; Zhang, Qiang

    2016-09-22

    To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It's theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

  18. A Super-resolution Reconstruction Algorithm for Surveillance Video

    Directory of Open Access Journals (Sweden)

    Jian Shao

    2017-01-01

    Full Text Available Recent technological developments have resulted in surveillance video becoming a primary method of preserving public security. Many city crimes are observed in surveillance video. The most abundant evidence collected by the police is also acquired through surveillance video sources. Surveillance video footage offers very strong support for solving criminal cases, therefore, creating an effective policy, and applying useful methods to the retrieval of additional evidence is becoming increasingly important. However, surveillance video has had its failings, namely, video footage being captured in low resolution (LR and bad visual quality. In this paper, we discuss the characteristics of surveillance video and describe the manual feature registration – maximum a posteriori – projection onto convex sets to develop a super-resolution reconstruction method, which improves the quality of surveillance video. From this method, we can make optimal use of information contained in the LR video image, but we can also control the image edge clearly as well as the convergence of the algorithm. Finally, we make a suggestion on how to adjust the algorithm adaptability by analyzing the prior information of target image.

  19. A new recontruction algorithm for use with capacitance-based tomography

    Directory of Open Access Journals (Sweden)

    Ø. Isaksen

    1994-01-01

    Full Text Available A new reconstruction algorithm for use with capacitance-based process tomography is proposed. A numerical simulator, capable of calculating the capacitances for a particular sensor configuration and flow regime is used together with a parameter representation of the dielectric distribution and an optimization algorithm. The algorithm calculates these parameters and hence the dielectric distribution, by minimizing a function defined as a weighted sum of square differences between the measured and estimated capacitances. The method is tested by using both synthetic and experimental data, and the results are compared with results from the commonly used Linear Back Projection (LBP algorithm. The method is capable of obtaining the correct parameter values for all the flow regimes tested, and does provide a better estimate than the LBP method. The method proves to be very promising, and is a step towards quantitative capacitance tomography.

  20. Convergence of SART + OS + TV iterative reconstruction algorithm for optical CT imaging of gel dosimeters

    International Nuclear Information System (INIS)

    Du, Yi; Yu, Gongyi; Xiang, Xincheng; Wang, Xiangang; De Deene, Yves

    2017-01-01

    Computational simulations are used to investigate the convergence of a hybrid iterative algorithm for optical CT reconstruction, i.e. the simultaneous algebraic reconstruction technique (SART) integrated with ordered subsets (OS) iteration and total variation (TV) minimization regularization, or SART+OS+TV for short. The influence of parameter selection to reach convergence, spatial dose gradient integrity, MTF and convergent speed are discussed. It’s shown that the results of SART+OS+TV algorithm converge to the true values without significant bias, and MTF and convergent speed are affected by different parameter sets used for iterative calculation. In conclusion, the performance of the SART+OS+TV depends on parameter selection, which also implies that careful parameter tuning work is required and necessary for proper spatial performance and fast convergence. (paper)

  1. A three-step reconstruction method for fluorescence molecular tomography based on compressive sensing

    DEFF Research Database (Denmark)

    Zhu, Yansong; Jha, Abhinav K.; Dreyer, Jakob K.

    2017-01-01

    Fluorescence molecular tomography (FMT) is a promising tool for real time in vivo quantification of neurotransmission (NT) as we pursue in our BRAIN initiative effort. However, the acquired image data are noisy and the reconstruction problem is ill-posed. Further, while spatial sparsity of the NT...... matrix coherence. The resultant image data are input to a homotopy-based reconstruction strategy that exploits sparsity via ℓ1 regularization. The reconstructed image is then input to a maximum-likelihood expectation maximization (MLEM) algorithm that retains the sparseness of the input estimate...... and improves upon the quantitation by accurate Poisson noise modeling. The proposed reconstruction method was evaluated in a three-dimensional simulated setup with fluorescent sources in a cuboidal scattering medium with optical properties simulating human brain cortex (reduced scattering coefficient: 9.2 cm-1...

  2. List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

    International Nuclear Information System (INIS)

    Lamare, F; Carbayo, M J Ledesma; Cresson, T; Kontaxakis, G; Santos, A; Rest, C Cheze Le; Reader, A J; Visvikis, D

    2007-01-01

    Respiratory motion in emission tomography leads to reduced image quality. Developed correction methodology has been concentrating on the use of respiratory synchronized acquisitions leading to gated frames. Such frames, however, are of low signal-to-noise ratio as a result of containing reduced statistics. In this work, we describe the implementation of an elastic transformation within a list-mode-based reconstruction for the correction of respiratory motion over the thorax, allowing the use of all data available throughout a respiratory motion average acquisition. The developed algorithm was evaluated using datasets of the NCAT phantom generated at different points throughout the respiratory cycle. List-mode-data-based PET-simulated frames were subsequently produced by combining the NCAT datasets with Monte Carlo simulation. A non-rigid registration algorithm based on B-spline basis functions was employed to derive transformation parameters accounting for the respiratory motion using the NCAT dynamic CT images. The displacement matrices derived were subsequently applied during the image reconstruction of the original emission list mode data. Two different implementations for the incorporation of the elastic transformations within the one-pass list mode EM (OPL-EM) algorithm were developed and evaluated. The corrected images were compared with those produced using an affine transformation of list mode data prior to reconstruction, as well as with uncorrected respiratory motion average images. Results demonstrate that although both correction techniques considered lead to significant improvements in accounting for respiratory motion artefacts in the lung fields, the elastic-transformation-based correction leads to a more uniform improvement across the lungs for different lesion sizes and locations

  3. Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties

    Science.gov (United States)

    Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Asma, Evren; Kinahan, Paul E.

    2015-01-01

    Extremely low-dose CT acquisitions for the purpose of PET attenuation correction will have a high level of noise and biasing artifacts due to factors such as photon starvation. This work explores a priori knowledge appropriate for CT iterative image reconstruction for PET attenuation correction. We investigate the maximum a posteriori (MAP) framework with cluster-based, multinomial priors for the direct reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction was modeled as a Poisson log-likelihood with prior terms consisting of quadratic (Q) and mixture (M) distributions. The attenuation map is assumed to have values in 4 clusters: air+background, lung, soft tissue, and bone. Under this assumption, the MP was a mixture probability density function consisting of one exponential and three Gaussian distributions. The relative proportion of each cluster was jointly estimated during each voxel update of direct iterative coordinate decent (dICD) method. Noise-free data were generated from NCAT phantom and Poisson noise was added. Reconstruction with FBP (ramp filter) was performed on the noise-free (ground truth) and noisy data. For the noisy data, dICD reconstruction was performed with the combination of different prior strength parameters (β and γ) of Q- and M-penalties. The combined quadratic and mixture penalties reduces the RMSE by 18.7% compared to post-smoothed iterative reconstruction and only 0.7% compared to quadratic alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of quadratic and mixture priors offers regularization of both variance and bias and is a potential method to derive attenuation maps with negligible patient dose. However, the small improvement in quantitative accuracy relative to the substantial increase in algorithm complexity does not currently justify the use of mixture-based PET attenuation priors for reconstruction of CT

  4. Evaluation of 3D reconstruction algorithms for a small animal PET camera

    International Nuclear Information System (INIS)

    Johnson, C.A.; Gandler, W.R.; Seidel, J.

    1996-01-01

    The use of paired, opposing position-sensitive phototube scintillation cameras (SCs) operating in coincidence for small animal imaging with positron emitters is currently under study. Because of the low sensitivity of the system even in 3D mode and the need to produce images with high resolution, it was postulated that a 3D expectation maximization (EM) reconstruction algorithm might be well suited for this application. We investigated four reconstruction algorithms for the 3D SC PET camera: 2D filtered back-projection (FBP), 2D ordered subset EM (OSEM), 3D reprojection (3DRP), and 3D OSEM. Noise was assessed for all slices by the coefficient of variation in a simulated uniform cylinder. Resolution was assessed from a simulation of 15 point sources in the warm background of the uniform cylinder. At comparable noise levels, the resolution achieved with OSEM (0.9-mm to 1.2-mm) is significantly better than that obtained with FBP or 3DRP (1.5-mm to 2.0-mm.) Images of a rat skull labeled with 18 F-fluoride suggest that 3D OSEM can improve image quality of a small animal PET camera

  5. SU-D-207-04: GPU-Based 4D Cone-Beam CT Reconstruction Using Adaptive Meshing Method

    International Nuclear Information System (INIS)

    Zhong, Z; Gu, X; Iyengar, P; Mao, W; Wang, J; Guo, X

    2015-01-01

    Purpose: Due to the limited number of projections at each phase, the image quality of a four-dimensional cone-beam CT (4D-CBCT) is often degraded, which decreases the accuracy of subsequent motion modeling. One of the promising methods is the simultaneous motion estimation and image reconstruction (SMEIR) approach. The objective of this work is to enhance the computational speed of the SMEIR algorithm using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step is to generate the tetrahedral mesh based on the features of a reference phase 4D-CBCT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. After the mesh generation, the updated motion model and other phases of 4D-CBCT can be obtained by matching the 4D-CBCT projection images at each phase with the corresponding forward projections of the deformed reference phase of 4D-CBCT. The entire process of this 4D-CBCT reconstruction method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its tremendous parallel computing ability. Results: A 4D XCAT digital phantom was used to test the proposed mesh-based image reconstruction algorithm. The image Result shows both bone structures and inside of the lung are well-preserved and the tumor position can be well captured. Compared to the previous voxel-based CPU implementation of SMEIR, the proposed method is about 157 times faster for reconstructing a 10 -phase 4D-CBCT with dimension 256×256×150. Conclusion: The GPU-based parallel 4D CBCT reconstruction method uses the feature-based mesh for estimating motion model and demonstrates equivalent image Result with previous voxel-based SMEIR approach, with significantly improved computational speed

  6. Iterative image reconstruction algorithms in coronary CT angiography improve the detection of lipid-core plaque - a comparison with histology

    Energy Technology Data Exchange (ETDEWEB)

    Puchner, Stefan B. [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Medical University of Vienna, Department of Biomedical Imaging and Image-Guided Therapy, Vienna (Austria); Ferencik, Maros [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Harvard Medical School, Division of Cardiology, Massachusetts General Hospital, Boston, MA (United States); Maurovich-Horvat, Pal [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Semmelweis University, MTA-SE Lenduelet Cardiovascular Imaging Research Group, Heart and Vascular Center, Budapest (Hungary); Nakano, Masataka; Otsuka, Fumiyuki; Virmani, Renu [CV Path Institute Inc., Gaithersburg, MD (United States); Kauczor, Hans-Ulrich [University Hospital Heidelberg, Ruprecht-Karls-University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany); Hoffmann, Udo [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Schlett, Christopher L. [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); University Hospital Heidelberg, Ruprecht-Karls-University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany)

    2015-01-15

    To evaluate whether iterative reconstruction algorithms improve the diagnostic accuracy of coronary CT angiography (CCTA) for detection of lipid-core plaque (LCP) compared to histology. CCTA and histological data were acquired from three ex vivo hearts. CCTA images were reconstructed using filtered back projection (FBP), adaptive-statistical (ASIR) and model-based (MBIR) iterative algorithms. Vessel cross-sections were co-registered between FBP/ASIR/MBIR and histology. Plaque area <60 HU was semiautomatically quantified in CCTA. LCP was defined by histology as fibroatheroma with a large lipid/necrotic core. Area under the curve (AUC) was derived from logistic regression analysis as a measure of diagnostic accuracy. Overall, 173 CCTA triplets (FBP/ASIR/MBIR) were co-registered with histology. LCP was present in 26 cross-sections. Average measured plaque area <60 HU was significantly larger in LCP compared to non-LCP cross-sections (mm{sup 2}: 5.78 ± 2.29 vs. 3.39 ± 1.68 FBP; 5.92 ± 1.87 vs. 3.43 ± 1.62 ASIR; 6.40 ± 1.55 vs. 3.49 ± 1.50 MBIR; all p < 0.0001). AUC for detecting LCP was 0.803/0.850/0.903 for FBP/ASIR/MBIR and was significantly higher for MBIR compared to FBP (p = 0.01). MBIR increased sensitivity for detection of LCP by CCTA. Plaque area <60 HU in CCTA was associated with LCP in histology regardless of the reconstruction algorithm. However, MBIR demonstrated higher accuracy for detecting LCP, which may improve vulnerable plaque detection by CCTA. (orig.)

  7. Quick plasma equilibrium reconstruction based on GPU

    International Nuclear Information System (INIS)

    Xiao Bingjia; Huang, Y.; Luo, Z.P.; Yuan, Q.P.; Lao, L.

    2014-01-01

    A parallel code named P-EFIT which could complete an equilibrium reconstruction iteration in 250 μs is described. It is built with the CUDA TM architecture by using Graphical Processing Unit (GPU). It is described for the optimization of middle-scale matrix multiplication on GPU and an algorithm which could solve block tri-diagonal linear system efficiently in parallel. Benchmark test is conducted. Static test proves the accuracy of the P-EFIT and simulation-test proves the feasibility of using P-EFIT for real-time reconstruction on 65x65 computation grids. (author)

  8. Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction.

    Science.gov (United States)

    Huang, Hsuan-Ming; Hsiao, Ing-Tsung

    2017-01-01

    Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

  9. Model-based image reconstruction for four-dimensional PET

    International Nuclear Information System (INIS)

    Li Tianfang; Thorndyke, Brian; Schreibmann, Eduard; Yang Yong; Xing Lei

    2006-01-01

    Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case

  10. Information-theoretic discrepancy based iterative reconstructions (IDIR) for polychromatic x-ray tomography

    International Nuclear Information System (INIS)

    Jang, Kwang Eun; Lee, Jongha; Sung, Younghun; Lee, SeongDeok

    2013-01-01

    Purpose: X-ray photons generated from a typical x-ray source for clinical applications exhibit a broad range of wavelengths, and the interactions between individual particles and biological substances depend on particles' energy levels. Most existing reconstruction methods for transmission tomography, however, neglect this polychromatic nature of measurements and rely on the monochromatic approximation. In this study, we developed a new family of iterative methods that incorporates the exact polychromatic model into tomographic image recovery, which improves the accuracy and quality of reconstruction.Methods: The generalized information-theoretic discrepancy (GID) was employed as a new metric for quantifying the distance between the measured and synthetic data. By using special features of the GID, the objective function for polychromatic reconstruction which contains a double integral over the wavelength and the trajectory of incident x-rays was simplified to a paraboloidal form without using the monochromatic approximation. More specifically, the original GID was replaced with a surrogate function with two auxiliary, energy-dependent variables. Subsequently, the alternating minimization technique was applied to solve the double minimization problem. Based on the optimization transfer principle, the objective function was further simplified to the paraboloidal equation, which leads to a closed-form update formula. Numerical experiments on the beam-hardening correction and material-selective reconstruction were conducted to compare and assess the performance of conventional methods and the proposed algorithms.Results: The authors found that the GID determines the distance between its two arguments in a flexible manner. In this study, three groups of GIDs with distinct data representations were considered. The authors demonstrated that one type of GIDs that comprises “raw” data can be viewed as an extension of existing statistical reconstructions; under a

  11. Industrial Computed Tomography using Proximal Algorithm

    KAUST Repository

    Zang, Guangming

    2016-04-14

    In this thesis, we present ProxiSART, a flexible proximal framework for robust 3D cone beam tomographic reconstruction based on the Simultaneous Algebraic Reconstruction Technique (SART). We derive the proximal operator for the SART algorithm and use it for minimizing the data term in a proximal algorithm. We show the flexibility of the framework by plugging in different powerful regularizers, and show its robustness in achieving better reconstruction results in the presence of noise and using fewer projections. We compare our framework to state-of-the-art methods and existing popular software tomography reconstruction packages, on both synthetic and real datasets, and show superior reconstruction quality, especially from noisy data and a small number of projections.

  12. Algorithm Validation of the Current Profile Reconstruction of EAST Based on Polarimeter/Interferometer

    International Nuclear Information System (INIS)

    Qian Jinping; Ren Qilong; Wan Baonian; Liu Haiqin; Zeng Long; Luo Zhengping; Chen Dalong; Shi Tonghui; Sun Youwen; Shen Biao; Xiao Bingjia; Lao, L. L.; Hanada, K.

    2015-01-01

    The method of plasma current profile reconstruction using the polarimeter/interferometer (POINT) data from a simulated equilibrium is explored and validated. It is shown that the safety factor (q) profile can be generally reconstructed from the external magnetic and POINT data. The reconstructed q profile is found to reasonably agree with the initial equilibriums. Comparisons of reconstructed q and density profiles using the magnetic data and the POINT data with 3%, 5% and 10% random errors are investigated. The result shows that the POINT data could be used to a reasonably accurate determination of the q profile. (fusion engineering)

  13. Model-based respiratory motion compensation for emission tomography image reconstruction

    International Nuclear Information System (INIS)

    Reyes, M; Malandain, G; Koulibaly, P M; Gonzalez-Ballester, M A; Darcourt, J

    2007-01-01

    In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data

  14. A Novel Kernel-Based Regularization Technique for PET Image Reconstruction

    Directory of Open Access Journals (Sweden)

    Abdelwahhab Boudjelal

    2017-06-01

    Full Text Available Positron emission tomography (PET is an imaging technique that generates 3D detail of physiological processes at the cellular level. The technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of “image reconstruction from projection”. This paper proposes a novel kernel-based regularization technique for maximum-likelihood expectation-maximization ( κ -MLEM to reconstruct the image. Compared to standard MLEM, the proposed algorithm is more robust and is more effective in removing background noise, whilst preserving the edges; this suppresses image artifacts, such as out-of-focus slice blur.

  15. Median prior constrained TV algorithm for sparse view low-dose CT reconstruction.

    Science.gov (United States)

    Liu, Yi; Shangguan, Hong; Zhang, Quan; Zhu, Hongqing; Shu, Huazhong; Gui, Zhiguo

    2015-05-01

    It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current, has been demonstrated to be able to result in significant radiation dose reduction while maintain image quality, noticeable patchy artifacts still exist in reconstructed images. In this study, to address the problem of patchy artifacts, we proposed a median prior constrained TV regularization to retain the image quality by introducing an auxiliary vector m in register with the object. Specifically, the approximate action of m is to draw, in each iteration, an object voxel toward its own local median, aiming to improve low-dose image quality with sparse-view projection measurements. Subsequently, an alternating optimization algorithm is adopted to optimize the associative objective function. We refer to the median prior constrained TV regularization as "TV_MP" for simplicity. Experimental results on digital phantoms and clinical phantom demonstrated that the proposed TV_MP with appropriate control parameters can not only ensure a higher signal to noise ratio (SNR) of the reconstructed image, but also its resolution compared with the original TV method. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

    International Nuclear Information System (INIS)

    Chen Jian-Lin; Li Lei; Wang Lin-Yuan; Cai Ai-Long; Xi Xiao-Qi; Zhang Han-Ming; Li Jian-Xin; Yan Bin

    2015-01-01

    The projection matrix model is used to describe the physical relationship between reconstructed object and projection. Such a model has a strong influence on projection and backprojection, two vital operations in iterative computed tomographic reconstruction. The distance-driven model (DDM) is a state-of-the-art technology that simulates forward and back projections. This model has a low computational complexity and a relatively high spatial resolution; however, it includes only a few methods in a parallel operation with a matched model scheme. This study introduces a fast and parallelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations. Our proposed model has been implemented on a GPU (graphic processing unit) platform and has achieved satisfactory computational efficiency with no approximation. The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop, respectively, with an image size of 256×256×256 and 360 projections with a size of 512×512. We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation. The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction. (paper)

  17. Jet Vertex Charge Reconstruction

    CERN Document Server

    Nektarijevic, Snezana; The ATLAS collaboration

    2015-01-01

    A newly developed algorithm called the jet vertex charge tagger, aimed at identifying the sign of the charge of jets containing $b$-hadrons, referred to as $b$-jets, is presented. In addition to the well established track-based jet charge determination, this algorithm introduces the so-called \\emph{jet vertex charge} reconstruction, which exploits the charge information associated to the displaced vertices within the jet. Furthermore, the charge of a soft muon contained in the jet is taken into account when available. All available information is combined into a multivariate discriminator. The algorithm has been developed on jets matched to generator level $b$-hadrons provided by $t\\bar{t}$ events simulated at $\\sqrt{s}$=13~TeV using the full ATLAS detector simulation and reconstruction.

  18. Efficient parsimony-based methods for phylogenetic network reconstruction.

    Science.gov (United States)

    Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir

    2007-01-15

    Phylogenies--the evolutionary histories of groups of organisms-play a major role in representing relationships among biological entities. Although many biological processes can be effectively modeled as tree-like relationships, others, such as hybrid speciation and horizontal gene transfer (HGT), result in networks, rather than trees, of relationships. Hybrid speciation is a significant evolutionary mechanism in plants, fish and other groups of species. HGT plays a major role in bacterial genome diversification and is a significant mechanism by which bacteria develop resistance to antibiotics. Maximum parsimony is one of the most commonly used criteria for phylogenetic tree inference. Roughly speaking, inference based on this criterion seeks the tree that minimizes the amount of evolution. In 1990, Jotun Hein proposed using this criterion for inferring the evolution of sequences subject to recombination. Preliminary results on small synthetic datasets. Nakhleh et al. (2005) demonstrated the criterion's application to phylogenetic network reconstruction in general and HGT detection in particular. However, the naive algorithms used by the authors are inapplicable to large datasets due to their demanding computational requirements. Further, no rigorous theoretical analysis of computing the criterion was given, nor was it tested on biological data. In the present work we prove that the problem of scoring the parsimony of a phylogenetic network is NP-hard and provide an improved fixed parameter tractable algorithm for it. Further, we devise efficient heuristics for parsimony-based reconstruction of phylogenetic networks. We test our methods on both synthetic and biological data (rbcL gene in bacteria) and obtain very promising results.

  19. Single image super resolution algorithm based on edge interpolation in NSCT domain

    Science.gov (United States)

    Zhang, Mengqun; Zhang, Wei; He, Xinyu

    2017-11-01

    In order to preserve the texture and edge information and to improve the space resolution of single frame, a superresolution algorithm based on Contourlet (NSCT) is proposed. The original low resolution image is transformed by NSCT, and the directional sub-band coefficients of the transform domain are obtained. According to the scale factor, the high frequency sub-band coefficients are amplified by the interpolation method based on the edge direction to the desired resolution. For high frequency sub-band coefficients with noise and weak targets, Bayesian shrinkage is used to calculate the threshold value. The coefficients below the threshold are determined by the correlation among the sub-bands of the same scale to determine whether it is noise and de-noising. The anisotropic diffusion filter is used to effectively enhance the weak target in the low contrast region of the target and background. Finally, the high-frequency sub-band is amplified by the bilinear interpolation method to the desired resolution, and then combined with the high-frequency subband coefficients after de-noising and small target enhancement, the NSCT inverse transform is used to obtain the desired resolution image. In order to verify the effectiveness of the proposed algorithm, the proposed algorithm and several common image reconstruction methods are used to test the synthetic image, motion blurred image and hyperspectral image, the experimental results show that compared with the traditional single resolution algorithm, the proposed algorithm can obtain smooth edges and good texture features, and the reconstructed image structure is well preserved and the noise is suppressed to some extent.

  20. Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure

    Energy Technology Data Exchange (ETDEWEB)

    Maier, Joscha, E-mail: joscha.maier@dkfz.de [Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg (Germany); Sawall, Stefan; Kachelrieß, Marc [Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany and Institute of Medical Physics, University of Erlangen–Nürnberg, 91052 Erlangen (Germany)

    2014-05-15

    Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the

  1. Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure

    International Nuclear Information System (INIS)

    Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc

    2014-01-01

    Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the

  2. Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure.

    Science.gov (United States)

    Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc

    2014-05-01

    Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the HDTV algorithm shows the

  3. Pan-sharpening via compressed superresolution reconstruction and multidictionary learning

    Science.gov (United States)

    Shi, Cheng; Liu, Fang; Li, Lingling; Jiao, Licheng; Hao, Hongxia; Shang, Ronghua; Li, Yangyang

    2018-01-01

    In recent compressed sensing (CS)-based pan-sharpening algorithms, pan-sharpening performance is affected by two key problems. One is that there are always errors between the high-resolution panchromatic (HRP) image and the linear weighted high-resolution multispectral (HRM) image, resulting in spatial and spectral information lost. The other is that the dictionary construction process depends on the nontruth training samples. These problems have limited applications to CS-based pan-sharpening algorithm. To solve these two problems, we propose a pan-sharpening algorithm via compressed superresolution reconstruction and multidictionary learning. Through a two-stage implementation, compressed superresolution reconstruction model reduces the error effectively between the HRP and the linear weighted HRM images. Meanwhile, the multidictionary with ridgelet and curvelet is learned for both the two stages in the superresolution reconstruction process. Since ridgelet and curvelet can better capture the structure and directional characteristics, a better reconstruction result can be obtained. Experiments are done on the QuickBird and IKONOS satellites images. The results indicate that the proposed algorithm is competitive compared with the recent CS-based pan-sharpening methods and other well-known methods.

  4. Favorable noise uniformity properties of Fourier-based interpolation and reconstruction approaches in single-slice helical computed tomography

    International Nuclear Information System (INIS)

    La Riviere, Patrick J.; Pan Xiaochuan

    2002-01-01

    Volumes reconstructed by standard methods from single-slice helical computed tomography (CT) data have been shown to have noise levels that are highly nonuniform relative to those in conventional CT. These noise nonuniformities can affect low-contrast object detectability and have also been identified as the cause of the zebra artifacts that plague maximum intensity projection (MIP) images of such volumes. While these spatially variant noise levels have their root in the peculiarities of the helical scan geometry, there is also a strong dependence on the interpolation and reconstruction algorithms employed. In this paper, we seek to develop image reconstruction strategies that eliminate or reduce, at its source, the nonuniformity of noise levels in helical CT relative to that in conventional CT. We pursue two approaches, independently and in concert. We argue, and verify, that Fourier-based longitudinal interpolation approaches lead to more uniform noise ratios than do the standard 360LI and 180LI approaches. We also demonstrate that a Fourier-based fan-to-parallel rebinning algorithm, used as an alternative to fanbeam filtered backprojection for slice reconstruction, also leads to more uniform noise ratios, even when making use of the 180LI and 360LI interpolation approaches

  5. Simulation and experimental studies of three-dimensional (3D) image reconstruction from insufficient sampling data based on compressed-sensing theory for potential applications to dental cone-beam CT

    International Nuclear Information System (INIS)

    Je, U.K.; Lee, M.S.; Cho, H.S.; Hong, D.K.; Park, Y.O.; Park, C.K.; Cho, H.M.; Choi, S.I.; Woo, T.H.

    2015-01-01

    In practical applications of three-dimensional (3D) tomographic imaging, there are often challenges for image reconstruction from insufficient sampling data. In computed tomography (CT), for example, image reconstruction from sparse views and/or limited-angle (<360°) views would enable fast scanning with reduced imaging doses to the patient. In this study, we investigated and implemented a reconstruction algorithm based on the compressed-sensing (CS) theory, which exploits the sparseness of the gradient image with substantially high accuracy, for potential applications to low-dose, high-accurate dental cone-beam CT (CBCT). We performed systematic simulation works to investigate the image characteristics and also performed experimental works by applying the algorithm to a commercially-available dental CBCT system to demonstrate its effectiveness for image reconstruction in insufficient sampling problems. We successfully reconstructed CBCT images of superior accuracy from insufficient sampling data and evaluated the reconstruction quality quantitatively. Both simulation and experimental demonstrations of the CS-based reconstruction from insufficient data indicate that the CS-based algorithm can be applied directly to current dental CBCT systems for reducing the imaging doses and further improving the image quality

  6. An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Donghao Wang

    2016-09-01

    Full Text Available To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It’s theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.

  7. Three-dimensional fracture visualisation of multidetector CT of the skull base in trauma patients: comparison of three reconstruction algorithms

    International Nuclear Information System (INIS)

    Ringl, Helmut; Schernthaner, Ruediger; Philipp, Marcel O.; Metz-Schimmerl, Sylvia; Czerny, Christian; Weber, Michael; Steiner-Ringl, Andrea; Peloschek, Philipp; Herold, Christian J.; Schima, Wolfgang; Gaebler, Christian

    2009-01-01

    The purpose of this study was to retrospectively assess the detection rate of skull-base fractures for three different three-dimensional (3D) reconstruction methods of cranial CT examinations in trauma patients. A total of 130 cranial CT examinations of patients with previous head trauma were subjected to 3D reconstruction of the skull base, using solid (SVR) and transparent (TVR) volume-rendering technique and maximum intensity projection (MIP). Three radiologists independently evaluated all reconstructions as well as standard high-resolution multiplanar reformations (HR-MPRs). Mean fracture detection rates for all readers reading rotating reconstructions were 39, 36, 61 and 64% for SVR, TVR, MIP and HR-MPR respectively. Although not significantly different from HR-MPR with respect to sensitivity (P = 0.9), MIP visualised 18% of fractures that were not reported in HR-MPR. Because of the relatively low detection rate using HR-MPRs alone, we recommend reading MIP reconstructions in addition to the obligatory HR-MPRs to improve fracture detection. (orig.)

  8. A combined reconstruction-classification method for diffuse optical tomography

    Energy Technology Data Exchange (ETDEWEB)

    Hiltunen, P [Department of Biomedical Engineering and Computational Science, Helsinki University of Technology, PO Box 3310, FI-02015 TKK (Finland); Prince, S J D; Arridge, S [Department of Computer Science, University College London, Gower Street London, WC1E 6B (United Kingdom)], E-mail: petri.hiltunen@tkk.fi, E-mail: s.prince@cs.ucl.ac.uk, E-mail: s.arridge@cs.ucl.ac.uk

    2009-11-07

    We present a combined classification and reconstruction algorithm for diffuse optical tomography (DOT). DOT is a nonlinear ill-posed inverse problem. Therefore, some regularization is needed. We present a mixture of Gaussians prior, which regularizes the DOT reconstruction step. During each iteration, the parameters of a mixture model are estimated. These associate each reconstructed pixel with one of several classes based on the current estimate of the optical parameters. This classification is exploited to form a new prior distribution to regularize the reconstruction step and update the optical parameters. The algorithm can be described as an iteration between an optimization scheme with zeroth-order variable mean and variance Tikhonov regularization and an expectation-maximization scheme for estimation of the model parameters. We describe the algorithm in a general Bayesian framework. Results from simulated test cases and phantom measurements show that the algorithm enhances the contrast of the reconstructed images with good spatial accuracy. The probabilistic classifications of each image contain only a few misclassified pixels.

  9. Frequency-domain optical tomographic image reconstruction algorithm with the simplified spherical harmonics (SP3) light propagation model.

    Science.gov (United States)

    Kim, Hyun Keol; Montejo, Ludguier D; Jia, Jingfei; Hielscher, Andreas H

    2017-06-01

    We introduce here the finite volume formulation of the frequency-domain simplified spherical harmonics model with n -th order absorption coefficients (FD-SP N ) that approximates the frequency-domain equation of radiative transfer (FD-ERT). We then present the FD-SP N based reconstruction algorithm that recovers absorption and scattering coefficients in biological tissue. The FD-SP N model with 3 rd order absorption coefficient (i.e., FD-SP 3 ) is used as a forward model to solve the inverse problem. The FD-SP 3 is discretized with a node-centered finite volume scheme and solved with a restarted generalized minimum residual (GMRES) algorithm. The absorption and scattering coefficients are retrieved using a limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. Finally, the forward and inverse algorithms are evaluated using numerical phantoms with optical properties and size that mimic small-volume tissue such as finger joints and small animals. The forward results show that the FD-SP 3 model approximates the FD-ERT (S 12 ) solution within relatively high accuracy; the average error in the phase (<3.7%) and the amplitude (<7.1%) of the partial current at the boundary are reported. From the inverse results we find that the absorption and scattering coefficient maps are more accurately reconstructed with the SP 3 model than those with the SP 1 model. Therefore, this work shows that the FD-SP 3 is an efficient model for optical tomographic imaging of small-volume media with non-diffuse properties both in terms of computational time and accuracy as it requires significantly lower CPU time than the FD-ERT (S 12 ) and also it is more accurate than the FD-SP 1 .

  10. Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis.

    Science.gov (United States)

    Kammen, Alexandra; Law, Meng; Tjan, Bosco S; Toga, Arthur W; Shi, Yonggang

    2016-01-15

    Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic

  11. Model-based microwave image reconstruction: simulations and experiments

    International Nuclear Information System (INIS)

    Ciocan, Razvan; Jiang Huabei

    2004-01-01

    We describe an integrated microwave imaging system that can provide spatial maps of dielectric properties of heterogeneous media with tomographically collected data. The hardware system (800-1200 MHz) was built based on a lock-in amplifier with 16 fixed antennas. The reconstruction algorithm was implemented using a Newton iterative method with combined Marquardt-Tikhonov regularizations. System performance was evaluated using heterogeneous media mimicking human breast tissue. Finite element method coupled with the Bayliss and Turkel radiation boundary conditions were applied to compute the electric field distribution in the heterogeneous media of interest. The results show that inclusions embedded in a 76-diameter background medium can be quantitatively reconstructed from both simulated and experimental data. Quantitative analysis of the microwave images obtained suggests that an inclusion of 14 mm in diameter is the smallest object that can be fully characterized presently using experimental data, while objects as small as 10 mm in diameter can be quantitatively resolved with simulated data

  12. Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

    Science.gov (United States)

    Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

    2018-05-08

    When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

  13. Hardware Implementation of a Modified Delay-Coordinate Mapping-Based QRS Complex Detection Algorithm

    Directory of Open Access Journals (Sweden)

    Andrej Zemva

    2007-01-01

    Full Text Available We present a modified delay-coordinate mapping-based QRS complex detection algorithm, suitable for hardware implementation. In the original algorithm, the phase-space portrait of an electrocardiogram signal is reconstructed in a two-dimensional plane using the method of delays. Geometrical properties of the obtained phase-space portrait are exploited for QRS complex detection. In our solution, a bandpass filter is used for ECG signal prefiltering and an improved method for detection threshold-level calculation is utilized. We developed the algorithm on the MIT-BIH Arrhythmia Database (sensitivity of 99.82% and positive predictivity of 99.82% and tested it on the long-term ST database (sensitivity of 99.72% and positive predictivity of 99.37%. Our algorithm outperforms several well-known QRS complex detection algorithms, including the original algorithm.

  14. Structured Light-Based 3D Reconstruction System for Plants

    Directory of Open Access Journals (Sweden)

    Thuy Tuong Nguyen

    2015-07-01

    Full Text Available Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces and software algorithms (including the proposed 3D point cloud registration and plant feature measurement. This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

  15. Structured Light-Based 3D Reconstruction System for Plants.

    Science.gov (United States)

    Nguyen, Thuy Tuong; Slaughter, David C; Max, Nelson; Maloof, Julin N; Sinha, Neelima

    2015-07-29

    Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

  16. Superficial temporal artery flap for reconstruction of complex facial defects: A new algorithm

    Directory of Open Access Journals (Sweden)

    Tarek M. Elbanoby

    2018-03-01

    Full Text Available Background A variety of island flaps can be based on the superficial temporal artery with variable tissue composition. They can be used for defect reconstruction, cavity resurfacing, facial hair restoration, or contracture release. Methods Seventy-two patients underwent facial reconstruction using a superficial temporal artery island flap from October 2010 to October 2014. The defects had various etiologies, including trauma, burns, tumors, exposed hardware, and congenital causes. We classified the patients by indication into 5 groups: cavity resurfacing, contracture release, facial hair restoration, skin coverage, and combined. The demographic data of the patients, defect characteristics, operative procedures, postoperative results, and complications were retrospectively documented. The follow-up period ranged from 24 to 54 months. Results A total of 24 females and 48 males were included in this study. The mean age of the patients was 33.7±15.6 years. The flaps were used for contracture release in 13 cases, cavity resurfacing in 10 cases, skin coverage in 17 cases, facial hair restoration in 19 cases, and combined defects in 13 cases. No major complications were reported. Conclusion: Based on our experiences with the use of superficial temporal artery island flaps, we have developed a detailed approach for the optimal management of patients with composite facial defects. The aim of this article is to provide the reader with a systematic algorithm to use for such patients.

  17. Computational acceleration for MR image reconstruction in partially parallel imaging.

    Science.gov (United States)

    Ye, Xiaojing; Chen, Yunmei; Huang, Feng

    2011-05-01

    In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images.

  18. Intra-patient comparison of reduced-dose model-based iterative reconstruction with standard-dose adaptive statistical iterative reconstruction in the CT diagnosis and follow-up of urolithiasis

    Energy Technology Data Exchange (ETDEWEB)

    Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth [Peninsula Radiology Academy, Plymouth (United Kingdom); Vardhanabhuti, Varut [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); University of Hong Kong, Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, Pokfulam (China); Stuckey, Colin; Gutteridge, Catherine [Plymouth Hospitals NHS Trust, Plymouth (United Kingdom); Hyde, Christopher [University of Exeter Medical School, St Luke' s Campus, Exeter (United Kingdom); Roobottom, Carl [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); Plymouth Hospitals NHS Trust, Plymouth (United Kingdom)

    2017-10-15

    To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. (orig.)

  19. Enhanced temporal resolution at cardiac CT with a novel CT image reconstruction algorithm: Initial patient experience

    Energy Technology Data Exchange (ETDEWEB)

    Apfaltrer, Paul, E-mail: paul.apfaltrer@medma.uni-heidelberg.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Schoendube, Harald, E-mail: harald.schoendube@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Schoepf, U. Joseph, E-mail: schoepf@musc.edu [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Allmendinger, Thomas, E-mail: thomas.allmendinger@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Tricarico, Francesco, E-mail: francescotricarico82@gmail.com [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Department of Bioimaging and Radiological Sciences, Catholic University of the Sacred Heart, “A. Gemelli” Hospital, Largo A. Gemelli 8, Rome (Italy); Schindler, Andreas, E-mail: andreas.schindler@campus.lmu.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Vogt, Sebastian, E-mail: sebastian.vogt@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Sunnegårdh, Johan, E-mail: johan.sunnegardh@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); and others

    2013-02-15

    Objective: To evaluate the effect of a temporal resolution improvement method (TRIM) for cardiac CT on diagnostic image quality for coronary artery assessment. Materials and methods: The TRIM-algorithm employs an iterative approach to reconstruct images from less than 180° of projections and uses a histogram constraint to prevent the occurrence of limited-angle artifacts. This algorithm was applied in 11 obese patients (7 men, 67.2 ± 9.8 years) who had undergone second generation dual-source cardiac CT with 120 kV, 175–426 mAs, and 500 ms gantry rotation. All data were reconstructed with a temporal resolution of 250 ms using traditional filtered-back projection (FBP) and of 200 ms using the TRIM-algorithm. Contrast attenuation and contrast-to-noise-ratio (CNR) were measured in the ascending aorta. The presence and severity of coronary motion artifacts was rated on a 4-point Likert scale. Results: All scans were considered of diagnostic quality. Mean BMI was 36 ± 3.6 kg/m{sup 2}. Average heart rate was 60 ± 9 bpm. Mean effective dose was 13.5 ± 4.6 mSv. When comparing FBP- and TRIM reconstructed series, the attenuation within the ascending aorta (392 ± 70.7 vs. 396.8 ± 70.1 HU, p > 0.05) and CNR (13.2 ± 3.2 vs. 11.7 ± 3.1, p > 0.05) were not significantly different. A total of 110 coronary segments were evaluated. All studies were deemed diagnostic; however, there was a significant (p < 0.05) difference in the severity score distribution of coronary motion artifacts between FBP (median = 2.5) and TRIM (median = 2.0) reconstructions. Conclusion: The algorithm evaluated here delivers diagnostic imaging quality of the coronary arteries despite 500 ms gantry rotation. Possible applications include improvement of cardiac imaging on slower gantry rotation systems or mitigation of the trade-off between temporal resolution and CNR in obese patients.

  20. A temporal interpolation approach for dynamic reconstruction in perfusion CT

    International Nuclear Information System (INIS)

    Montes, Pau; Lauritsch, Guenter

    2007-01-01

    This article presents a dynamic CT reconstruction algorithm for objects with time dependent attenuation coefficient. Projection data acquired over several rotations are interpreted as samples of a continuous signal. Based on this idea, a temporal interpolation approach is proposed which provides the maximum temporal resolution for a given rotational speed of the CT scanner. Interpolation is performed using polynomial splines. The algorithm can be adapted to slow signals, reducing the amount of data acquired and the computational cost. A theoretical analysis of the approximations made by the algorithm is provided. In simulation studies, the temporal interpolation approach is compared with three other dynamic reconstruction algorithms based on linear regression, linear interpolation, and generalized Parker weighting. The presented algorithm exhibits the highest temporal resolution for a given sampling interval. Hence, our approach needs less input data to achieve a certain quality in the reconstruction than the other algorithms discussed or, equivalently, less x-ray exposure and computational complexity. The proposed algorithm additionally allows the possibility of using slow rotating scanners for perfusion imaging purposes

  1. Application of a dual-resolution voxelization scheme to compressed-sensing (CS)-based iterative reconstruction in digital tomosynthesis (DTS)

    Science.gov (United States)

    Park, S. Y.; Kim, G. A.; Cho, H. S.; Park, C. K.; Lee, D. Y.; Lim, H. W.; Lee, H. W.; Kim, K. S.; Kang, S. Y.; Park, J. E.; Kim, W. S.; Jeon, D. H.; Je, U. K.; Woo, T. H.; Oh, J. E.

    2018-02-01

    In recent digital tomosynthesis (DTS), iterative reconstruction methods are often used owing to the potential to provide multiplanar images of superior image quality to conventional filtered-backprojection (FBP)-based methods. However, they require enormous computational cost in the iterative process, which has still been an obstacle to put them to practical use. In this work, we propose a new DTS reconstruction method incorporated with a dual-resolution voxelization scheme in attempt to overcome these difficulties, in which the voxels outside a small region-of-interest (ROI) containing target diagnosis are binned by 2 × 2 × 2 while the voxels inside the ROI remain unbinned. We considered a compressed-sensing (CS)-based iterative algorithm with a dual-constraint strategy for more accurate DTS reconstruction. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. Our results indicate that the proposed method seems to be effective for reducing computational cost considerably in iterative DTS reconstruction, keeping the image quality inside the ROI not much degraded. A binning size of 2 × 2 × 2 required only about 31.9% computational memory and about 2.6% reconstruction time, compared to those for no binning case. The reconstruction quality was evaluated in terms of the root-mean-square error (RMSE), the contrast-to-noise ratio (CNR), and the universal-quality index (UQI).

  2. Accelerating image reconstruction in three-dimensional optoacoustic tomography on graphics processing units.

    Science.gov (United States)

    Wang, Kun; Huang, Chao; Kao, Yu-Jiun; Chou, Cheng-Ying; Oraevsky, Alexander A; Anastasio, Mark A

    2013-02-01

    Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional imaging models. One important reason is because 3D image reconstruction is computationally burdensome. The aim of this work is to accelerate existing image reconstruction algorithms for 3D OAT by use of parallel programming techniques. Parallelization strategies are proposed to accelerate a filtered backprojection (FBP) algorithm and two different pairs of projection/backprojection operations that correspond to two different numerical imaging models. The algorithms are designed to fully exploit the parallel computing power of graphics processing units (GPUs). In order to evaluate the parallelization strategies for the projection/backprojection pairs, an iterative image reconstruction algorithm is implemented. Computer simulation and experimental studies are conducted to investigate the computational efficiency and numerical accuracy of the developed algorithms. The GPU implementations improve the computational efficiency by factors of 1000, 125, and 250 for the FBP algorithm and the two pairs of projection/backprojection operators, respectively. Accurate images are reconstructed by use of the FBP and iterative image reconstruction algorithms from both computer-simulated and experimental data. Parallelization strategies for 3D OAT image reconstruction are proposed for the first time. These GPU-based implementations significantly reduce the computational time for 3D image reconstruction, complementing our earlier work on 3D OAT iterative image reconstruction.

  3. Graph-cut based discrete-valued image reconstruction.

    Science.gov (United States)

    Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim

    2015-05-01

    Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.

  4. Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

    Science.gov (United States)

    Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

    2014-09-09

    This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm

  5. Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

    Directory of Open Access Journals (Sweden)

    Lingli Cui

    2014-09-01

    Full Text Available This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and

  6. Study of a reconstruction algorithm for electrons in the ATLAS experiment in LHC

    International Nuclear Information System (INIS)

    Kerschen, N.

    2006-09-01

    The ATLAS experiment is a general purpose particle physics experiment mainly aimed at the discovery of the origin of mass through the research of the Higgs boson. In order to achieve this, the Large Hadron Collider at CERN will accelerate two proton beams and make them collide at the centre of the experiment. ATLAS will discover new particles through the measurement of their decay products. Electrons are such decay products: they produce an electromagnetic shower in the calorimeter by which they lose all their energy. The calorimeter is divided into cells and the deposited energy is reconstructed using an algorithm to assemble the cells into clusters. The purpose of this thesis is to study a new kind of algorithm adapting the cluster to the shower topology. In order to reconstruct the energy of the initially created electron, the cluster has to be calibrated by taking into account the energy lost in the dead material in front of the calorimeter. Therefore. a Monte-Carlo simulation of the ATLAS detector has been used to correct for effects of response modulation in position and in energy and to optimise the energy resolution as well as the linearity. An analysis of test beam data has been performed to study the behaviour of the algorithm in a more realistic environment. We show that the requirements of the experiment can be met for the linearity and resolution. The improvement of this new algorithm, compared to a fixed sized cluster. is the better recovery of Bremsstrahlung photons emitted by the electron in the material in front of the calorimeter. A Monte-Carlo analysis of the Higgs boson decay in four electrons confirms this result. (author)

  7. An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data.

    Science.gov (United States)

    Ping, Bo; Su, Fenzhen; Meng, Yunshan

    2016-01-01

    In this study, an improved Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm for determination of missing values in a spatio-temporal dataset is presented. Compared with the ordinary DINEOF algorithm, the iterative reconstruction procedure until convergence based on every fixed EOF to determine the optimal EOF mode is not necessary and the convergence criterion is only reached once in the improved DINEOF algorithm. Moreover, in the ordinary DINEOF algorithm, after optimal EOF mode determination, the initial matrix with missing data will be iteratively reconstructed based on the optimal EOF mode until the reconstruction is convergent. However, the optimal EOF mode may be not the best EOF for some reconstructed matrices generated in the intermediate steps. Hence, instead of using asingle EOF to fill in the missing data, in the improved algorithm, the optimal EOFs for reconstruction are variable (because the optimal EOFs are variable, the improved algorithm is called VE-DINEOF algorithm in this study). To validate the accuracy of the VE-DINEOF algorithm, a sea surface temperature (SST) data set is reconstructed by using the DINEOF, I-DINEOF (proposed in 2015) and VE-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF and I-DINEOF algorithms, the VE-DINEOF algorithm can significantly enhance the accuracy of reconstruction and shorten the computational time.

  8. Image reconstruction method for electrical capacitance tomography based on the combined series and parallel normalization model

    International Nuclear Information System (INIS)

    Dong, Xiangyuan; Guo, Shuqing

    2008-01-01

    In this paper, a novel image reconstruction method for electrical capacitance tomography (ECT) based on the combined series and parallel model is presented. A regularization technique is used to obtain a stabilized solution of the inverse problem. Also, the adaptive coefficient of the combined model is deduced by numerical optimization. Simulation results indicate that it can produce higher quality images when compared to the algorithm based on the parallel or series models for the cases tested in this paper. It provides a new algorithm for ECT application

  9. Feasibility study for image reconstruction in circular digital tomosynthesis (CDTS) from limited-scan angle data based on compressed-sensing theory

    Energy Technology Data Exchange (ETDEWEB)

    Park, Yeonok; Je, Uikyu; Cho, Hyosung, E-mail: hscho1@yonsei.ac.kr; Hong, Daeki; Park, Chulkyu; Cho, Heemoon; Choi, Sungil; Woo, Taeho

    2015-03-21

    In this work, we performed a feasibility study for image reconstruction in a circular digital tomosynthesis (CDTS) from limited-scan angle data based on compressed-sensing (CS) theory. Here, the X-ray source moves along an arc within a limited-scan angle (≤ 180°) on a circular path set perpendicularly to the axial direction during the image acquisition. This geometry, compared to full-angle (360°) scan geometry, allows imaging system to be designed more compactly and gives better tomographic quality than conventional linear digital tomosynthesis (DTS). We implemented an efficient CS-based reconstruction algorithm for the proposed geometry and performed systematic simulations to investigate the image characteristics. We successfully reconstructed CDTS images with incomplete projections acquired at several selected limited-scan angles of 45°, 90°, 135°, and 180° for a given tomographic angle of 80° and evaluated the reconstruction quality. Our simulation results indicate that the proposed method can provide superior tomographic quality for axial view and even for the other views (i.e., sagittal and coronal), as in computed tomography, to conventional DTS. - Highlights: • Image reconstruction is done in circular digital tomosynthesis (CDTS). • The designed geometry allows imaging system to be the better image. • An efficient compressed-sensing (CS)-based reconstruction algorithm is performed. • Proposed method can provide superior tomographic quality for the axial view.

  10. A parallel stereo reconstruction algorithm with applications in entomology (APSRA)

    Science.gov (United States)

    Bhasin, Rajesh; Jang, Won Jun; Hart, John C.

    2012-03-01

    We propose a fast parallel algorithm for the reconstruction of 3-Dimensional point clouds of insects from binocular stereo image pairs using a hierarchical approach for disparity estimation. Entomologists study various features of insects to classify them, build their distribution maps, and discover genetic links between specimens among various other essential tasks. This information is important to the pesticide and the pharmaceutical industries among others. When considering the large collections of insects entomologists analyze, it becomes difficult to physically handle the entire collection and share the data with researchers across the world. With the method presented in our work, Entomologists can create an image database for their collections and use the 3D models for studying the shape and structure of the insects thus making it easier to maintain and share. Initial feedback shows that the reconstructed 3D models preserve the shape and size of the specimen. We further optimize our results to incorporate multiview stereo which produces better overall structure of the insects. Our main contribution is applying stereoscopic vision techniques to entomology to solve the problems faced by entomologists.

  11. Iterative image reconstruction for positron emission tomography based on a detector response function estimated from point source measurements

    International Nuclear Information System (INIS)

    Tohme, Michel S; Qi Jinyi

    2009-01-01

    The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed positron emission tomography (PET) images. For efficient computation in reconstruction, the system model in PET can be factored into a product of a geometric projection matrix and sinogram blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. Direct measurement of a sinogram blurring matrix is difficult in practice because of the requirement of a collimated source. In this work, we propose a method to estimate the 2D blurring kernels from uncollimated point source measurements. Since the resulting sinogram blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo (MC) simulation, and hence provide a more accurate system model. Another advantage of the proposed method over MC simulation is that it can easily be applied to data that have undergone a transformation to reduce the data size (e.g., Fourier rebinning). Point source measurements were acquired with high count statistics in a relatively fine grid inside the microPET II scanner using a high-precision 2D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner and explicitly models the detector block structure. The resulting sinogram blurring matrix is incorporated into a maximum a posteriori (MAP) image reconstruction algorithm. The proposed method has been validated using a 3 x 3 line phantom, an ultra-micro resolution phantom and a 22 Na point source superimposed on a warm background. The results of the proposed method show improvements in both resolution and contrast ratio when compared with the MAP

  12. Vertex Reconstruction in the ATLAS Experiment at the LHC

    CERN Document Server

    Bouhova-Thacker, E; The ATLAS collaboration; Kostyukhin, V; Liebig, W; Limper, M; Piacquadio, G; Lichard, P; Weiser, C; Wildauer, A

    2009-01-01

    In the harsh environment of the Large Hadron Collider at CERN (design luminosity of $10^{34}$ cm$^{-2}$ s$^{-1}$) efficient reconstruction of vertices is crucial for many physics analyses. Described in this paper are the strategies for vertex reconstruction used in the ATLAS experiment and their implementation in the software framework Athena. The algorithms for the reconstruction of primary and secondary vertices as well as for finding of photon conversions and vertex reconstruction in jets are described. A special emphasis is made on the vertex fitting with application of additional constraints. The implementation of mentioned algorithms follows a very modular design based on object-oriented C++ and use of abstract interfaces. The user-friendly concept allows event reconstruction and physics analyses to compare and optimize their choice among different vertex reconstruction strategies. The performance of implemented algorithms has been studied on a variety of Monte Carlo samples and results are presented.

  13. SU-G-TeP2-09: Evaluation of the MaxFOV Extended Field of View (EFOV) Reconstruction Algorithm On a GE RT590 CT Scanner

    International Nuclear Information System (INIS)

    Grzetic, S; Weldon, M; Noa, K; Gupta, N

    2016-01-01

    Purpose: This study compares the newly released MaxFOV Revision 1 EFOV reconstruction algorithm for GE RT590 to the older WideView EFOV algorithm. Two radiotherapy overlays from Q-fix and Diacor, are included in our analysis. Hounsfield Units (HU) generated with the WideView algorithm varied in the extended field (beyond 50cm) and the scanned object’s border varied from slice to slice. A validation of HU consistency between the two reconstruction algorithms is performed. Methods: A CatPhan 504 and CIRS062 Electron Density Phantom were scanned on a GE RT590 CT-Simulator. The phantoms were positioned in multiple locations within the scan field of view so some of the density plugs were outside the 50cm reconstruction circle. Images were reconstructed using both the WideView and MaxFOV algorithms. The HU for each scan were characterized both in average over a volume and in profile. Results: HU values are consistent between the two algorithms. Low-density material will have a slight increase in HU value and high-density material will have a slight decrease in HU value as the distance from the sweet spot increases. Border inconsistencies and shading artifacts are still present with the MaxFOV reconstruction on the Q-fix overlay but not the Diacor overlay (It should be noted that the Q-fix overlay is not currently GE-certified). HU values for water outside the 50cm FOV are within 40HU of reconstructions at the sweet spot of the scanner. CatPhan HU profiles show improvement with the MaxFOV algorithm as it approaches the scanner edge. Conclusion: The new MaxFOV algorithm improves the contour border for objects outside of the standard FOV when using a GE-approved tabletop. Air cavities outside of the standard FOV create inconsistent object borders. HU consistency is within GE specifications and the accuracy of the phantom edge improves. Further adjustments to the algorithm are being investigated by GE.

  14. Surface Reconstruction and Image Enhancement via $L^1$-Minimization

    KAUST Repository

    Dobrev, Veselin

    2010-01-01

    A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright © by SIAM.

  15. A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods

    International Nuclear Information System (INIS)

    Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

    2014-01-01

    As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate O(1/k 2 ). In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques. (paper)

  16. A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

    Science.gov (United States)

    Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

    2014-06-21

    As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

  17. Evaluation of iterative algorithms for tomography image reconstruction: A study using a third generation industrial tomography system

    Energy Technology Data Exchange (ETDEWEB)

    Velo, Alexandre F.; Carvalho, Diego V.; Alvarez, Alexandre G.; Hamada, Margarida M.; Mesquita, Carlos H., E-mail: afvelo@usp.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2017-07-01

    The greatest impact of the tomography technology currently occurs in medicine. The success is due to the human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is much interest in using the tomography in order to know the inner of (1) the manufactured industrial objects or (2) the machines and their means of production. In these cases, the purpose of the tomography is to (a) control the quality of the final product and (b) to optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image presents a great spatial resolution with a satisfactory temporal resolution. Thus the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, such Maximum Likelihood Estimation Method (MLEM), Maximum Likelihood Transmitted Method (MLTR) and Simultaneous Iterative Reconstruction Method (SIRT. The analysis consists on measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF), to know which algorithm fits better the conditions in order to optimize system. The algorithms and the image quality analysis were performed by the Matlab® 2013b. (author)

  18. Evaluation of iterative algorithms for tomography image reconstruction: A study using a third generation industrial tomography system

    International Nuclear Information System (INIS)

    Velo, Alexandre F.; Carvalho, Diego V.; Alvarez, Alexandre G.; Hamada, Margarida M.; Mesquita, Carlos H.

    2017-01-01

    The greatest impact of the tomography technology currently occurs in medicine. The success is due to the human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is much interest in using the tomography in order to know the inner of (1) the manufactured industrial objects or (2) the machines and their means of production. In these cases, the purpose of the tomography is to (a) control the quality of the final product and (b) to optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image presents a great spatial resolution with a satisfactory temporal resolution. Thus the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, such Maximum Likelihood Estimation Method (MLEM), Maximum Likelihood Transmitted Method (MLTR) and Simultaneous Iterative Reconstruction Method (SIRT. The analysis consists on measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF), to know which algorithm fits better the conditions in order to optimize system. The algorithms and the image quality analysis were performed by the Matlab® 2013b. (author)

  19. Expediting model-based optoacoustic reconstructions with tomographic symmetries

    International Nuclear Information System (INIS)

    Lutzweiler, Christian; Deán-Ben, Xosé Luís; Razansky, Daniel

    2014-01-01

    Purpose: Image quantification in optoacoustic tomography implies the use of accurate forward models of excitation, propagation, and detection of optoacoustic signals while inversions with high spatial resolution usually involve very large matrices, leading to unreasonably long computation times. The development of fast and memory efficient model-based approaches represents then an important challenge to advance on the quantitative and dynamic imaging capabilities of tomographic optoacoustic imaging. Methods: Herein, a method for simplification and acceleration of model-based inversions, relying on inherent symmetries present in common tomographic acquisition geometries, has been introduced. The method is showcased for the case of cylindrical symmetries by using polar image discretization of the time-domain optoacoustic forward model combined with efficient storage and inversion strategies. Results: The suggested methodology is shown to render fast and accurate model-based inversions in both numerical simulations andpost mortem small animal experiments. In case of a full-view detection scheme, the memory requirements are reduced by one order of magnitude while high-resolution reconstructions are achieved at video rate. Conclusions: By considering the rotational symmetry present in many tomographic optoacoustic imaging systems, the proposed methodology allows exploiting the advantages of model-based algorithms with feasible computational requirements and fast reconstruction times, so that its convenience and general applicability in optoacoustic imaging systems with tomographic symmetries is anticipated

  20. Vertex Reconstruction for AEGIS’ FACT Detector

    CERN Document Server

    Themistokleous, Neofytos

    2017-01-01

    My project dealt with the development of a vertex reconstruction technique to discriminate antihydrogen from background signals in the AEGIS apparatus. It involved the creation of a Toy Monte-Carlo to simulate particle annihilation events, and a vertex reconstruction utility based on the Bayesian theory of probability. The first results based on 107 generated events with single track in the detector are encouraging. For such events, the algorithm can reconstruct the z-coordinate accurately , while for the r-coordinate the result is less accurate.