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.

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

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

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.

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

Fast and accurate algorithm for the computation of complex linear canonical transforms.

Science.gov (United States)

Koç, Aykut; Ozaktas, Haldun M; Hesselink, Lambertus

2010-09-01

A fast and accurate algorithm is developed for the numerical computation of the family of complex linear canonical transforms (CLCTs), which represent the input-output relationship of complex quadratic-phase systems. Allowing the linear canonical transform parameters to be complex numbers makes it possible to represent paraxial optical systems that involve complex parameters. These include lossy systems such as Gaussian apertures, Gaussian ducts, or complex graded-index media, as well as lossless thin lenses and sections of free space and any arbitrary combinations of them. Complex-ordered fractional Fourier transforms (CFRTs) are a special case of CLCTs, and therefore a fast and accurate algorithm to compute CFRTs is included as a special case of the presented algorithm. The algorithm is based on decomposition of an arbitrary CLCT matrix into real and complex chirp multiplications and Fourier transforms. The samples of the output are obtained from the samples of the input in approximately N log N time, where N is the number of input samples. A space-bandwidth product tracking formalism is developed to ensure that the number of samples is information-theoretically sufficient to reconstruct the continuous transform, but not unnecessarily redundant.

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

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

Science.gov (United States)

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.

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....

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.

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.

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.

Comprehensive Use of Curvature for Robust and Accurate Online Surface Reconstruction.

Science.gov (United States)

Lefloch, Damien; Kluge, Markus; Sarbolandi, Hamed; Weyrich, Tim; Kolb, Andreas

2017-12-01

Interactive real-time scene acquisition from hand-held depth cameras has recently developed much momentum, enabling applications in ad-hoc object acquisition, augmented reality and other fields. A key challenge to online reconstruction remains error accumulation in the reconstructed camera trajectory, due to drift-inducing instabilities in the range scan alignments of the underlying iterative-closest-point (ICP) algorithm. Various strategies have been proposed to mitigate that drift, including SIFT-based pre-alignment, color-based weighting of ICP pairs, stronger weighting of edge features, and so on. In our work, we focus on surface curvature as a feature that is detectable on range scans alone and hence does not depend on accurate multi-sensor alignment. In contrast to previous work that took curvature into consideration, however, we treat curvature as an independent quantity that we consistently incorporate into every stage of the real-time reconstruction pipeline, including densely curvature-weighted ICP, range image fusion, local surface reconstruction, and rendering. Using multiple benchmark sequences, and in direct comparison to other state-of-the-art online acquisition systems, we show that our approach significantly reduces drift, both when analyzing individual pipeline stages in isolation, as well as seen across the online reconstruction pipeline as a whole.

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)

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.

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)

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.

Accurate reconstruction of insertion-deletion histories by statistical phylogenetics.

Directory of Open Access Journals (Sweden)

Oscar Westesson

Full Text Available The Multiple Sequence Alignment (MSA is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history, it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.

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

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

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

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...

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.

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.)

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.)

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.

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.

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

A new iterative algorithm to reconstruct the refractive index.

Science.gov (United States)

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.

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.

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)

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.

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

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)

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.

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.

Accurate phylogenetic tree reconstruction from quartets: a heuristic approach.

Science.gov (United States)

Reaz, Rezwana; Bayzid, Md Shamsuzzoha; Rahman, M Sohel

2014-01-01

Supertree methods construct trees on a set of taxa (species) combining many smaller trees on the overlapping subsets of the entire set of taxa. A 'quartet' is an unrooted tree over 4 taxa, hence the quartet-based supertree methods combine many 4-taxon unrooted trees into a single and coherent tree over the complete set of taxa. Quartet-based phylogeny reconstruction methods have been receiving considerable attentions in the recent years. An accurate and efficient quartet-based method might be competitive with the current best phylogenetic tree reconstruction methods (such as maximum likelihood or Bayesian MCMC analyses), without being as computationally intensive. In this paper, we present a novel and highly accurate quartet-based phylogenetic tree reconstruction method. We performed an extensive experimental study to evaluate the accuracy and scalability of our approach on both simulated and biological datasets.

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

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

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

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.

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

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.)

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)

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

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

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)

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.)

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

Directory of Open Access Journals (Sweden)

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.

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.)

Analysis of algebraic reconstruction technique for accurate imaging of gas temperature and concentration based on tunable diode laser absorption spectroscopy

International Nuclear Information System (INIS)

Xia Hui-Hui; Kan Rui-Feng; Liu Jian-Guo; Xu Zhen-Yu; He Ya-Bai

2016-01-01

An improved algebraic reconstruction technique (ART) combined with tunable diode laser absorption spectroscopy(TDLAS) is presented in this paper for determining two-dimensional (2D) distribution of H 2 O concentration and temperature in a simulated combustion flame. This work aims to simulate the reconstruction of spectroscopic measurements by a multi-view parallel-beam scanning geometry and analyze the effects of projection rays on reconstruction accuracy. It finally proves that reconstruction quality dramatically increases with the number of projection rays increasing until more than 180 for 20 × 20 grid, and after that point, the number of projection rays has little influence on reconstruction accuracy. It is clear that the temperature reconstruction results are more accurate than the water vapor concentration obtained by the traditional concentration calculation method. In the present study an innovative way to reduce the error of concentration reconstruction and improve the reconstruction quality greatly is also proposed, and the capability of this new method is evaluated by using appropriate assessment parameters. By using this new approach, not only the concentration reconstruction accuracy is greatly improved, but also a suitable parallel-beam arrangement is put forward for high reconstruction accuracy and simplicity of experimental validation. Finally, a bimodal structure of the combustion region is assumed to demonstrate the robustness and universality of the proposed method. Numerical investigation indicates that the proposed TDLAS tomographic algorithm is capable of detecting accurate temperature and concentration profiles. This feasible formula for reconstruction research is expected to resolve several key issues in practical combustion devices. (paper)

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)

Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq.

Science.gov (United States)

Liu, Ruolin; Dickerson, Julie

2017-11-01

We propose a novel method and software tool, Strawberry, for transcript reconstruction and quantification from RNA-Seq data under the guidance of genome alignment and independent of gene annotation. Strawberry consists of two modules: assembly and quantification. The novelty of Strawberry is that the two modules use different optimization frameworks but utilize the same data graph structure, which allows a highly efficient, expandable and accurate algorithm for dealing large data. The assembly module parses aligned reads into splicing graphs, and uses network flow algorithms to select the most likely transcripts. The quantification module uses a latent class model to assign read counts from the nodes of splicing graphs to transcripts. Strawberry simultaneously estimates the transcript abundances and corrects for sequencing bias through an EM algorithm. Based on simulations, Strawberry outperforms Cufflinks and StringTie in terms of both assembly and quantification accuracies. Under the evaluation of a real data set, the estimated transcript expression by Strawberry has the highest correlation with Nanostring probe counts, an independent experiment measure for transcript expression. Strawberry is written in C++14, and is available as open source software at https://github.com/ruolin/strawberry under the MIT license.

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.

Reconstruction algorithm in compressed sensing based on maximum a posteriori estimation

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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

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

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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)

Quantitative tomography simulations and reconstruction algorithms

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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

Inverse Monte Carlo: a unified reconstruction algorithm for SPECT

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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

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.

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

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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.

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

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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.

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)

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

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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)

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.

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)

Advancements to the planogram frequency–distance rebinning algorithm

International Nuclear Information System (INIS)

Champley, Kyle M; Kinahan, Paul E; Raylman, Raymond R

2010-01-01

reconstruction) and planogram filtered backprojection image reconstruction algorithms. We show that the PFDRX algorithm produces images that are nearly as accurate as images reconstructed with the planogram filtered backprojection algorithm and more accurate than images reconstructed with the PFDR+FBP algorithm. Both the PFDR+FBP and PFDRX algorithms provide a dramatic improvement in computation time over the planogram filtered backprojection algorithm

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

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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)

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.

On-line reconstruction algorithms for the CBM and ALICE experiments

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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.

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

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)

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

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.

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.

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

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.

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

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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.

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.

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

Improvement of Quality of Reconstructed Images in Multi-Frame Fresnel Digital Holography

International Nuclear Information System (INIS)

Xiao-Wei, Lu; Jing-Zhen, Li; Hong-Yi, Chen

2010-01-01

A modified reconstruction algorithm to improve the quality of reconstructed images of multi-frame Fresnel digital holography is presented. When the reference beams are plane or spherical waves with azimuth encoding, by introducing two spherical wave factors, images can be reconstructed with only one time Fourier transform. In numerical simulation, this algorithm could simplify the reconstruction process and improve the signal-to-noise ratio of the reconstructed images. In single-frame reconstruction experiments, the accurate reconstructed image is obtained with this simplified algorithm

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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.

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

Directory of Open Access Journals (Sweden)

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.

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.

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

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.

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)

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.

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)

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

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...

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.

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

follow up reconstructed images are not appropriate considered so far. These deviations may result from changes in anatomy including tumour shrinkage and loss of weight and may result in a degraded image quality of the reconstructed images. Deformable registration methods that adapt the prior images adequately can compensate this shortcoming of PICCS. Such registration techniques, however, suffer from limited accurateness and much higher computation time for the overall reconstruction process. Therefore, the aim of this thesis was to develop a new knowledge-based reconstruction algorithm that incorporates additionally local dependent reliability information about the prior images into reconstruction algorithm. The basic idea of the new algorithm is the assumption that the prior images are composed of areas with large and of areas with small deviations. Accordingly, the areas of the prior image were assigned as variable where substantial deformations due to motion or change in structure over the time series were expected. Hence, these regions were not providing valuable structural information for the anticipated result anymore. In contrast, ''a priori'' information was assigned to structurally stationary areas where no changes were expected. Based on this composition, a weighting matrix was generated that considers the strength of these variations during reconstruction. The new algorithm was tested in different feasibility studies to common dose reduction strategies. These dose reduction strategies includes the reduction of the number of projections, the acquisition of projections with strong noise and the reduction of the acquisition space. The main aim of this work was to demonstrate the gain of image quality when prior images with major variations are used compared to standard reconstruction techniques. The studies were performed with a computer phantom, and in particular with experimental data that have been acquired with the clinical CBCT. The new reconstruction

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 .

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.

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)

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.

Simultaneous reconstruction of temperature distribution and radiative properties in participating media using a hybrid LSQR-PSO algorithm

Science.gov (United States)

Niu, Chun-Yang; Qi, Hong; Huang, Xing; Ruan, Li-Ming; Wang, Wei; Tan, He-Ping

2015-11-01

A hybrid least-square QR decomposition (LSQR)-particle swarm optimization (LSQR-PSO) algorithm was developed to estimate the three-dimensional (3D) temperature distributions and absorption coefficients simultaneously. The outgoing radiative intensities at the boundary surface of the absorbing media were simulated by the line-of-sight (LOS) method, which served as the input for the inverse analysis. The retrieval results showed that the 3D temperature distributions of the participating media with known radiative properties could be retrieved accurately using the LSQR algorithm, even with noisy data. For the participating media with unknown radiative properties, the 3D temperature distributions and absorption coefficients could be retrieved accurately using the LSQR-PSO algorithm even with measurement errors. It was also found that the temperature field could be estimated more accurately than the absorption coefficients. In order to gain insight into the effects on the accuracy of temperature distribution reconstruction, the selection of the detection direction and the angle between two detection directions was also analyzed. Project supported by the Major National Scientific Instruments and Equipment Development Special Foundation of China (Grant No. 51327803), the National Natural Science Foundation of China (Grant No. 51476043), and the Fund of Tianjin Key Laboratory of Civil Aircraft Airworthiness and Maintenance in Civil Aviation University of China.

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

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

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

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

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)

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

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.

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.

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.

Activity concentration measurements using a conjugate gradient (Siemens xSPECT) reconstruction algorithm in SPECT/CT.

Science.gov (United States)

Armstrong, Ian S; Hoffmann, Sandra A

2016-11-01

The interest in quantitative single photon emission computer tomography (SPECT) shows potential in a number of clinical applications and now several vendors are providing software and hardware solutions to allow 'SUV-SPECT' to mirror metrics used in PET imaging. This brief technical report assesses the accuracy of activity concentration measurements using a new algorithm 'xSPECT' from Siemens Healthcare. SPECT/CT data were acquired from a uniform cylinder with 5, 10, 15 and 20 s/projection and NEMA image quality phantom with 25 s/projection. The NEMA phantom had hot spheres filled with an 8 : 1 activity concentration relative to the background compartment. Reconstructions were performed using parameters defined by manufacturer presets available with the algorithm. The accuracy of activity concentration measurements was assessed. A dose calibrator-camera cross-calibration factor (CCF) was derived from the uniform phantom data. In uniform phantom images, a positive bias was observed, ranging from ∼6% in the lower count images to ∼4% in the higher-count images. On the basis of the higher-count data, a CCF of 0.96 was derived. As expected, considerable negative bias was measured in the NEMA spheres using region mean values whereas positive bias was measured in the four largest NEMA spheres. Nonmonotonically increasing recovery curves for the hot spheres suggested the presence of Gibbs edge enhancement from resolution modelling. Sufficiently accurate activity concentration measurements can easily be measured on images reconstructed with the xSPECT algorithm without a CCF. However, the use of a CCF is likely to improve accuracy further. A manual conversion of voxel values into SUV should be possible, provided that the patient weight, injected activity and time between injection and imaging are all known accurately.

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/

Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials

Energy Technology Data Exchange (ETDEWEB)

Van Eyndhoven, G., E-mail: geert.vaneyndhoven@uantwerpen.be [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Kurttepeli, M. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Van Oers, C.J.; Cool, P. [Laboratory of Adsorption and Catalysis, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Bals, S. [EMAT, University of Antwerp, Groenenborgerlaan 171, B-2020 Antwerp (Belgium); Batenburg, K.J. [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium); Centrum Wiskunde and Informatica, Science Park 123, NL-1090 GB Amsterdam (Netherlands); Mathematical Institute, Universiteit Leiden, Niels Bohrweg 1, NL-2333 CA Leiden (Netherlands); Sijbers, J. [iMinds-Vision Lab, University of Antwerp, Universiteitsplein 1, B-2610 Wilrijk (Belgium)

2015-01-15

Electron tomography is currently a versatile tool to investigate the connection between the structure and properties of nanomaterials. However, a quantitative interpretation of electron tomography results is still far from straightforward. Especially accurate quantification of pore-space is hampered by artifacts introduced in all steps of the processing chain, i.e., acquisition, reconstruction, segmentation and quantification. Furthermore, most common approaches require subjective manual user input. In this paper, the PORES algorithm “POre REconstruction and Segmentation” is introduced; it is a tailor-made, integral approach, for the reconstruction, segmentation, and quantification of porous nanomaterials. The PORES processing chain starts by calculating a reconstruction with a nanoporous-specific reconstruction algorithm: the Simultaneous Update of Pore Pixels by iterative REconstruction and Simple Segmentation algorithm (SUPPRESS). It classifies the interior region to the pores during reconstruction, while reconstructing the remaining region by reducing the error with respect to the acquired electron microscopy data. The SUPPRESS reconstruction can be directly plugged into the remaining processing chain of the PORES algorithm, resulting in accurate individual pore quantification and full sample pore statistics. The proposed approach was extensively validated on both simulated and experimental data, indicating its ability to generate accurate statistics of nanoporous materials. - Highlights: • An electron tomography reconstruction/segmentation method for nanoporous materials. • The method exploits the porous nature of the scanned material. • Validated extensively on both simulation and real data experiments. • Results in increased image resolution and improved porosity quantification.

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.

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

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

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

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

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

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)

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

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

Automated Development of Accurate Algorithms and Efficient Codes for Computational Aeroacoustics

Science.gov (United States)

Goodrich, John W.; Dyson, Rodger W.

1999-01-01

The simulation of sound generation and propagation in three space dimensions with realistic aircraft components is a very large time dependent computation with fine details. Simulations in open domains with embedded objects require accurate and robust algorithms for propagation, for artificial inflow and outflow boundaries, and for the definition of geometrically complex objects. The development, implementation, and validation of methods for solving these demanding problems is being done to support the NASA pillar goals for reducing aircraft noise levels. Our goal is to provide algorithms which are sufficiently accurate and efficient to produce usable results rapidly enough to allow design engineers to study the effects on sound levels of design changes in propulsion systems, and in the integration of propulsion systems with airframes. There is a lack of design tools for these purposes at this time. Our technical approach to this problem combines the development of new, algorithms with the use of Mathematica and Unix utilities to automate the algorithm development, code implementation, and validation. We use explicit methods to ensure effective implementation by domain decomposition for SPMD parallel computing. There are several orders of magnitude difference in the computational efficiencies of the algorithms which we have considered. We currently have new artificial inflow and outflow boundary conditions that are stable, accurate, and unobtrusive, with implementations that match the accuracy and efficiency of the propagation methods. The artificial numerical boundary treatments have been proven to have solutions which converge to the full open domain problems, so that the error from the boundary treatments can be driven as low as is required. The purpose of this paper is to briefly present a method for developing highly accurate algorithms for computational aeroacoustics, the use of computer automation in this process, and a brief survey of the algorithms that

Fast and accurate phylogeny reconstruction using filtered spaced-word matches

Science.gov (United States)

Sohrabi-Jahromi, Salma; Morgenstern, Burkhard

2017-01-01

Abstract Motivation: Word-based or ‘alignment-free’ algorithms are increasingly used for phylogeny reconstruction and genome comparison, since they are much faster than traditional approaches that are based on full sequence alignments. Existing alignment-free programs, however, are less accurate than alignment-based methods. Results: We propose Filtered Spaced Word Matches (FSWM), a fast alignment-free approach to estimate phylogenetic distances between large genomic sequences. For a pre-defined binary pattern of match and don’t-care positions, FSWM rapidly identifies spaced word-matches between input sequences, i.e. gap-free local alignments with matching nucleotides at the match positions and with mismatches allowed at the don’t-care positions. We then estimate the number of nucleotide substitutions per site by considering the nucleotides aligned at the don’t-care positions of the identified spaced-word matches. To reduce the noise from spurious random matches, we use a filtering procedure where we discard all spaced-word matches for which the overall similarity between the aligned segments is below a threshold. We show that our approach can accurately estimate substitution frequencies even for distantly related sequences that cannot be analyzed with existing alignment-free methods; phylogenetic trees constructed with FSWM distances are of high quality. A program run on a pair of eukaryotic genomes of a few hundred Mb each takes a few minutes. Availability and Implementation: The program source code for FSWM including a documentation, as well as the software that we used to generate artificial genome sequences are freely available at http://fswm.gobics.de/ Contact: chris.leimeister@stud.uni-goettingen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28073754

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...

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....

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)

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. ...

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...

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...

Historian: accurate reconstruction of ancestral sequences and evolutionary rates.

Science.gov (United States)

Holmes, Ian H

2017-04-15

Reconstruction of ancestral sequence histories, and estimation of parameters like indel rates, are improved by using explicit evolutionary models and summing over uncertain alignments. The previous best tool for this purpose (according to simulation benchmarks) was ProtPal, but this tool was too slow for practical use. Historian combines an efficient reimplementation of the ProtPal algorithm with performance-improving heuristics from other alignment tools. Simulation results on fidelity of rate estimation via ancestral reconstruction, along with evaluations on the structurally informed alignment dataset BAliBase 3.0, recommend Historian over other alignment tools for evolutionary applications. Historian is available at https://github.com/evoldoers/historian under the Creative Commons Attribution 3.0 US license. ihholmes+historian@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Robust and accurate detection algorithm for multimode polymer optical FBG sensor system

DEFF Research Database (Denmark)

Ganziy, Denis; Jespersen, O.; Rose, B.

2015-01-01

We propose a novel dynamic gate algorithm (DGA) for robust and fast peak detection. The algorithm uses a threshold determined detection window and center of gravity algorithm with bias compensation. Our experiment demonstrates that the DGA method is fast and robust with better stability and accur...

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...

Fast and accurate phylogenetic reconstruction from high-resolution whole-genome data and a novel robustness estimator.

Science.gov (United States)

Lin, Y; Rajan, V; Moret, B M E

2011-09-01

The rapid accumulation of whole-genome data has renewed interest in the study of genomic rearrangements. Comparative genomics, evolutionary biology, and cancer research all require models and algorithms to elucidate the mechanisms, history, and consequences of these rearrangements. However, even simple models lead to NP-hard problems, particularly in the area of phylogenetic analysis. Current approaches are limited to small collections of genomes and low-resolution data (typically a few hundred syntenic blocks). Moreover, whereas phylogenetic analyses from sequence data are deemed incomplete unless bootstrapping scores (a measure of confidence) are given for each tree edge, no equivalent to bootstrapping exists for rearrangement-based phylogenetic analysis. We describe a fast and accurate algorithm for rearrangement analysis that scales up, in both time and accuracy, to modern high-resolution genomic data. We also describe a novel approach to estimate the robustness of results-an equivalent to the bootstrapping analysis used in sequence-based phylogenetic reconstruction. We present the results of extensive testing on both simulated and real data showing that our algorithm returns very accurate results, while scaling linearly with the size of the genomes and cubically with their number. We also present extensive experimental results showing that our approach to robustness testing provides excellent estimates of confidence, which, moreover, can be tuned to trade off thresholds between false positives and false negatives. Together, these two novel approaches enable us to attack heretofore intractable problems, such as phylogenetic inference for high-resolution vertebrate genomes, as we demonstrate on a set of six vertebrate genomes with 8,380 syntenic blocks. A copy of the software is available on demand.

FASTSIM2: a second-order accurate frictional rolling contact algorithm

Science.gov (United States)

Vollebregt, E. A. H.; Wilders, P.

2011-01-01

In this paper we consider the frictional (tangential) steady rolling contact problem. We confine ourselves to the simplified theory, instead of using full elastostatic theory, in order to be able to compute results fast, as needed for on-line application in vehicle system dynamics simulation packages. The FASTSIM algorithm is the leading technology in this field and is employed in all dominant railway vehicle system dynamics packages (VSD) in the world. The main contribution of this paper is a new version "FASTSIM2" of the FASTSIM algorithm, which is second-order accurate. This is relevant for VSD, because with the new algorithm 16 times less grid points are required for sufficiently accurate computations of the contact forces. The approach is based on new insights in the characteristics of the rolling contact problem when using the simplified theory, and on taking precise care of the contact conditions in the numerical integration scheme employed.

Digital holography super-resolution for accurate three-dimensional reconstruction of particle holograms.

Science.gov (United States)

Verrier, Nicolas; Fournier, Corinne

2015-01-15

In-line digital holography (DH) is used in many fields to locate and size micro or nano-objects spread in a volume. To reconstruct simple shaped objects, the optimal approach is to fit an imaging model to accurately estimate their position and their characteristic parameters. Increasing the accuracy of the reconstruction is a big issue in DH, particularly when the pixel is large or the signal-to-noise ratio is low. We suggest exploiting the information redundancy of videos to improve the reconstruction of the holograms by jointly estimating the position of the objects and the characteristic parameters. Using synthetic and experimental data, we checked experimentally that this approach can improve the accuracy of the reconstruction by a factor more than the square root of the image number.

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.

A practical method for three-dimensional reconstruction of joints using a C-arm system and shift-and-add algorithm

International Nuclear Information System (INIS)

Li Senhu; Jiang Huabei

2005-01-01

Currently, radiography with C-arm systems is playing a major role in the assessment of arthritis. However, the radiographic two-dimensional projection images of joints often interfere with physicians' efforts to better understand and measure the structure changes of joints due to the overlap of bone structures at different depths. An accurate, low-cost, and practical three-dimensional (3D) reconstruction approach of joints will be beneficial in diagnosing arthritis. Toward this end, a novel method is developed in this paper based on a C-arm system. The idea is to apply the shift-and-add algorithm (commonly used in digital tomosynthesis) on the segmented projection images at multiple angles, which results in accurate reconstruction of the 3D structures of joints. The method provides a new solution to precisely distinguish objects from blurring background. The proposed method has been tested and evaluated on simulated cylinders, a chicken bone phantom with known structure, and an in vivo human index finger. The results are demonstrated and discussed

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

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

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.

Fast in vivo volume dose reconstruction via reference dose perturbation

International Nuclear Information System (INIS)

Lu, Weiguo; Chen, Mingli; Mo, Xiaohu; Parnell, Donald; Olivera, Gustavo; Galmarini, Daniel

2014-01-01

Purpose: Accurate on-line reconstruction of in-vivo volume dose that accounts for both machine and patient discrepancy is not clinically available. We present a simple reference-dose-perturbation algorithm that reconstructs in-vivo volume dose fast and accurately. Methods: We modelled the volume dose as a function of the fluence map and density image. Machine (output variation, jaw/leaf position errors, etc.) and patient (setup error, weight loss, etc.) discrepancies between the plan and delivery were modelled as perturbation of the fluence map and density image, respectively. Delivered dose is modelled as perturbation of the reference dose due to change of the fluence map and density image. We used both simulated and clinical data to validate the algorithm. The planned dose was used as the reference. The reconstruction was perturbed from the reference and accounted for output-variations and the registered daily image. The reconstruction was compared with the ground truth via isodose lines and the Gamma Index. Results: For various plans and geometries, the volume doses were reconstructed in few seconds. The reconstruction generally matched well with the ground truth. For the 3%/3mm criteria, the Gamma pass rates were 98% for simulations and 95% for clinical data. The differences mainly appeared on the surface of the phantom/patient. Conclusions: A novel reference-dose-perturbation dose reconstruction model is presented. The model accounts for machine and patient discrepancy from planning. The algorithm is simple, fast, yet accurate, which makes online in-vivo 3D dose reconstruction clinically feasible.

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

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.)

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.

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)

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.

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

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

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...

Fast Tomographic Reconstruction From Limited Data Using Artificial Neural Networks

NARCIS (Netherlands)

D.M. Pelt (Daniël); K.J. Batenburg (Joost)

2013-01-01

htmlabstractImage reconstruction from a small number of projections is a challenging problem in tomography. Advanced algorithms that incorporate prior knowledge can sometimes produce accurate reconstructions, but they typically require long computation times. Furthermore, the required prior

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.

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

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

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.

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.

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

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

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

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

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

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

Directory of Open Access Journals (Sweden)

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.

Integration of multi-modality imaging for accurate 3D reconstruction of human coronary arteries in vivo

International Nuclear Information System (INIS)

Giannoglou, George D.; Chatzizisis, Yiannis S.; Sianos, George; Tsikaderis, Dimitrios; Matakos, Antonis; Koutkias, Vassilios; Diamantopoulos, Panagiotis; Maglaveras, Nicos; Parcharidis, George E.; Louridas, George E.

2006-01-01

In conventional intravascular ultrasound (IVUS)-based three-dimensional (3D) reconstruction of human coronary arteries, IVUS images are arranged linearly generating a straight vessel volume. However, with this approach real vessel curvature is neglected. To overcome this limitation an imaging method was developed based on integration of IVUS and biplane coronary angiography (BCA). In 17 coronary arteries from nine patients, IVUS and BCA were performed. From each angiographic projection, a single end-diastolic frame was selected and in each frame the IVUS catheter was interactively detected for the extraction of 3D catheter path. Ultrasound data was obtained with a sheath-based catheter and recorded on S-VHS videotape. S-VHS data was digitized and lumen and media-adventitia contours were semi-automatically detected in end-diastolic IVUS images. Each pair of contours was aligned perpendicularly to the catheter path and rotated in space by implementing an algorithm based on Frenet-Serret rules. Lumen and media-adventitia contours were interpolated through generation of intermediate contours creating a real 3D lumen and vessel volume, respectively. The absolute orientation of the reconstructed lumen was determined by back-projecting it onto both angiographic planes and comparing the projected lumen with the actual angiographic lumen. In conclusion, our method is capable of performing rapid and accurate 3D reconstruction of human coronary arteries in vivo. This technique can be utilized for reliable plaque morphometric, geometrical and hemodynamic analyses

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)

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

Iterative feature refinement for accurate undersampled MR image reconstruction

Science.gov (United States)

Wang, Shanshan; Liu, Jianbo; Liu, Qiegen; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong

2016-05-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches.

Iterative feature refinement for accurate undersampled MR image reconstruction

International Nuclear Information System (INIS)

Wang, Shanshan; Liu, Jianbo; Liu, Xin; Zheng, Hairong; Liang, Dong; Liu, Qiegen; Ying, Leslie

2016-01-01

Accelerating MR scan is of great significance for clinical, research and advanced applications, and one main effort to achieve this is the utilization of compressed sensing (CS) theory. Nevertheless, the existing CSMRI approaches still have limitations such as fine structure loss or high computational complexity. This paper proposes a novel iterative feature refinement (IFR) module for accurate MR image reconstruction from undersampled K-space data. Integrating IFR with CSMRI which is equipped with fixed transforms, we develop an IFR-CS method to restore meaningful structures and details that are originally discarded without introducing too much additional complexity. Specifically, the proposed IFR-CS is realized with three iterative steps, namely sparsity-promoting denoising, feature refinement and Tikhonov regularization. Experimental results on both simulated and in vivo MR datasets have shown that the proposed module has a strong capability to capture image details, and that IFR-CS is comparable and even superior to other state-of-the-art reconstruction approaches. (paper)

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

Science.gov (United States)

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.

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)

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.

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

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

Axially symmetric reconstruction of plasma emission and absorption coefficients

International Nuclear Information System (INIS)

Yang Lixin; Jia Hui; Yang Jiankun; Li Xiujian; Chen Shaorong; Liu Xishun

2013-01-01

A layered structure imaging model is developed in order to reconstruct emission coefficients and absorption coefficients simultaneously, in laser fusion core plasma diagnostics. A novel axially symmetric reconstruction method that utilizes the LM (Levenberg-Marquardt) nonlinear least squares minimization algorithm is proposed based on the layered structure. Numerical simulation results demonstrate that the proposed method is sufficiently accurate to reconstruct emission coefficients and absorption coefficients, and when the standard deviation of noise is 0.01, the errors of emission coefficients and absorption coefficients are 0.17, 0.22, respectively. Furthermore, this method could perform much better on reconstruction effect compared with traditional inverse Abel transform algorithms. (authors)

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

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.

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.

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.

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)

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

DEEP WIDEBAND SINGLE POINTINGS AND MOSAICS IN RADIO INTERFEROMETRY: HOW ACCURATELY DO WE RECONSTRUCT INTENSITIES AND SPECTRAL INDICES OF FAINT SOURCES?

Energy Technology Data Exchange (ETDEWEB)

Rau, U.; Bhatnagar, S.; Owen, F. N., E-mail: rurvashi@nrao.edu [National Radio Astronomy Observatory, Socorro, NM-87801 (United States)

2016-11-01

Many deep wideband wide-field radio interferometric surveys are being designed to accurately measure intensities, spectral indices, and polarization properties of faint source populations. In this paper, we compare various wideband imaging methods to evaluate the accuracy to which intensities and spectral indices of sources close to the confusion limit can be reconstructed. We simulated a wideband single-pointing (C-array, L-Band (1–2 GHz)) and 46-pointing mosaic (D-array, C-Band (4–8 GHz)) JVLA observation using a realistic brightness distribution ranging from 1 μ Jy to 100 mJy and time-, frequency-, polarization-, and direction-dependent instrumental effects. The main results from these comparisons are (a) errors in the reconstructed intensities and spectral indices are larger for weaker sources even in the absence of simulated noise, (b) errors are systematically lower for joint reconstruction methods (such as Multi-Term Multi-Frequency-Synthesis (MT-MFS)) along with A-Projection for accurate primary beam correction, and (c) use of MT-MFS for image reconstruction eliminates Clean-bias (which is present otherwise). Auxiliary tests include solutions for deficiencies of data partitioning methods (e.g., the use of masks to remove clean bias and hybrid methods to remove sidelobes from sources left un-deconvolved), the effect of sources not at pixel centers, and the consequences of various other numerical approximations within software implementations. This paper also demonstrates the level of detail at which such simulations must be done in order to reflect reality, enable one to systematically identify specific reasons for every trend that is observed, and to estimate scientifically defensible imaging performance metrics and the associated computational complexity of the algorithms/analysis procedures.

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.

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.

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

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

Science.gov (United States)

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.

Research on reconstruction of steel tube section from few projections

International Nuclear Information System (INIS)

Peng Shuaijun; Wu Haifeng; Wang Kai

2007-01-01

Most parameters of steel tube can be acquired from CT image of the section so as to evaluate its quality. But large numbers of projections are needed in order to reconstruct the section image, so the collection and calculation of the projections consume lots of time. In order to solve the problem, reconstruction algorithms of steel tube from few projections are researched and the results are validated with simulation data in the paper. Three iterative algorithms, ART, MAP and OSEM, are attempted to reconstruct the section of steel tube by using the simulation model. Considering the prior information distributing of steel tube, we improve the algorithms and get better reconstruction images. The results of simulation experiment indicate that ART, MAP and OSEM can reconstruct accurate section images of steel tube from less than 20 projections and approximate images from 10 projections. (authors)

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.

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

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.

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

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

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.

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...

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)

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)

Toward Accurate On-Ground Attitude Determination for the Gaia Spacecraft

Science.gov (United States)

Samaan, Malak A.

2010-03-01

The work presented in this paper concerns the accurate On-Ground Attitude (OGA) reconstruction for the astrometry spacecraft Gaia in the presence of disturbance and of control torques acting on the spacecraft. The reconstruction of the expected environmental torques which influence the spacecraft dynamics will be also investigated. The telemetry data from the spacecraft will include the on-board real-time attitude, which is of order of several arcsec. This raw attitude is the starting point for the further attitude reconstruction. The OGA will use the inputs from the field coordinates of known stars (attitude stars) and also the field coordinate differences of objects on the Sky Mapper (SM) and Astrometric Field (AF) payload instruments to improve this raw attitude. The on-board attitude determination uses a Kalman Filter (KF) to minimize the attitude errors and produce a more accurate attitude estimation than the pure star tracker measurement. Therefore the first approach for the OGA will be an adapted version of KF. Furthermore, we will design a batch least squares algorithm to investigate how to obtain a more accurate OGA estimation. Finally, a comparison between these different attitude determination techniques in terms of accuracy, robustness, speed and memory required will be evaluated in order to choose the best attitude algorithm for the OGA. The expected resulting accuracy for the OGA determination will be on the order of milli-arcsec.

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

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

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)

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.

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.

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.

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%.

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

Science.gov (United States)

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.

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)

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.

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.)

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)

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

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.

Simultaneous reconstruction of attenuation and activity in ToF PET/MRI with additional transmission data

Energy Technology Data Exchange (ETDEWEB)

D’Hoe, Ester [MEDISIP Medical Imaging and Signal Processing Group, Ghent University, IBBT-IBiTech, iMinds Medical IT, Ghent (Belgium); Department of Nuclear Medicine, Vrije Universiteit Brussel, Brussels (Belgium); Mollet, Pieter; Mikhaylova, Ekaterina [MEDISIP Medical Imaging and Signal Processing Group, Ghent University, IBBT-IBiTech, iMinds Medical IT, Ghent (Belgium); Defrise, Michel [Department of Nuclear Medicine, Vrije Universiteit Brussel, Brussels (Belgium); Vandenberghe, Stefaan [MEDISIP Medical Imaging and Signal Processing Group, Ghent University, IBBT-IBiTech, iMinds Medical IT, Ghent (Belgium)

2015-05-18

In Time-of-Flight PET/MRI systems accurate attenuation correction, based on the MRI image, is not straight forward. An alternative is attenuation correction based on emission data only. This is for instance done by simultaneous reconstruction of attenuation and activity with the MLAA algorithm, but the method as originally proposed has certain limits. The attenuation can only be determined up to a constant and in regions of low tracer uptake, the method results in less accurate attenuation values. An adapted MLAA algorithm has been proposed to overcome this issues and was successfully applied on simulation studies. The so called MLAA+ algorithm uses regular PET emission data as well as transmission data. This transmission data is acquired after insertion of an annulus shaped transmission source into the scanner bore. The Time-of-Flight information allows to separate transmission and emission data in a simultaneous acquisition. With the transmission data, an MLTR-based reference attenuation image is reconstructed. Afterwards, this attenuation image is used in the MLAA+ simultaneous reconstruction of attenuation and emission as a reference. We here propose the results of the reconstruction of patient data, based on the MLAA+ algorithm. In total, seven patients were scanned in a sequential PET/MRI scanner and afterwards in a CT scanner. The CT scan is used as an attenuation map to reconstruct the PET emission data with the well established MLEM algorithm. This reconstruction can be seen as the gold standard to which we can compare the MLAA and MLAA+ reconstructions. A preliminary study on one patient indicates that the MLAA+ algorithm results in better reconstructed emission and attenuation images as compared to the MLAA algorithm. If we compare the MLAA+ method to the gold standard, there is still room for improvement.

Simultaneous reconstruction of attenuation and activity in ToF PET/MRI with additional transmission data

International Nuclear Information System (INIS)

D’Hoe, Ester; Mollet, Pieter; Mikhaylova, Ekaterina; Defrise, Michel; Vandenberghe, Stefaan

2015-01-01

In Time-of-Flight PET/MRI systems accurate attenuation correction, based on the MRI image, is not straight forward. An alternative is attenuation correction based on emission data only. This is for instance done by simultaneous reconstruction of attenuation and activity with the MLAA algorithm, but the method as originally proposed has certain limits. The attenuation can only be determined up to a constant and in regions of low tracer uptake, the method results in less accurate attenuation values. An adapted MLAA algorithm has been proposed to overcome this issues and was successfully applied on simulation studies. The so called MLAA+ algorithm uses regular PET emission data as well as transmission data. This transmission data is acquired after insertion of an annulus shaped transmission source into the scanner bore. The Time-of-Flight information allows to separate transmission and emission data in a simultaneous acquisition. With the transmission data, an MLTR-based reference attenuation image is reconstructed. Afterwards, this attenuation image is used in the MLAA+ simultaneous reconstruction of attenuation and emission as a reference. We here propose the results of the reconstruction of patient data, based on the MLAA+ algorithm. In total, seven patients were scanned in a sequential PET/MRI scanner and afterwards in a CT scanner. The CT scan is used as an attenuation map to reconstruct the PET emission data with the well established MLEM algorithm. This reconstruction can be seen as the gold standard to which we can compare the MLAA and MLAA+ reconstructions. A preliminary study on one patient indicates that the MLAA+ algorithm results in better reconstructed emission and attenuation images as compared to the MLAA algorithm. If we compare the MLAA+ method to the gold standard, there is still room for improvement.

Reconstruction of bremsstrahlung spectra from attenuation data using generalized simulated annealing

International Nuclear Information System (INIS)

Menin, O.H.; Martinez, A.S.; Costa, A.M.

2016-01-01

A generalized simulated annealing algorithm, combined with a suitable smoothing regularization function is used to solve the inverse problem of X-ray spectrum reconstruction from attenuation data. The approach is to set the initial acceptance and visitation temperatures and to standardize the terms of objective function to automate the algorithm to accommodate different spectra ranges. Experiments with both numerical and measured attenuation data are presented. Results show that the algorithm reconstructs spectra shapes accurately. It should be noted that in this algorithm, the regularization function was formulated to guarantee a smooth spectrum, thus, the presented technique does not apply to X-ray spectrum where characteristic radiation are present. - Highlights: • X-ray spectra reconstruction from attenuation data using generalized simulated annealing. • Algorithm employs a smoothing regularization function, and sets the initial acceptance and visitation temperatures. • Algorithmic is automated by standardizing the terms of the objective function. • Algorithm is compared with classical methods.

Fully automated reconstruction of three-dimensional vascular tree structures from two orthogonal views using computational algorithms and productionrules

Science.gov (United States)

Liu, Iching; Sun, Ying

1992-10-01

A system for reconstructing 3-D vascular structure from two orthogonally projected images is presented. The formidable problem of matching segments between two views is solved using knowledge of the epipolar constraint and the similarity of segment geometry and connectivity. The knowledge is represented in a rule-based system, which also controls the operation of several computational algorithms for tracking segments in each image, representing 2-D segments with directed graphs, and reconstructing 3-D segments from matching 2-D segment pairs. Uncertain reasoning governs the interaction between segmentation and matching; it also provides a framework for resolving the matching ambiguities in an iterative way. The system was implemented in the C language and the C Language Integrated Production System (CLIPS) expert system shell. Using video images of a tree model, the standard deviation of reconstructed centerlines was estimated to be 0.8 mm (1.7 mm) when the view direction was parallel (perpendicular) to the epipolar plane. Feasibility of clinical use was shown using x-ray angiograms of a human chest phantom. The correspondence of vessel segments between two views was accurate. Computational time for the entire reconstruction process was under 30 s on a workstation. A fully automated system for two-view reconstruction that does not require the a priori knowledge of vascular anatomy is demonstrated.

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

Science.gov (United States)

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

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.

Anatomically Plausible Surface Alignment and Reconstruction

DEFF Research Database (Denmark)

Paulsen, Rasmus R.; Larsen, Rasmus

2010-01-01

With the increasing clinical use of 3D surface scanners, there is a need for accurate and reliable algorithms that can produce anatomically plausible surfaces. In this paper, a combined method for surface alignment and reconstruction is proposed. It is based on an implicit surface representation...

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.

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

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.

Fourier rebinning algorithm for inverse geometry CT.

Science.gov (United States)

Mazin, Samuel R; Pele, Norbert J

2008-11-01

Inverse geometry computed tomography (IGCT) is a new type of volumetric CT geometry that employs a large array of x-ray sources opposite a smaller detector array. Volumetric coverage and high isotropic resolution produce very large data sets and therefore require a computationally efficient three-dimensional reconstruction algorithm. The purpose of this work was to adapt and evaluate a fast algorithm based on Defrise's Fourier rebinning (FORE), originally developed for positron emission tomography. The results were compared with the average of FDK reconstructions from each source row. The FORE algorithm is an order of magnitude faster than the FDK-type method for the case of 11 source rows. In the center of the field-of-view both algorithms exhibited the same resolution and noise performance. FORE exhibited some resolution loss (and less noise) in the periphery of the field-of-view. FORE appears to be a fast and reasonably accurate reconstruction method for IGCT.

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.

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

Fast, automatic, and accurate catheter reconstruction in HDR brachytherapy using an electromagnetic 3D tracking system

Energy Technology Data Exchange (ETDEWEB)

Poulin, Eric; Racine, Emmanuel; Beaulieu, Luc, E-mail: Luc.Beaulieu@phy.ulaval.ca [Département de physique, de génie physique et d’optique et Centre de recherche sur le cancer de l’Université Laval, Université Laval, Québec, Québec G1V 0A6, Canada and Département de radio-oncologie et Axe Oncologie du Centre de recherche du CHU de Québec, CHU de Québec, 11 Côte du Palais, Québec, Québec G1R 2J6 (Canada); Binnekamp, Dirk [Integrated Clinical Solutions and Marketing, Philips Healthcare, Veenpluis 4-6, Best 5680 DA (Netherlands)

2015-03-15

Purpose: In high dose rate brachytherapy (HDR-B), current catheter reconstruction protocols are relatively slow and error prone. The purpose of this technical note is to evaluate the accuracy and the robustness of an electromagnetic (EM) tracking system for automated and real-time catheter reconstruction. Methods: For this preclinical study, a total of ten catheters were inserted in gelatin phantoms with different trajectories. Catheters were reconstructed using a 18G biopsy needle, used as an EM stylet and equipped with a miniaturized sensor, and the second generation Aurora{sup ®} Planar Field Generator from Northern Digital Inc. The Aurora EM system provides position and orientation value with precisions of 0.7 mm and 0.2°, respectively. Phantoms were also scanned using a μCT (GE Healthcare) and Philips Big Bore clinical computed tomography (CT) system with a spatial resolution of 89 μm and 2 mm, respectively. Reconstructions using the EM stylet were compared to μCT and CT. To assess the robustness of the EM reconstruction, five catheters were reconstructed twice and compared. Results: Reconstruction time for one catheter was 10 s, leading to a total reconstruction time inferior to 3 min for a typical 17-catheter implant. When compared to the μCT, the mean EM tip identification error was 0.69 ± 0.29 mm while the CT error was 1.08 ± 0.67 mm. The mean 3D distance error was found to be 0.66 ± 0.33 mm and 1.08 ± 0.72 mm for the EM and CT, respectively. EM 3D catheter trajectories were found to be more accurate. A maximum difference of less than 0.6 mm was found between successive EM reconstructions. Conclusions: The EM reconstruction was found to be more accurate and precise than the conventional methods used for catheter reconstruction in HDR-B. This approach can be applied to any type of catheters and applicators.

Fast, automatic, and accurate catheter reconstruction in HDR brachytherapy using an electromagnetic 3D tracking system

International Nuclear Information System (INIS)

Poulin, Eric; Racine, Emmanuel; Beaulieu, Luc; Binnekamp, Dirk

2015-01-01

Purpose: In high dose rate brachytherapy (HDR-B), current catheter reconstruction protocols are relatively slow and error prone. The purpose of this technical note is to evaluate the accuracy and the robustness of an electromagnetic (EM) tracking system for automated and real-time catheter reconstruction. Methods: For this preclinical study, a total of ten catheters were inserted in gelatin phantoms with different trajectories. Catheters were reconstructed using a 18G biopsy needle, used as an EM stylet and equipped with a miniaturized sensor, and the second generation Aurora ® Planar Field Generator from Northern Digital Inc. The Aurora EM system provides position and orientation value with precisions of 0.7 mm and 0.2°, respectively. Phantoms were also scanned using a μCT (GE Healthcare) and Philips Big Bore clinical computed tomography (CT) system with a spatial resolution of 89 μm and 2 mm, respectively. Reconstructions using the EM stylet were compared to μCT and CT. To assess the robustness of the EM reconstruction, five catheters were reconstructed twice and compared. Results: Reconstruction time for one catheter was 10 s, leading to a total reconstruction time inferior to 3 min for a typical 17-catheter implant. When compared to the μCT, the mean EM tip identification error was 0.69 ± 0.29 mm while the CT error was 1.08 ± 0.67 mm. The mean 3D distance error was found to be 0.66 ± 0.33 mm and 1.08 ± 0.72 mm for the EM and CT, respectively. EM 3D catheter trajectories were found to be more accurate. A maximum difference of less than 0.6 mm was found between successive EM reconstructions. Conclusions: The EM reconstruction was found to be more accurate and precise than the conventional methods used for catheter reconstruction in HDR-B. This approach can be applied to any type of catheters and applicators

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.

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...

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.

Quantitative SPECT reconstruction of iodine-123 data

International Nuclear Information System (INIS)

Gilland, D.R.; Jaszczak, R.J.; Greer, K.L.; Coleman, R.E.

1991-01-01

Many clinical and research studies in nuclear medicine require quantitation of iodine-123 ( 123 I) distribution for the determination of kinetics or localization. The objective of this study was to implement several reconstruction methods designed for single-photon emission computed tomography (SPECT) using 123 I and to evaluate their performance in terms of quantitative accuracy, image artifacts, and noise. The methods consisted of four attenuation and scatter compensation schemes incorporated into both the filtered backprojection/Chang (FBP) and maximum likelihood-expectation maximization (ML-EM) reconstruction algorithms. The methods were evaluated on data acquired of a phantom containing a hot sphere of 123 I activity in a lower level background 123 I distribution and nonuniform density media. For both reconstruction algorithms, nonuniform attenuation compensation combined with either scatter subtraction or Metz filtering produced images that were quantitatively accurate to within 15% of the true value. The ML-EM algorithm demonstrated quantitative accuracy comparable to FBP and smaller relative noise magnitude for all compensation schemes

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.

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.

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.

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.

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.

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)

Accurate reconstruction in digital holographic microscopy using Fresnel dual-tree complex wavelet transform

Science.gov (United States)

Zhang, Xiaolei; Zhang, Xiangchao; Yuan, He; Zhang, Hao; Xu, Min

2018-02-01

Digital holography is a promising measurement method in the fields of bio-medicine and micro-electronics. But the captured images of digital holography are severely polluted by the speckle noise because of optical scattering and diffraction. Via analyzing the properties of Fresnel diffraction and the topographies of micro-structures, a novel reconstruction method based on the dual-tree complex wavelet transform (DT-CWT) is proposed. This algorithm is shiftinvariant and capable of obtaining sparse representations for the diffracted signals of salient features, thus it is well suited for multiresolution processing of the interferometric holograms of directional morphologies. An explicit representation of orthogonal Fresnel DT-CWT bases and a specific filtering method are developed. This method can effectively remove the speckle noise without destroying the salient features. Finally, the proposed reconstruction method is compared with the conventional Fresnel diffraction integration and Fresnel wavelet transform with compressive sensing methods to validate its remarkable superiority on the aspects of topography reconstruction and speckle removal.

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

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)

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.

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...

Development of regularized expectation maximization algorithms for fan-beam SPECT data

International Nuclear Information System (INIS)

Kim, Soo Mee; Lee, Jae Sung; Lee, Dong Soo; Lee, Soo Jin; Kim, Kyeong Min

2005-01-01

SPECT using a fan-beam collimator improves spatial resolution and sensitivity. For the reconstruction from fan-beam projections, it is necessary to implement direct fan-beam reconstruction methods without transforming the data into the parallel geometry. In this study, various fan-beam reconstruction algorithms were implemented and their performances were compared. The projector for fan-beam SPECT was implemented using a ray-tracing method. The direct reconstruction algorithms implemented for fan-beam projection data were FBP (filtered backprojection), EM (expectation maximization), OS-EM (ordered subsets EM) and MAP-EM OSL (maximum a posteriori EM using the one-step late method) with membrane and thin-plate models as priors. For comparison, the fan-beam projection data were also rebinned into the parallel data using various interpolation methods, such as the nearest neighbor, bilinear and bicubic interpolations, and reconstructed using the conventional EM algorithm for parallel data. Noiseless and noisy projection data from the digital Hoffman brain and Shepp/Logan phantoms were reconstructed using the above algorithms. The reconstructed images were compared in terms of a percent error metric. For the fan-beam data with Poisson noise, the MAP-EM OSL algorithm with the thin-plate prior showed the best result in both percent error and stability. Bilinear interpolation was the most effective method for rebinning from the fan-beam to parallel geometry when the accuracy and computation load were considered. Direct fan-beam EM reconstructions were more accurate than the standard EM reconstructions obtained from rebinned parallel data. Direct fan-beam reconstruction algorithms were implemented, which provided significantly improved reconstructions

Optimization of extracranial stereotactic radiation therapy of small lung lesions using accurate dose calculation algorithms

International Nuclear Information System (INIS)

Dobler, Barbara; Walter, Cornelia; Knopf, Antje; Fabri, Daniella; Loeschel, Rainer; Polednik, Martin; Schneider, Frank; Wenz, Frederik; Lohr, Frank

2006-01-01

The aim of this study was to compare and to validate different dose calculation algorithms for the use in radiation therapy of small lung lesions and to optimize the treatment planning using accurate dose calculation algorithms. A 9-field conformal treatment plan was generated on an inhomogeneous phantom with lung mimics and a soft tissue equivalent insert, mimicking a lung tumor. The dose distribution was calculated with the Pencil Beam and Collapsed Cone algorithms implemented in Masterplan (Nucletron) and the Monte Carlo system XVMC and validated using Gafchromic EBT films. Differences in dose distribution were evaluated. The plans were then optimized by adding segments to the outer shell of the target in order to increase the dose near the interface to the lung. The Pencil Beam algorithm overestimated the dose by up to 15% compared to the measurements. Collapsed Cone and Monte Carlo predicted the dose more accurately with a maximum difference of -8% and -3% respectively compared to the film. Plan optimization by adding small segments to the peripheral parts of the target, creating a 2-step fluence modulation, allowed to increase target coverage and homogeneity as compared to the uncorrected 9 field plan. The use of forward 2-step fluence modulation in radiotherapy of small lung lesions allows the improvement of tumor coverage and dose homogeneity as compared to non-modulated treatment plans and may thus help to increase the local tumor control probability. While the Collapsed Cone algorithm is closer to measurements than the Pencil Beam algorithm, both algorithms are limited at tissue/lung interfaces, leaving Monte-Carlo the most accurate algorithm for dose prediction

Image Reconstruction. Chapter 13

Energy Technology Data Exchange (ETDEWEB)

Nuyts, J. [Department of Nuclear Medicine and Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven (Belgium); Matej, S. [Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA (United States)

2014-12-15

This chapter discusses how 2‑D or 3‑D images of tracer distribution can be reconstructed from a series of so-called projection images acquired with a gamma camera or a positron emission tomography (PET) system [13.1]. This is often called an ‘inverse problem’. The reconstruction is the inverse of the acquisition. The reconstruction is called an inverse problem because making software to compute the true tracer distribution from the acquired data turns out to be more difficult than the ‘forward’ direction, i.e. making software to simulate the acquisition. There are basically two approaches to image reconstruction: analytical reconstruction and iterative reconstruction. The analytical approach is based on mathematical inversion, yielding efficient, non-iterative reconstruction algorithms. In the iterative approach, the reconstruction problem is reduced to computing a finite number of image values from a finite number of measurements. That simplification enables the use of iterative instead of mathematical inversion. Iterative inversion tends to require more computer power, but it can cope with more complex (and hopefully more accurate) models of the acquisition process.

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.

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.

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.

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.

Optical properties reconstruction using the adjoint method based on the radiative transfer equation

Science.gov (United States)

Addoum, Ahmad; Farges, Olivier; Asllanaj, Fatmir

2018-01-01

An efficient algorithm is proposed to reconstruct the spatial distribution of optical properties in heterogeneous media like biological tissues. The light transport through such media is accurately described by the radiative transfer equation in the frequency-domain. The adjoint method is used to efficiently compute the objective function gradient with respect to optical parameters. Numerical tests show that the algorithm is accurate and robust to retrieve simultaneously the absorption μa and scattering μs coefficients for lowly and highly absorbing medium. Moreover, the simultaneous reconstruction of μs and the anisotropy factor g of the Henyey-Greenstein phase function is achieved with a reasonable accuracy. The main novelty in this work is the reconstruction of g which might open the possibility to image this parameter in tissues as an additional contrast agent in optical tomography.

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

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)

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)

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)

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.)

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

BPF-type region-of-interest reconstruction for parallel translational computed tomography.

Science.gov (United States)

Wu, Weiwen; Yu, Hengyong; Wang, Shaoyu; Liu, Fenglin

2017-01-01

The objective of this study is to present and test a new ultra-low-cost linear scan based tomography architecture. Similar to linear tomosynthesis, the source and detector are translated in opposite directions and the data acquisition system targets on a region-of-interest (ROI) to acquire data for image reconstruction. This kind of tomographic architecture was named parallel translational computed tomography (PTCT). In previous studies, filtered backprojection (FBP)-type algorithms were developed to reconstruct images from PTCT. However, the reconstructed ROI images from truncated projections have severe truncation artefact. In order to overcome this limitation, we in this study proposed two backprojection filtering (BPF)-type algorithms named MP-BPF and MZ-BPF to reconstruct ROI images from truncated PTCT data. A weight function is constructed to deal with data redundancy for multi-linear translations modes. Extensive numerical simulations are performed to evaluate the proposed MP-BPF and MZ-BPF algorithms for PTCT in fan-beam geometry. Qualitative and quantitative results demonstrate that the proposed BPF-type algorithms cannot only more accurately reconstruct ROI images from truncated projections but also generate high-quality images for the entire image support in some circumstances.

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)

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.

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.

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...

$xy$ Position Reconstruction in DarkSide-50

Energy Technology Data Exchange (ETDEWEB)

Brodsky, Jason Philip [Princeton Univ., NJ (United States)

2015-01-01

The DarkSide-50 experiment seeks to directly detect dark matter in a liquid argon time projection chamber. In this dissertation, I present an algorithm of my design that determines the position of particle interactions with the liquid argon. This position reconstruction algorithm will be used by DarkSide-50 to reject backgrounds, particularly backgrounds from radioactive elements on the detector surface. The position reconstruction algorithm functions by constructing light response functions (LRFs) that map locations in the detector to the expected distribution of signal in DarkSide-50's 38 photomultiplier tubes. Accurate LRFs cannot be produced by simulations of DarkSide-50's optics because such simulations are known to be awed. Instead, this algorithm constructs LRFs using an iterative process driven by data. Initial, awed LRFs are produced using simulated events but then used to produce new LRFs from data events. Multiple generations of LRFs are created from data with each generation driven to better satisfy a known feature of the detector: the dominant argon-39 background is uniformly distributed. I also discuss a method of discriminating against surface background as an alternative to the common approach of ducialization. This method considers the di erence in goodnessof- t between the best- t reconstructed position and the best- t position at the detector's surface. I conclude by presenting results on the performance and validity of this algorithm, including some discussion of reconstruction errors.

Experimental reconstruction of a highly reflecting fiber Bragg grating by using spectral regularization and inverse scattering.

Science.gov (United States)

Rosenthal, Amir; Horowitz, Moshe; Kieckbusch, Sven; Brinkmeyer, Ernst

2007-10-01

We demonstrate experimentally, for the first time to our knowledge, a reconstruction of a highly reflecting fiber Bragg grating from its complex reflection spectrum by using a regularization algorithm. The regularization method is based on correcting the measured reflection spectrum at the Bragg zone frequencies and enables the reconstruction of the grating profile using the integral-layer-peeling algorithm. A grating with an approximately uniform profile and with a maximum reflectivity of 99.98% was accurately reconstructed by measuring only its complex reflection spectrum.

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.

Accurate reconstruction of hyperspectral images from compressive sensing measurements

Science.gov (United States)

Greer, John B.; Flake, J. C.

2013-05-01

The emerging field of Compressive Sensing (CS) provides a new way to capture data by shifting the heaviest burden of data collection from the sensor to the computer on the user-end. This new means of sensing requires fewer measurements for a given amount of information than traditional sensors. We investigate the efficacy of CS for capturing HyperSpectral Imagery (HSI) remotely. We also introduce a new family of algorithms for constructing HSI from CS measurements with Split Bregman Iteration [Goldstein and Osher,2009]. These algorithms combine spatial Total Variation (TV) with smoothing in the spectral dimension. We examine models for three different CS sensors: the Coded Aperture Snapshot Spectral Imager-Single Disperser (CASSI-SD) [Wagadarikar et al.,2008] and Dual Disperser (CASSI-DD) [Gehm et al.,2007] cameras, and a hypothetical random sensing model closer to CS theory, but not necessarily implementable with existing technology. We simulate the capture of remotely sensed images by applying the sensor forward models to well-known HSI scenes - an AVIRIS image of Cuprite, Nevada and the HYMAP Urban image. To measure accuracy of the CS models, we compare the scenes constructed with our new algorithm to the original AVIRIS and HYMAP cubes. The results demonstrate the possibility of accurately sensing HSI remotely with significantly fewer measurements than standard hyperspectral cameras.

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

Fast and Easy 3D Reconstruction with the Help of Geometric Constraints and Genetic Algorithms

Science.gov (United States)

Annich, Afafe; El Abderrahmani, Abdellatif; Satori, Khalid

2017-09-01

The purpose of the work presented in this paper is to describe new method of 3D reconstruction from one or more uncalibrated images. This method is based on two important concepts: geometric constraints and genetic algorithms (GAs). At first, we are going to discuss the combination between bundle adjustment and GAs that we have proposed in order to improve 3D reconstruction efficiency and success. We used GAs in order to improve fitness quality of initial values that are used in the optimization problem. It will increase surely convergence rate. Extracted geometric constraints are used first to obtain an estimated value of focal length that helps us in the initialization step. Matching homologous points and constraints is used to estimate the 3D model. In fact, our new method gives us a lot of advantages: reducing the estimated parameter number in optimization step, decreasing used image number, winning time and stabilizing good quality of 3D results. At the end, without any prior information about our 3D scene, we obtain an accurate calibration of the cameras, and a realistic 3D model that strictly respects the geometric constraints defined before in an easy way. Various data and examples will be used to highlight the efficiency and competitiveness of our present approach.

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.)

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.

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.

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

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

MREIT experiments with 200 µA injected currents: a feasibility study using two reconstruction algorithms, SMM and harmonic BZ

International Nuclear Information System (INIS)

Arpinar, V E; Muftuler, L T; Hamamura, M J; Degirmenci, E

2012-01-01

Magnetic resonance electrical impedance tomography (MREIT) is a technique that produces images of conductivity in tissues and phantoms. In this technique, electrical currents are applied to an object and the resulting magnetic flux density is measured using magnetic resonance imaging (MRI) and the conductivity distribution is reconstructed using these MRI data. Currently, the technique is used in research environments, primarily studying phantoms and animals. In order to translate MREIT to clinical applications, strict safety standards need to be established, especially for safe current limits. However, there are currently no standards for safe current limits specific to MREIT. Until such standards are established, human MREIT applications need to conform to existing electrical safety standards in medical instrumentation, such as IEC601. This protocol limits patient auxiliary currents to 100 µA for low frequencies. However, published MREIT studies have utilized currents 10–400 times larger than this limit, bringing into question whether the clinical applications of MREIT are attainable under current standards. In this study, we investigated the feasibility of MREIT to accurately reconstruct the relative conductivity of a simple agarose phantom using 200 µA total injected current and tested the performance of two MREIT reconstruction algorithms. These reconstruction algorithms used are the iterative sensitivity matrix method (SMM) by Ider and Birgul (1998 Elektrik 6 215–25) with Tikhonov regularization and the harmonic B Z proposed by Oh et al (2003 Magn. Reason. Med. 50 875–8). The reconstruction techniques were tested at both 200 µA and 5 mA injected currents to investigate their noise sensitivity at low and high current conditions. It should be noted that 200 µA total injected current into a cylindrical phantom generates only 14.7 µA current in imaging slice. Similarly, 5 mA total injected current results in 367 µA in imaging slice. Total acquisition

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.

SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

International Nuclear Information System (INIS)

Noid, G; Chen, G; Tai, A; Li, X

2014-01-01

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance

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

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

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

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

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.

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.)

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.)

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

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.

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)

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.

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

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

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

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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.

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.

Reconstructing random media

International Nuclear Information System (INIS)

Yeong, C.L.; Torquato, S.

1998-01-01

We formulate a procedure to reconstruct the structure of general random heterogeneous media from limited morphological information by extending the methodology of Rintoul and Torquato [J. Colloid Interface Sci. 186, 467 (1997)] developed for dispersions. The procedure has the advantages that it is simple to implement and generally applicable to multidimensional, multiphase, and anisotropic structures. Furthermore, an extremely useful feature is that it can incorporate any type and number of correlation functions in order to provide as much morphological information as is necessary for accurate reconstruction. We consider a variety of one- and two-dimensional reconstructions, including periodic and random arrays of rods, various distribution of disks, Debye random media, and a Fontainebleau sandstone sample. We also use our algorithm to construct heterogeneous media from specified hypothetical correlation functions, including an exponentially damped, oscillating function as well as physically unrealizable ones. copyright 1998 The American Physical Society

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.

Research of cartographer laser SLAM algorithm

Science.gov (United States)

Xu, Bo; Liu, Zhengjun; Fu, Yiran; Zhang, Changsai

2017-11-01

As the indoor is a relatively closed and small space, total station, GPS, close-range photogrammetry technology is difficult to achieve fast and accurate indoor three-dimensional space reconstruction task. LIDAR SLAM technology does not rely on the external environment a priori knowledge, only use their own portable lidar, IMU, odometer and other sensors to establish an independent environment map, a good solution to this problem. This paper analyzes the Google Cartographer laser SLAM algorithm from the point cloud matching and closed loop detection. Finally, the algorithm is presented in the 3D visualization tool RViz from the data acquisition and processing to create the environment map, complete the SLAM technology and realize the process of indoor threedimensional space reconstruction

An accurate algorithm to calculate the Hurst exponent of self-similar processes

International Nuclear Information System (INIS)

Fernández-Martínez, M.; Sánchez-Granero, M.A.; Trinidad Segovia, J.E.; Román-Sánchez, I.M.

2014-01-01

In this paper, we introduce a new approach which generalizes the GM2 algorithm (introduced in Sánchez-Granero et al. (2008) [52]) as well as fractal dimension algorithms (FD1, FD2 and FD3) (first appeared in Sánchez-Granero et al. (2012) [51]), providing an accurate algorithm to calculate the Hurst exponent of self-similar processes. We prove that this algorithm performs properly in the case of short time series when fractional Brownian motions and Lévy stable motions are considered. We conclude the paper with a dynamic study of the Hurst exponent evolution in the S and P500 index stocks. - Highlights: • We provide a new approach to properly calculate the Hurst exponent. • This generalizes FD algorithms and GM2, introduced previously by the authors. • This method (FD4) results especially appropriate for short time series. • FD4 may be used in both unifractal and multifractal contexts. • As an empirical application, we show that S and P500 stocks improved their efficiency

An accurate algorithm to calculate the Hurst exponent of self-similar processes

Energy Technology Data Exchange (ETDEWEB)

Fernández-Martínez, M., E-mail: fmm124@ual.es [Department of Mathematics, Faculty of Science, Universidad de Almería, 04120 Almería (Spain); Sánchez-Granero, M.A., E-mail: misanche@ual.es [Department of Mathematics, Faculty of Science, Universidad de Almería, 04120 Almería (Spain); Trinidad Segovia, J.E., E-mail: jetrini@ual.es [Department of Accounting and Finance, Faculty of Economics and Business, Universidad de Almería, 04120 Almería (Spain); Román-Sánchez, I.M., E-mail: iroman@ual.es [Department of Accounting and Finance, Faculty of Economics and Business, Universidad de Almería, 04120 Almería (Spain)

2014-06-27

In this paper, we introduce a new approach which generalizes the GM2 algorithm (introduced in Sánchez-Granero et al. (2008) [52]) as well as fractal dimension algorithms (FD1, FD2 and FD3) (first appeared in Sánchez-Granero et al. (2012) [51]), providing an accurate algorithm to calculate the Hurst exponent of self-similar processes. We prove that this algorithm performs properly in the case of short time series when fractional Brownian motions and Lévy stable motions are considered. We conclude the paper with a dynamic study of the Hurst exponent evolution in the S and P500 index stocks. - Highlights: • We provide a new approach to properly calculate the Hurst exponent. • This generalizes FD algorithms and GM2, introduced previously by the authors. • This method (FD4) results especially appropriate for short time series. • FD4 may be used in both unifractal and multifractal contexts. • As an empirical application, we show that S and P500 stocks improved their efficiency.

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

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.

Evaluating low pass filters on SPECT reconstructed cardiac orientation estimation

Science.gov (United States)

Dwivedi, Shekhar

2009-02-01

Low pass filters can affect the quality of clinical SPECT images by smoothing. Appropriate filter and parameter selection leads to optimum smoothing that leads to a better quantification followed by correct diagnosis and accurate interpretation by the physician. This study aims at evaluating the low pass filters on SPECT reconstruction algorithms. Criteria for evaluating the filters are estimating the SPECT reconstructed cardiac azimuth and elevation angle. Low pass filters studied are butterworth, gaussian, hamming, hanning and parzen. Experiments are conducted using three reconstruction algorithms, FBP (filtered back projection), MLEM (maximum likelihood expectation maximization) and OSEM (ordered subsets expectation maximization), on four gated cardiac patient projections (two patients with stress and rest projections). Each filter is applied with varying cutoff and order for each reconstruction algorithm (only butterworth used for MLEM and OSEM). The azimuth and elevation angles are calculated from the reconstructed volume and the variation observed in the angles with varying filter parameters is reported. Our results demonstrate that behavior of hamming, hanning and parzen filter (used with FBP) with varying cutoff is similar for all the datasets. Butterworth filter (cutoff > 0.4) behaves in a similar fashion for all the datasets using all the algorithms whereas with OSEM for a cutoff < 0.4, it fails to generate cardiac orientation due to oversmoothing, and gives an unstable response with FBP and MLEM. This study on evaluating effect of low pass filter cutoff and order on cardiac orientation using three different reconstruction algorithms provides an interesting insight into optimal selection of filter parameters.

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

Novel Low Cost 3D Surface Model Reconstruction System for Plant Phenotyping

Directory of Open Access Journals (Sweden)

Suxing Liu

2017-09-01

Full Text Available Accurate high-resolution three-dimensional (3D models are essential for a non-invasive analysis of phenotypic characteristics of plants. Previous limitations in 3D computer vision algorithms have led to a reliance on volumetric methods or expensive hardware to record plant structure. We present an image-based 3D plant reconstruction system that can be achieved by using a single camera and a rotation stand. Our method is based on the structure from motion method, with a SIFT image feature descriptor. In order to improve the quality of the 3D models, we segmented the plant objects based on the PlantCV platform. We also deducted the optimal number of images needed for reconstructing a high-quality model. Experiments showed that an accurate 3D model of the plant was successfully could be reconstructed by our approach. This 3D surface model reconstruction system provides a simple and accurate computational platform for non-destructive, plant phenotyping.

Validation of the Gate simulation platform in single photon emission computed tomography and application to the development of a complete 3-dimensional reconstruction algorithm; Validation de la plate-forme de simulation GATE en tomographie a emission monophotonique et application au developpement d'un algorithme de reconstruction 3D complete

Energy Technology Data Exchange (ETDEWEB)

Lazaro, D

2003-10-01

Monte Carlo simulations are currently considered in nuclear medical imaging as a powerful tool to design and optimize detection systems, and also to assess reconstruction algorithms and correction methods for degrading physical effects. Among the many simulators available, none of them is considered as a standard in nuclear medical imaging: this fact has motivated the development of a new generic Monte Carlo simulation platform (GATE), based on GEANT4 and dedicated to SPECT/PET (single photo emission computed tomography / positron emission tomography) applications. We participated during this thesis to the development of the GATE platform within an international collaboration. GATE was validated in SPECT by modeling two gamma cameras characterized by a different geometry, one dedicated to small animal imaging and the other used in a clinical context (Philips AXIS), and by comparing the results obtained with GATE simulations with experimental data. The simulation results reproduce accurately the measured performances of both gamma cameras. The GATE platform was then used to develop a new 3-dimensional reconstruction method: F3DMC (fully 3-dimension Monte-Carlo) which consists in computing with Monte Carlo simulation the transition matrix used in an iterative reconstruction algorithm (in this case, ML-EM), including within the transition matrix the main physical effects degrading the image formation process. The results obtained with the F3DMC method were compared to the results obtained with three other more conventional methods (FBP, MLEM, MLEMC) for different phantoms. The results of this study show that F3DMC allows to improve the reconstruction efficiency, the spatial resolution and the signal to noise ratio with a satisfactory quantification of the images. These results should be confirmed by performing clinical experiments and open the door to a unified reconstruction method, which could be applied in SPECT but also in PET. (author)

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

TSaT-MUSIC: a novel algorithm for rapid and accurate ultrasonic 3D localization

Science.gov (United States)

Mizutani, Kyohei; Ito, Toshio; Sugimoto, Masanori; Hashizume, Hiromichi

2011-12-01

We describe a fast and accurate indoor localization technique using the multiple signal classification (MUSIC) algorithm. The MUSIC algorithm is known as a high-resolution method for estimating directions of arrival (DOAs) or propagation delays. A critical problem in using the MUSIC algorithm for localization is its computational complexity. Therefore, we devised a novel algorithm called Time Space additional Temporal-MUSIC, which can rapidly and simultaneously identify DOAs and delays of mul-ticarrier ultrasonic waves from transmitters. Computer simulations have proved that the computation time of the proposed algorithm is almost constant in spite of increasing numbers of incoming waves and is faster than that of existing methods based on the MUSIC algorithm. The robustness of the proposed algorithm is discussed through simulations. Experiments in real environments showed that the standard deviation of position estimations in 3D space is less than 10 mm, which is satisfactory for indoor localization.

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.

Accuracy improvement of CT reconstruction using tree-structured filter bank

International Nuclear Information System (INIS)

Ueda, Kazuhiro; Morimoto, Hiroaki; Morikawa, Yoshitaka; Murakami, Junichi

2009-01-01

Accuracy improvement of 'CT reconstruction algorithm using TSFB (Tree-Structured Filter Bank)' that is high-speed CT reconstruction algorithm, was proposed. TSFB method could largely reduce the amount of computation in comparison with the CB (Convolution Backprojection) method, but it was the problem that an artifact occurred in a reconstruction image since reconstruction was performed with disregard to a signal out of the reconstruction domain in stage processing. Also the whole band filter being the component of a two-dimensional synthesis filter was IIR filter and then an artifact occurred at the end of the reconstruction image. In order to suppress these artifacts the proposed method enlarged the processing range by the TSFB method in the domain outside by the width control of the specimen line and line addition to the reconstruction domain outside. And, furthermore, to avoid increase of the amount of computation, the algorithm was proposed such as to decide the needed processing range depending on the number of steps processing with the TSFB and the degree of incline of filter, and then update the position and width of the specimen line to process the needed range. According to the simulation to realize a high-speed and highly accurate CT reconstruction in this way, the quality of the reconstruction image of the proposed method was improved in comparison with the TSFB method and got the same result with the CB method. (T. Tanaka)

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.

Efficient statistically accurate algorithms for the Fokker-Planck equation in large dimensions

Science.gov (United States)

Chen, Nan; Majda, Andrew J.

2018-02-01

Solving the Fokker-Planck equation for high-dimensional complex turbulent dynamical systems is an important and practical issue. However, most traditional methods suffer from the curse of dimensionality and have difficulties in capturing the fat tailed highly intermittent probability density functions (PDFs) of complex systems in turbulence, neuroscience and excitable media. In this article, efficient statistically accurate algorithms are developed for solving both the transient and the equilibrium solutions of Fokker-Planck equations associated with high-dimensional nonlinear turbulent dynamical systems with conditional Gaussian structures. The algorithms involve a hybrid strategy that requires only a small number of ensembles. Here, a conditional Gaussian mixture in a high-dimensional subspace via an extremely efficient parametric method is combined with a judicious non-parametric Gaussian kernel density estimation in the remaining low-dimensional subspace. Particularly, the parametric method provides closed analytical formulae for determining the conditional Gaussian distributions in the high-dimensional subspace and is therefore computationally efficient and accurate. The full non-Gaussian PDF of the system is then given by a Gaussian mixture. Different from traditional particle methods, each conditional Gaussian distribution here covers a significant portion of the high-dimensional PDF. Therefore a small number of ensembles is sufficient to recover the full PDF, which overcomes the curse of dimensionality. Notably, the mixture distribution has significant skill in capturing the transient behavior with fat tails of the high-dimensional non-Gaussian PDFs, and this facilitates the algorithms in accurately describing the intermittency and extreme events in complex turbulent systems. It is shown in a stringent set of test problems that the method only requires an order of O (100) ensembles to successfully recover the highly non-Gaussian transient PDFs in up to 6

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.

Fourier transform profilometry (FTP) using an innovative band-pass filter for accurate 3-D surface reconstruction

Science.gov (United States)

Chen, Liang-Chia; Ho, Hsuan-Wei; Nguyen, Xuan-Loc

2010-02-01

This article presents a novel band-pass filter for Fourier transform profilometry (FTP) for accurate 3-D surface reconstruction. FTP can be employed to obtain 3-D surface profiles by one-shot images to achieve high-speed measurement. However, its measurement accuracy has been significantly influenced by the spectrum filtering process required to extract the phase information representing various surface heights. Using the commonly applied 2-D Hanning filter, the measurement errors could be up to 5-10% of the overall measuring height and it is unacceptable to various industrial application. To resolve this issue, the article proposes an elliptical band-pass filter for extracting the spectral region possessing essential phase information for reconstructing accurate 3-D surface profiles. The elliptical band-pass filter was developed and optimized to reconstruct 3-D surface models with improved measurement accuracy. Some experimental results verify that the accuracy can be effectively enhanced by using the elliptical filter. The accuracy improvement of 44.1% and 30.4% can be achieved in 3-D and sphericity measurement, respectively, when the elliptical filter replaces the traditional filter as the band-pass filtering method. Employing the developed method, the maximum measured error can be kept within 3.3% of the overall measuring range.

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.

An algorithm for selecting the most accurate protocol for contact angle measurement by drop shape analysis.

Science.gov (United States)

Xu, Z N

2014-12-01

In this study, an error analysis is performed to study real water drop images and the corresponding numerically generated water drop profiles for three widely used static contact angle algorithms: the circle- and ellipse-fitting algorithms and the axisymmetric drop shape analysis-profile (ADSA-P) algorithm. The results demonstrate the accuracy of the numerically generated drop profiles based on the Laplace equation. A significant number of water drop profiles with different volumes, contact angles, and noise levels are generated, and the influences of the three factors on the accuracies of the three algorithms are systematically investigated. The results reveal that the above-mentioned three algorithms are complementary. In fact, the circle- and ellipse-fitting algorithms show low errors and are highly resistant to noise for water drops with small/medium volumes and contact angles, while for water drop with large volumes and contact angles just the ADSA-P algorithm can meet accuracy requirement. However, this algorithm introduces significant errors in the case of small volumes and contact angles because of its high sensitivity to noise. The critical water drop volumes of the circle- and ellipse-fitting algorithms corresponding to a certain contact angle error are obtained through a significant amount of computation. To improve the precision of the static contact angle measurement, a more accurate algorithm based on a combination of the three algorithms is proposed. Following a systematic investigation, the algorithm selection rule is described in detail, while maintaining the advantages of the three algorithms and overcoming their deficiencies. In general, static contact angles over the entire hydrophobicity range can be accurately evaluated using the proposed algorithm. The ease of erroneous judgment in static contact angle measurements is avoided. The proposed algorithm is validated by a static contact angle evaluation of real and numerically generated water drop

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.

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.

TVR-DART: A More Robust Algorithm for Discrete Tomography From Limited Projection Data With Automated Gray Value Estimation.

Science.gov (United States)

Xiaodong Zhuge; Palenstijn, Willem Jan; Batenburg, Kees Joost

2016-01-01

In this paper, we present a novel iterative reconstruction algorithm for discrete tomography (DT) named total variation regularized discrete algebraic reconstruction technique (TVR-DART) with automated gray value estimation. This algorithm is more robust and automated than the original DART algorithm, and is aimed at imaging of objects consisting of only a few different material compositions, each corresponding to a different gray value in the reconstruction. By exploiting two types of prior knowledge of the scanned object simultaneously, TVR-DART solves the discrete reconstruction problem within an optimization framework inspired by compressive sensing to steer the current reconstruction toward a solution with the specified number of discrete gray values. The gray values and the thresholds are estimated as the reconstruction improves through iterations. Extensive experiments from simulated data, experimental μCT, and electron tomography data sets show that TVR-DART is capable of providing more accurate reconstruction than existing algorithms under noisy conditions from a small number of projection images and/or from a small angular range. Furthermore, the new algorithm requires less effort on parameter tuning compared with the original DART algorithm. With TVR-DART, we aim to provide the tomography society with an easy-to-use and robust algorithm for DT.

Tools for Accurate and Efficient Analysis of Complex Evolutionary Mechanisms in Microbial Genomes. Final Report

Energy Technology Data Exchange (ETDEWEB)

Nakhleh, Luay

2014-03-12

I proposed to develop computationally efficient tools for accurate detection and reconstruction of microbes' complex evolutionary mechanisms, thus enabling rapid and accurate annotation, analysis and understanding of their genomes. To achieve this goal, I proposed to address three aspects. (1) Mathematical modeling. A major challenge facing the accurate detection of HGT is that of distinguishing between these two events on the one hand and other events that have similar "effects." I proposed to develop a novel mathematical approach for distinguishing among these events. Further, I proposed to develop a set of novel optimization criteria for the evolutionary analysis of microbial genomes in the presence of these complex evolutionary events. (2) Algorithm design. In this aspect of the project, I proposed to develop an array of e cient and accurate algorithms for analyzing microbial genomes based on the formulated optimization criteria. Further, I proposed to test the viability of the criteria and the accuracy of the algorithms in an experimental setting using both synthetic as well as biological data. (3) Software development. I proposed the nal outcome to be a suite of software tools which implements the mathematical models as well as the algorithms developed.

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

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.

Bad Clade Deletion Supertrees: A Fast and Accurate Supertree Algorithm.

Science.gov (United States)

Fleischauer, Markus; Böcker, Sebastian

2017-09-01

Supertree methods merge a set of overlapping phylogenetic trees into a supertree containing all taxa of the input trees. The challenge in supertree reconstruction is the way of dealing with conflicting information in the input trees. Many different algorithms for different objective functions have been suggested to resolve these conflicts. In particular, there exist methods based on encoding the source trees in a matrix, where the supertree is constructed applying a local search heuristic to optimize the respective objective function. We present a novel heuristic supertree algorithm called Bad Clade Deletion (BCD) supertrees. It uses minimum cuts to delete a locally minimal number of columns from such a matrix representation so that it is compatible. This is the complement problem to Matrix Representation with Compatibility (Maximum Split Fit). Our algorithm has guaranteed polynomial worst-case running time and performs swiftly in practice. Different from local search heuristics, it guarantees to return the directed perfect phylogeny for the input matrix, corresponding to the parent tree of the input trees, if one exists. Comparing supertrees to model trees for simulated data, BCD shows a better accuracy (F1 score) than the state-of-the-art algorithms SuperFine (up to 3%) and Matrix Representation with Parsimony (up to 7%); at the same time, BCD is up to 7 times faster than SuperFine, and up to 600 times faster than Matrix Representation with Parsimony. Finally, using the BCD supertree as a starting tree for a combined Maximum Likelihood analysis using RAxML, we reach significantly improved accuracy (1% higher F1 score) and running time (1.7-fold speedup). © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography

Energy Technology Data Exchange (ETDEWEB)

Okariz, Ana, E-mail: ana.okariz@ehu.es [eMERG, Fisika Aplikatua I Saila, Faculty of Engineering, University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao (Spain); Guraya, Teresa [eMERG, Departamento de Ingeniería Minera y Metalúrgica y Ciencia de los Materiales, Faculty of Engineering, University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao (Spain); Iturrondobeitia, Maider [eMERG, Departamento de Expresión Gráfica y Proyectos de Ingeniería, Faculty of Engineering, University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 3, 48013 Bilbao (Spain); Ibarretxe, Julen [eMERG, Fisika Aplikatua I Saila, Faculty of Engineering,University of the Basque Country, UPV/EHU, Rafael Moreno “Pitxitxi” Pasealekua 2, 48013 Bilbao (Spain)

2017-02-15

The SIRT (Simultaneous Iterative Reconstruction Technique) algorithm is commonly used in Electron Tomography to calculate the original volume of the sample from noisy images, but the results provided by this iterative procedure are strongly dependent on the specific implementation of the algorithm, as well as on the number of iterations employed for the reconstruction. In this work, a methodology for selecting the iteration number of the SIRT reconstruction that provides the most accurate segmentation is proposed. The methodology is based on the statistical analysis of the intensity profiles at the edge of the objects in the reconstructed volume. A phantom which resembles a a carbon black aggregate has been created to validate the methodology and the SIRT implementations of two free software packages (TOMOJ and TOMO3D) have been used. - Highlights: • The non uniformity of the resolution in electron tomography reconstructions has been demonstrated. • An overall resolution for the evaluation of the quality of electron tomography reconstructions has been defined. • Parameters for estimating an overall resolution across the reconstructed volume have been proposed. • The overall resolution of the reconstructions of a phantom has been estimated from the probability density functions. • It has been proven that reconstructions with the best overall resolutions have provided the most accurate segmentations.

A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography

International Nuclear Information System (INIS)

Okariz, Ana; Guraya, Teresa; Iturrondobeitia, Maider; Ibarretxe, Julen

2017-01-01

The SIRT (Simultaneous Iterative Reconstruction Technique) algorithm is commonly used in Electron Tomography to calculate the original volume of the sample from noisy images, but the results provided by this iterative procedure are strongly dependent on the specific implementation of the algorithm, as well as on the number of iterations employed for the reconstruction. In this work, a methodology for selecting the iteration number of the SIRT reconstruction that provides the most accurate segmentation is proposed. The methodology is based on the statistical analysis of the intensity profiles at the edge of the objects in the reconstructed volume. A phantom which resembles a a carbon black aggregate has been created to validate the methodology and the SIRT implementations of two free software packages (TOMOJ and TOMO3D) have been used. - Highlights: • The non uniformity of the resolution in electron tomography reconstructions has been demonstrated. • An overall resolution for the evaluation of the quality of electron tomography reconstructions has been defined. • Parameters for estimating an overall resolution across the reconstructed volume have been proposed. • The overall resolution of the reconstructions of a phantom has been estimated from the probability density functions. • It has been proven that reconstructions with the best overall resolutions have provided the most accurate segmentations.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

Science.gov (United States)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

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)

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.

A new accurate curvature matching and optimal tool based five-axis machining algorithm

International Nuclear Information System (INIS)

Lin, Than; Lee, Jae Woo; Bohez, Erik L. J.

2009-01-01

Free-form surfaces are widely used in CAD systems to describe the part surface. Today, the most advanced machining of free from surfaces is done in five-axis machining using a flat end mill cutter. However, five-axis machining requires complex algorithms for gouging avoidance, collision detection and powerful computer-aided manufacturing (CAM) systems to support various operations. An accurate and efficient method is proposed for five-axis CNC machining of free-form surfaces. The proposed algorithm selects the best tool and plans the tool path autonomously using curvature matching and integrated inverse kinematics of the machine tool. The new algorithm uses the real cutter contact tool path generated by the inverse kinematics and not the linearized piecewise real cutter location tool path

Validation of the Gate simulation platform in single photon emission computed tomography and application to the development of a complete 3-dimensional reconstruction algorithm

International Nuclear Information System (INIS)

Lazaro, D.

2003-10-01

Monte Carlo simulations are currently considered in nuclear medical imaging as a powerful tool to design and optimize detection systems, and also to assess reconstruction algorithms and correction methods for degrading physical effects. Among the many simulators available, none of them is considered as a standard in nuclear medical imaging: this fact has motivated the development of a new generic Monte Carlo simulation platform (GATE), based on GEANT4 and dedicated to SPECT/PET (single photo emission computed tomography / positron emission tomography) applications. We participated during this thesis to the development of the GATE platform within an international collaboration. GATE was validated in SPECT by modeling two gamma cameras characterized by a different geometry, one dedicated to small animal imaging and the other used in a clinical context (Philips AXIS), and by comparing the results obtained with GATE simulations with experimental data. The simulation results reproduce accurately the measured performances of both gamma cameras. The GATE platform was then used to develop a new 3-dimensional reconstruction method: F3DMC (fully 3-dimension Monte-Carlo) which consists in computing with Monte Carlo simulation the transition matrix used in an iterative reconstruction algorithm (in this case, ML-EM), including within the transition matrix the main physical effects degrading the image formation process. The results obtained with the F3DMC method were compared to the results obtained with three other more conventional methods (FBP, MLEM, MLEMC) for different phantoms. The results of this study show that F3DMC allows to improve the reconstruction efficiency, the spatial resolution and the signal to noise ratio with a satisfactory quantification of the images. These results should be confirmed by performing clinical experiments and open the door to a unified reconstruction method, which could be applied in SPECT but also in PET. (author)

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.

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.

Robustness of the ATLAS pixel clustering neural network algorithm

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration

2016-01-01

Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. The algorithms depend heavily on accurate estimation of the position of particles as they traverse the inner detector elements. An artificial neural network algorithm is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The method recovers otherwise lost tracks in dense environments where particles are separated by distances comparable to the size of the detector read-out elements. Such environments are highly relevant for LHC run 2, e.g. in searches for heavy resonances. Within the scope of run 2 track reconstruction performance and upgrades, the robustness of the neural network algorithm will be presented. The robustness has been studied by evaluating the stability of the algorithm’s performance under a range of variations in the pixel detector conditions.

Noniterative accurate algorithm for the exact exchange potential of density-functional theory

International Nuclear Information System (INIS)

Cinal, M.; Holas, A.

2007-01-01

An algorithm for determination of the exchange potential is constructed and tested. It represents a one-step procedure based on the equations derived by Krieger, Li, and Iafrate (KLI) [Phys. Rev. A 46, 5453 (1992)], implemented already as an iterative procedure by Kuemmel and Perdew [Phys. Rev. Lett. 90, 043004 (2003)]. Due to suitable transformation of the KLI equations, we can solve them avoiding iterations. Our algorithm is applied to the closed-shell atoms, from Be up to Kr, within the DFT exchange-only approximation. Using pseudospectral techniques for representing orbitals, we obtain extremely accurate values of total and orbital energies with errors at least four orders of magnitude smaller than known in the literature

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.

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)

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)

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.

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.

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.

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.

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)

Iterative CT reconstruction via minimizing adaptively reweighted total variation.

Science.gov (United States)

Zhu, Lei; Niu, Tianye; Petrongolo, Michael

2014-01-01

Iterative reconstruction via total variation (TV) minimization has demonstrated great successes in accurate CT imaging from under-sampled projections. When projections are further reduced, over-smoothing artifacts appear in the current reconstruction especially around the structure boundaries. We propose a practical algorithm to improve TV-minimization based CT reconstruction on very few projection data. Based on the theory of compressed sensing, the L-0 norm approach is more desirable to further reduce the projection views. To overcome the computational difficulty of the non-convex optimization of the L-0 norm, we implement an adaptive weighting scheme to approximate the solution via a series of TV minimizations for practical use in CT reconstruction. The weight on TV is initialized as uniform ones, and is automatically changed based on the gradient of the reconstructed image from the previous iteration. The iteration stops when a small difference between the weighted TV values is observed on two consecutive reconstructed images. We evaluate the proposed algorithm on both a digital phantom and a physical phantom. Using 20 equiangular projections, our method reduces reconstruction errors in the conventional TV minimization by a factor of more than 5, with improved spatial resolution. By adaptively reweighting TV in iterative CT reconstruction, we successfully further reduce the projection number for the same or better image quality.

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.

A penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography.

Science.gov (United States)

Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn

2007-01-01

Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT.

Reconstruction of Clear-PEM data with STIR

CERN Document Server

Martins, M V; Rodrigues, P; Trindade, A; Oliveira, N; Correia, M; Cordeiro, H; Ferreira, N C; Varela, J; Almeida, P

2006-01-01

The Clear-PEM scanner is a device based on planar detectors that is currently under development within the Crystal Clear Collaboration, at CERN. The basis for 3D image reconstruction in Clear-PEM is the software for tomographic image reconstruction (STIR). STIR is an open source object-oriented library that efficiently deals with the 3D positron emission tomography data sets. This library was originally designed for the traditional cylindrical scanners. In order to make its use compatible with planar scanner data, new functionalities were introduced into the library's framework. In this work, Monte Carlo simulations of the Clear-PEM scanner acquisitions were used as input for image reconstruction with the 3D OSEM algorithm available in STIR. The results presented indicate that dual plate PEM data can be accurately reconstructed using the enhanced STIR framework.

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)

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.

Cone-beam ROI reconstruction using the laplace operator

Energy Technology Data Exchange (ETDEWEB)

Dennerlein, Frank [Siemens AG, Nuernberg (Germany). Healthcare Sector

2011-07-01

A novel filtered-backprojection (FBP) algorithm for 3D reconstruction in the circular geometry is presented. This algorithm achieves data filtering in two steps. The first step is a 2D Laplace filtering of the projections, which acts locally on the data and can thus be carried out accurately even in presence of (transaxial) data truncation. In a second step, a nonlocal 2D filtering operation is applied on the outcome of step 1. First simulation studies show that our algorithm is implicitly more resistant to truncated projections than many standard FBP methods without the need to involve an explicit data extrapolation scheme. (orig.)

On the Accuracy of Ancestral Sequence Reconstruction for Ultrametric Trees with Parsimony.

Science.gov (United States)

Herbst, Lina; Fischer, Mareike

2018-04-01

We examine a mathematical question concerning the reconstruction accuracy of the Fitch algorithm for reconstructing the ancestral sequence of the most recent common ancestor given a phylogenetic tree and sequence data for all taxa under consideration. In particular, for the symmetric four-state substitution model which is also known as Jukes-Cantor model, we answer affirmatively a conjecture of Li, Steel and Zhang which states that for any ultrametric phylogenetic tree and a symmetric model, the Fitch parsimony method using all terminal taxa is more accurate, or at least as accurate, for ancestral state reconstruction than using any particular terminal taxon or any particular pair of taxa. This conjecture had so far only been answered for two-state data by Fischer and Thatte. Here, we focus on answering the biologically more relevant case with four states, which corresponds to ancestral sequence reconstruction from DNA or RNA data.

Multi-view 3D scene reconstruction using ant colony optimization techniques

International Nuclear Information System (INIS)

Chrysostomou, Dimitrios; Gasteratos, Antonios; Nalpantidis, Lazaros; Sirakoulis, Georgios C

2012-01-01

This paper presents a new method performing high-quality 3D object reconstruction of complex shapes derived from multiple, calibrated photographs of the same scene. The novelty of this research is found in two basic elements, namely: (i) a novel voxel dissimilarity measure, which accommodates the elimination of the lighting variations of the models and (ii) the use of an ant colony approach for further refinement of the final 3D models. The proposed reconstruction procedure employs a volumetric method based on a novel projection test for the production of a visual hull. While the presented algorithm shares certain aspects with the space carving algorithm, it is, nevertheless, first enhanced with the lightness compensating image comparison method, and then refined using ant colony optimization. The algorithm is fast, computationally simple and results in accurate representations of the input scenes. In addition, compared to previous publications, the particular nature of the proposed algorithm allows accurate 3D volumetric measurements under demanding lighting environmental conditions, due to the fact that it can cope with uneven light scenes, resulting from the characteristics of the voxel dissimilarity measure applied. Besides, the intelligent behavior of the ant colony framework provides the opportunity to formulate the process as a combinatorial optimization problem, which can then be solved by means of a colony of cooperating artificial ants, resulting in very promising results. The method is validated with several real datasets, along with qualitative comparisons with other state-of-the-art 3D reconstruction techniques, following the Middlebury benchmark. (paper)

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

Accurate determination of rates from non-uniformly sampled relaxation data

Energy Technology Data Exchange (ETDEWEB)

Stetz, Matthew A.; Wand, A. Joshua, E-mail: wand@upenn.edu [University of Pennsylvania Perelman School of Medicine, Johnson Research Foundation and Department of Biochemistry and Biophysics (United States)

2016-08-15

The application of non-uniform sampling (NUS) to relaxation experiments traditionally used to characterize the fast internal motion of proteins is quantitatively examined. Experimentally acquired Poisson-gap sampled data reconstructed with iterative soft thresholding are compared to regular sequentially sampled (RSS) data. Using ubiquitin as a model system, it is shown that 25 % sampling is sufficient for the determination of quantitatively accurate relaxation rates. When the sampling density is fixed at 25 %, the accuracy of rates is shown to increase sharply with the total number of sampled points until eventually converging near the inherent reproducibility of the experiment. Perhaps contrary to some expectations, it is found that accurate peak height reconstruction is not required for the determination of accurate rates. Instead, inaccuracies in rates arise from inconsistencies in reconstruction across the relaxation series that primarily manifest as a non-linearity in the recovered peak height. This indicates that the performance of an NUS relaxation experiment cannot be predicted from comparison of peak heights using a single RSS reference spectrum. The generality of these findings was assessed using three alternative reconstruction algorithms, eight different relaxation measurements, and three additional proteins that exhibit varying degrees of spectral complexity. From these data, it is revealed that non-linearity in peak height reconstruction across the relaxation series is strongly correlated with errors in NUS-derived relaxation rates. Importantly, it is shown that this correlation can be exploited to reliably predict the performance of an NUS-relaxation experiment by using three or more RSS reference planes from the relaxation series. The RSS reference time points can also serve to provide estimates of the uncertainty of the sampled intensity, which for a typical relaxation times series incurs no penalty in total acquisition time.

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.

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.

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.

Science.gov (United States)

Xu, Yaofang; Wu, Jiayi; Yin, Chang-Cheng; Mao, Youdong

2016-01-01

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.

Effects of light refraction on the accuracy of camera calibration and reconstruction in underwater motion analysis.

Science.gov (United States)