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.
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.
Overview of image reconstruction
International Nuclear Information System (INIS)
Marr, R.B.
1980-04-01
Image reconstruction (or computerized tomography, etc.) is any process whereby a function, f, on R/sup n/ is estimated from empirical data pertaining to its integrals, ∫f(x) dx, for some collection of hyperplanes of dimension k < n. The paper begins with background information on how image reconstruction problems have arisen in practice, and describes some of the application areas of past or current interest; these include radioastronomy, optics, radiology and nuclear medicine, electron microscopy, acoustical imaging, geophysical tomography, nondestructive testing, and NMR zeugmatography. Then the various reconstruction algorithms are discussed in five classes: summation, or simple back-projection; convolution, or filtered back-projection; Fourier and other functional transforms; orthogonal function series expansion; and iterative methods. Certain more technical mathematical aspects of image reconstruction are considered from the standpoint of uniqueness, consistency, and stability of solution. The paper concludes by presenting certain open problems. 73 references
May, Matthias S; Wüst, Wolfgang; Brand, Michael; Stahl, Christian; Allmendinger, Thomas; Schmidt, Bernhard; Uder, Michael; Lell, Michael M
2011-07-01
We sought to evaluate the image quality of iterative reconstruction in image space (IRIS) in half-dose (HD) datasets compared with full-dose (FD) and HD filtered back projection (FBP) reconstruction in abdominal computed tomography (CT). To acquire data with FD and HD simultaneously, contrast-enhanced abdominal CT was performed with a dual-source CT system, both tubes operating at 120 kV, 100 ref.mAs, and pitch 0.8. Three different image datasets were reconstructed from the raw data: Standard FD images applying FBP which served as reference, HD images applying FBP and HD images applying IRIS. For the HD data sets, only data from 1 tube detector-system was used. Quantitative image quality analysis was performed by measuring image noise in tissue and air. Qualitative image quality was evaluated according to the European Guidelines on Quality criteria for CT. Additional assessment of artifacts, lesion conspicuity, and edge sharpness was performed. : Image noise in soft tissue was substantially decreased in HD-IRIS (-3.4 HU, -22%) and increased in HD-FBP (+6.2 HU, +39%) images when compared with the reference (mean noise, 15.9 HU). No significant differences between the FD-FBP and HD-IRIS images were found for the visually sharp anatomic reproduction, overall diagnostic acceptability (P = 0.923), lesion conspicuity (P = 0.592), and edge sharpness (P = 0.589), while HD-FBP was rated inferior. Streak artifacts and beam hardening was significantly more prominent in HD-FBP while HD-IRIS images exhibited a slightly different noise pattern. Direct intrapatient comparison of standard FD body protocols and HD-IRIS reconstruction suggest that the latest iterative reconstruction algorithms allow for approximately 50% dose reduction without deterioration of the high image quality necessary for confident diagnosis.
Reconstruction of Undersampled Atomic Force Microscopy Images
DEFF Research Database (Denmark)
Jensen, Tobias Lindstrøm; Arildsen, Thomas; Østergaard, Jan
2013-01-01
Atomic force microscopy (AFM) is one of the most advanced tools for high-resolution imaging and manipulation of nanoscale matter. Unfortunately, standard AFM imaging requires a timescale on the order of seconds to minutes to acquire an image which makes it complicated to observe dynamic processes....... Moreover, it is often required to take several images before a relevant observation region is identified. In this paper we show how to significantly reduce the image acquisition time by undersampling. The reconstruction of an undersampled AFM image can be viewed as an inpainting, interpolating problem...... should be reconstructed using interpolation....
International Nuclear Information System (INIS)
Duc, Sylvain R.; Mengiardi, Bernard; Pfirrmann, Christian W.A.; Hodler, Juerg; Zanetti, Marco
2007-01-01
The purpose of the study was to evaluate the visualization of the collateral ankle ligaments on multiplanar reconstructions (MPR) based on standard 2D turbo spin-echo images. Coronal and axial T2-weighted turbo spin-echo and MPR angled parallel to the course of the ligaments of 15 asymptomatic and 15 symptomatic ankles were separately analyzed by two musculoskeletal radiologists. Image quality was assessed in the asymptomatic ankles qualitatively. In the symptomatic ankles interobserver agreement and reader confidence was determined for each ligament. On MPR the tibionavicular and calcaneofibular ligaments were more commonly demonstrated on a single image than on standard MR images (reader 1: 13 versus 0, P=0.002; reader 2: 14 versus 1, P=0.001 and reader 1: 13 versus 2, P=0.001; reader 2: 14 versus 0, P<0.001). The tibionavicular ligament was considered to be better delineated on MPR by reader 1 (12 versus 3, P=0.031). In the symptomatic ankles, reader confidence was greater with MPR for all ligaments except for the tibiocalcanear ligament (both readers) and the anterior and posterior talofibular ligaments (for reader 2). Interobserver agreement was increased with MPR for the tibionavicular ligament. Multiplanar reconstructions of 2D turbo spin-echo images improve the visualization of the tibionavicular and calcaneofibular ligaments and strengthen diagnostic confidence for these ligaments. (orig.)
International Nuclear Information System (INIS)
Nyflot, MJ; Yang, F; Byrd, D; Bowen, SR; Sandison, GA; Kinahan, PE
2015-01-01
Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials
Energy Technology Data Exchange (ETDEWEB)
Nyflot, MJ; Yang, F; Byrd, D; Bowen, SR; Sandison, GA; Kinahan, PE [University of Washington, Seattle, WA (United States)
2015-06-15
Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials
Photoacoustic image reconstruction via deep learning
Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes
2018-02-01
Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.
Photoacoustic image reconstruction: a quantitative analysis
Sperl, Jonathan I.; Zell, Karin; Menzenbach, Peter; Haisch, Christoph; Ketzer, Stephan; Marquart, Markus; Koenig, Hartmut; Vogel, Mika W.
2007-07-01
Photoacoustic imaging is a promising new way to generate unprecedented contrast in ultrasound diagnostic imaging. It differs from other medical imaging approaches, in that it provides spatially resolved information about optical absorption of targeted tissue structures. Because the data acquisition process deviates from standard clinical ultrasound, choice of the proper image reconstruction method is crucial for successful application of the technique. In the literature, multiple approaches have been advocated, and the purpose of this paper is to compare four reconstruction techniques. Thereby, we focused on resolution limits, stability, reconstruction speed, and SNR. We generated experimental and simulated data and reconstructed images of the pressure distribution using four different methods: delay-and-sum (DnS), circular backprojection (CBP), generalized 2D Hough transform (HTA), and Fourier transform (FTA). All methods were able to depict the point sources properly. DnS and CBP produce blurred images containing typical superposition artifacts. The HTA provides excellent SNR and allows a good point source separation. The FTA is the fastest and shows the best FWHM. In our study, we found the FTA to show the best overall performance. It allows a very fast and theoretically exact reconstruction. Only a hardware-implemented DnS might be faster and enable real-time imaging. A commercial system may also perform several methods to fully utilize the new contrast mechanism and guarantee optimal resolution and fidelity.
Tomographic image reconstruction using training images
DEFF Research Database (Denmark)
Soltani, Sara; Andersen, Martin Skovgaard; Hansen, Per Christian
2017-01-01
We describe and examine an algorithm for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a non-negative dictionary based on prototype elements from the training images; this problem is formulated within...
Colour reconstruction of underwater images
Hoth, Julian; Kowalczyk, Wojciech
2017-01-01
Objects look very different in the underwater environment compared to their appearance in sunlight. Images with correct colouring simplify the detection of underwater objects and may allow the use of visual SLAM algorithms developed for land-based robots underwater. Hence, image processing is required. Current algorithms focus on the colour reconstruction of scenery at diving depth where different colours can still be distinguished. At greater depth this is not the case. In this study it is i...
Accelerated Compressed Sensing Based CT Image Reconstruction.
Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C
2015-01-01
In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.
Accelerated Compressed Sensing Based CT Image Reconstruction
Directory of Open Access Journals (Sweden)
SayedMasoud Hashemi
2015-01-01
Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.
DEFF Research Database (Denmark)
Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell
2007-01-01
in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method...
Image reconstruction by domain-transform manifold learning
Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.
2018-03-01
Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development
D.E. Meuffels (Duncan); J.W. Potters (Jan Willem); A.H.J. Koning (Anton); C.H. Brown Jr Jr. (Charles); J.A.N. Verhaar (Jan); M. Reijman (Max)
2011-01-01
textabstractBackground and purpose: Non-anatomic bone tunnel placement is the most common cause of a failed ACL reconstruction. Accurate and reproducible methods to visualize and document bone tunnel placement are therefore important. We evaluated the reliability of standard radiographs, CT scans,
Method for position emission mammography image reconstruction
Smith, Mark Frederick
2004-10-12
An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.
Tomographic image reconstruction using Artificial Neural Networks
International Nuclear Information System (INIS)
Paschalis, P.; Giokaris, N.D.; Karabarbounis, A.; Loudos, G.K.; Maintas, D.; Papanicolas, C.N.; Spanoudaki, V.; Tsoumpas, Ch.; Stiliaris, E.
2004-01-01
A new image reconstruction technique based on the usage of an Artificial Neural Network (ANN) is presented. The most crucial factor in designing such a reconstruction system is the network architecture and the number of the input projections needed to reconstruct the image. Although the training phase requires a large amount of input samples and a considerable CPU time, the trained network is characterized by simplicity and quick response. The performance of this ANN is tested using several image patterns. It is intended to be used together with a phantom rotating table and the γ-camera of IASA for SPECT image reconstruction
Optoelectronic Computer Architecture Development for Image Reconstruction
National Research Council Canada - National Science Library
Forber, Richard
1996-01-01
.... Specifically, we collaborated with UCSD and ERIM on the development of an optically augmented electronic computer for high speed inverse transform calculations to enable real time image reconstruction...
EIT image reconstruction with four dimensional regularization.
Dai, Tao; Soleimani, Manuchehr; Adler, Andy
2008-09-01
Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.
High-speed reconstruction of compressed images
Cox, Jerome R., Jr.; Moore, Stephen M.
1990-07-01
A compression scheme is described that allows high-definition radiological images with greater than 8-bit intensity resolution to be represented by 8-bit pixels. Reconstruction of the images with their original intensity resolution can be carried out by means of a pipeline architecture suitable for compact, high-speed implementation. A reconstruction system is described that can be fabricated according to this approach and placed between an 8-bit display buffer and the display's video system thereby allowing contrast control of images at video rates. Results for 50 CR chest images are described showing that error-free reconstruction of the original 10-bit CR images can be achieved.
Iterative image reconstruction in ECT
International Nuclear Information System (INIS)
Chintu Chen; Ordonez, C.E.; Wernick, M.N.; Aarsvold, J.N.; Gunter, D.L.; Wong, W.H.; Kapp, O.H.; Xiaolong Ouyang; Levenson, M.; Metz, C.E.
1992-01-01
A series of preliminary studies has been performed in the authors laboratories to explore the use of a priori information in Bayesian image restoration and reconstruction. One piece of a priori information is the fact that intensities of neighboring pixels tend to be similar if they belong to the same region within which similar tissue characteristics are exhibited. this property of local continuity can be modeled by the use of Gibbs priors, as first suggested by German and Geman. In their investigation, they also included line sites between each pair of neighboring pixels in the Gibbs prior and used discrete binary numbers to indicate the absence or presence of boundaries between regions. These two features of the a priori model permit averaging within boundaries of homogeneous regions to alleviate the degradation caused by Poisson noise. with the use of this Gibbs prior in combination with the technique of stochastic relaxation, German and Geman demonstrated that noise levels can be reduced significantly in 2-D image restoration. They have developed a Bayesian method that utilizes a Gibbs prior to describe the spatial correlation of neighboring regions and takes into account the effect of limited spatial resolution as well. The statistical framework of the proposed approach is based on the data augmentation scheme suggested by Tanner and Wong. Briefly outlined here, this Bayesian method is based on Geman and Geman's approach
Simultaneous maximum a posteriori longitudinal PET image reconstruction
Ellis, Sam; Reader, Andrew J.
2017-09-01
Positron emission tomography (PET) is frequently used to monitor functional changes that occur over extended time scales, for example in longitudinal oncology PET protocols that include routine clinical follow-up scans to assess the efficacy of a course of treatment. In these contexts PET datasets are currently reconstructed into images using single-dataset reconstruction methods. Inspired by recently proposed joint PET-MR reconstruction methods, we propose to reconstruct longitudinal datasets simultaneously by using a joint penalty term in order to exploit the high degree of similarity between longitudinal images. We achieved this by penalising voxel-wise differences between pairs of longitudinal PET images in a one-step-late maximum a posteriori (MAP) fashion, resulting in the MAP simultaneous longitudinal reconstruction (SLR) method. The proposed method reduced reconstruction errors and visually improved images relative to standard maximum likelihood expectation-maximisation (ML-EM) in simulated 2D longitudinal brain tumour scans. In reconstructions of split real 3D data with inserted simulated tumours, noise across images reconstructed with MAP-SLR was reduced to levels equivalent to doubling the number of detected counts when using ML-EM. Furthermore, quantification of tumour activities was largely preserved over a variety of longitudinal tumour changes, including changes in size and activity, with larger changes inducing larger biases relative to standard ML-EM reconstructions. Similar improvements were observed for a range of counts levels, demonstrating the robustness of the method when used with a single penalty strength. The results suggest that longitudinal regularisation is a simple but effective method of improving reconstructed PET images without using resolution degrading priors.
Optimized Quasi-Interpolators for Image Reconstruction.
Sacht, Leonardo; Nehab, Diego
2015-12-01
We propose new quasi-interpolators for the continuous reconstruction of sampled images, combining a narrowly supported piecewise-polynomial kernel and an efficient digital filter. In other words, our quasi-interpolators fit within the generalized sampling framework and are straightforward to use. We go against standard practice and optimize for approximation quality over the entire Nyquist range, rather than focusing exclusively on the asymptotic behavior as the sample spacing goes to zero. In contrast to previous work, we jointly optimize with respect to all degrees of freedom available in both the kernel and the digital filter. We consider linear, quadratic, and cubic schemes, offering different tradeoffs between quality and computational cost. Experiments with compounded rotations and translations over a range of input images confirm that, due to the additional degrees of freedom and the more realistic objective function, our new quasi-interpolators perform better than the state of the art, at a similar computational cost.
Sparse Image Reconstruction in Computed Tomography
DEFF Research Database (Denmark)
Jørgensen, Jakob Sauer
In recent years, increased focus on the potentially harmful effects of x-ray computed tomography (CT) scans, such as radiation-induced cancer, has motivated research on new low-dose imaging techniques. Sparse image reconstruction methods, as studied for instance in the field of compressed sensing...... applications. This thesis takes a systematic approach toward establishing quantitative understanding of conditions for sparse reconstruction to work well in CT. A general framework for analyzing sparse reconstruction methods in CT is introduced and two sets of computational tools are proposed: 1...... contributions to a general set of computational characterization tools. Thus, the thesis contributions help advance sparse reconstruction methods toward routine use in...
Medical image reconstruction. A conceptual tutorial
International Nuclear Information System (INIS)
Zeng, Gengsheng Lawrence
2010-01-01
''Medical Image Reconstruction: A Conceptual Tutorial'' introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l 0 -minimization are also included. (orig.)
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
International Nuclear Information System (INIS)
Kadrmas, Dan J.; Karimi, Seemeen S.; Frey, Eric C.; Tsui, Benjamin M.W.
1998-01-01
Accurate scatter compensation in SPECT can be performed by modelling the scatter response function during the reconstruction process. This method is called reconstruction-based scatter compensation (RBSC). It has been shown that RBSC has a number of advantages over other methods of compensating for scatter, but using RBSC for fully 3D compensation has resulted in prohibitively long reconstruction times. In this work we propose two new methods that can be used in conjunction with existing methods to achieve marked reductions in RBSC reconstruction times. The first method, coarse-grid scatter modelling, significantly accelerates the scatter model by exploiting the fact that scatter is dominated by low-frequency information. The second method, intermittent RBSC, further accelerates the reconstruction process by limiting the number of iterations during which scatter is modelled. The fast implementations were evaluated using a Monte Carlo simulated experiment of the 3D MCAT phantom with 99m Tc tracer, and also using experimentally acquired data with 201 Tl tracer. Results indicated that these fast methods can reconstruct, with fully 3D compensation, images very similar to those obtained using standard RBSC methods, and in reconstruction times that are an order of magnitude shorter. Using these methods, fully 3D iterative reconstruction with RBSC can be performed well within the realm of clinically realistic times (under 10 minutes for 64x64x24 image reconstruction). (author)
International Nuclear Information System (INIS)
Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell; Knutsen, Bjoern Helge; Roeislien, Jo; Olsen, Dag Rune
2007-01-01
The purpose of this study is to investigate whether the method of applicator reconstruction and/or the applicator orientation influence the dose calculation to points around the applicator for brachytherapy of cervical cancer with CT-based treatment planning. A phantom, containing a fixed ring applicator set and six lead pellets representing dose points, was used. The phantom was CT scanned with the ring applicator at four different angles related to the image plane. In each scan the applicator was reconstructed by three methods: (1) direct reconstruction in each image (DR) (2) reconstruction in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method was significantly lower (p < 0.05) than for the DR and MPR methods for all but two points. All applicator orientations had similar dose calculation reproducibility. Using library plans for applicator reconstruction gives the most reproducible dose calculation. However, with restrictive guidelines for applicator reconstruction the uncertainties for all methods are low compared to other factors influencing the accuracy of brachytherapy
Reconstructed Image Spatial Resolution of Multiple Coincidences Compton Imager
Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna
2010-02-01
We study the multiple coincidences Compton imager (MCCI) which is based on a simultaneous acquisition of several photons emitted in cascade from a single nuclear decay. Theoretically, this technique should provide a major improvement in localization of a single radioactive source as compared to a standard Compton camera. In this work, we investigated the performance and limitations of MCCI using Monte Carlo computer simulations. Spatial resolutions of the reconstructed point source have been studied as a function of the MCCI parameters, including geometrical dimensions and detector characteristics such as materials, energy and spatial resolutions.
Parallel Algorithm for Reconstruction of TAC Images
International Nuclear Information System (INIS)
Vidal Gimeno, V.
2012-01-01
The algebraic reconstruction methods are based on solving a system of linear equations. In a previous study, was used and showed as the PETSc library, was and is a scientific computing tool, which facilitates and enables the optimal use of a computer system in the image reconstruction process.
Speeding up image reconstruction in computed tomography
CERN. Geneva
2018-01-01
Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality images even with missing or dirty data, modern detectors provide high resolution without increasing radiation dose, and high-performance multi-core computing devices are there to help us solving such tasks even faster. I will start with CT basics, then briefly present existing classes of reconstruction algorithms and their differences. After that I will proceed to employing distinctive architectural features of modern multi-core devices (CPUs and GPUs) and popular program interfaces (OpenMP, MPI, CUDA, OpenCL) for developing effective parallel realizations of image reconstruction algorithms. Decreasing full reconstruction time from long hours up to minutes or even seconds has a revolutionary impact in diagnostic medicine and industria...
Parallel CT image reconstruction based on GPUs
International Nuclear Information System (INIS)
Flores, Liubov A.; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo
2014-01-01
In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data. - Highlights: • We developed GPU-based iterative algorithm to reconstruct images. • Iterative algorithms are capable to reconstruct images from under sampled set of projections. • The computer cost of the implementation of the developed algorithm is low. • The efficiency of the algorithm increases for the large scale problems
Robust sparse image reconstruction of radio interferometric observations with PURIFY
Pratley, Luke; McEwen, Jason D.; d'Avezac, Mayeul; Carrillo, Rafael E.; Onose, Alexandru; Wiaux, Yves
2018-01-01
Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply PURIFY to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by PURIFY are of higher quality than those recovered by CLEAN. Thirdly, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.
Energy Technology Data Exchange (ETDEWEB)
Park, Juil [Seoul National University Children' s Hospital, Department of Radiology, Seoul (Korea, Republic of); Choi, Young Hun [Seoul National University Children' s Hospital, Department of Radiology, Seoul (Korea, Republic of); Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Cheon, Jung-Eun; Kim, Woo Sun; Kim, In-One [Seoul National University Children' s Hospital, Department of Radiology, Seoul (Korea, Republic of); Seoul National University College of Medicine, Department of Radiology, Seoul (Korea, Republic of); Seoul National University Medical Research Center, Institute of Radiation Medicine, Seoul (Korea, Republic of); Pak, Seong Yong [Siemens Healthineers, Seoul (Korea, Republic of); Krauss, Bernhard [Siemens Healthineers, Forchheim (Germany)
2017-11-15
Advanced virtual monochromatic reconstruction from dual-energy brain CT has not been evaluated in children. To determine the most effective advanced virtual monochromatic imaging energy level for maximizing pediatric brain parenchymal image quality in dual-energy unenhanced brain CT and to compare this technique with conventional monochromatic reconstruction and polychromatic scanning. Using both conventional (Mono) and advanced monochromatic reconstruction (Mono+) techniques, we retrospectively reconstructed 13 virtual monochromatic imaging energy levels from 40 keV to 100 keV in 5-keV increments from dual-source, dual-energy unenhanced brain CT scans obtained in 23 children. We analyzed gray and white matter noise ratios, signal-to-noise ratios and contrast-to-noise ratio, and posterior fossa artifact. We chose the optimal mono-energetic levels and compared them with conventional CT. For Mono+maximum optima were observed at 60 keV, and minimum posterior fossa artifact at 70 keV. For Mono, optima were at 65-70 keV, with minimum posterior fossa artifact at 75 keV. Mono+ was superior to Mono and to polychromatic CT for image-quality measures. Subjective analysis rated Mono+superior to other image sets. Optimal virtual monochromatic imaging using Mono+ algorithm demonstrated better image quality for gray-white matter differentiation and reduction of the artifact in the posterior fossa. (orig.)
Time-of-flight PET image reconstruction using origin ensembles
Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven
2015-03-01
The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.
Reconstruction Algorithms in Undersampled AFM Imaging
DEFF Research Database (Denmark)
Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen
2016-01-01
This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby...... the scanning time as well as the amount of interaction between the AFM probe and the specimen. It can easily be applied on conventional AFM hardware. Due to undersampling, it is then necessary to further process the acquired image in order to reconstruct an approximation of the image. Based on real AFM cell...... images, our simulations reveal that using a simple raster scanning pattern in combination with conventional image interpolation performs very well. Moreover, this combination enables a reduction by a factor 10 of the scanning time while retaining an average reconstruction quality around 36 dB PSNR...
3D Reconstruction of NMR Images
Directory of Open Access Journals (Sweden)
Peter Izak
2007-01-01
Full Text Available This paper introduces experiment of 3D reconstruction NMR images scanned from magnetic resonance device. There are described methods which can be used for 3D reconstruction magnetic resonance images in biomedical application. The main idea is based on marching cubes algorithm. For this task was chosen sophistication method by program Vision Assistant, which is a part of program LabVIEW.
Photogrammetric 3D reconstruction using mobile imaging
Fritsch, Dieter; Syll, Miguel
2015-03-01
In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.
Fast parallel algorithm for CT image reconstruction.
Flores, Liubov A; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo
2012-01-01
In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).
International Nuclear Information System (INIS)
Böning, G.; Schäfer, M.; Grupp, U.; Kaul, D.; Kahn, J.; Pavel, M.; Maurer, M.; Denecke, T.; Hamm, B.; Streitparth, F.
2015-01-01
Highlights: • Iterative reconstruction (IR) in staging CT provides equal objective image quality compared to filtered back projection (FBP). • IR delivers excellent subjective quality and reduces effective dose compared to FBP. • In patients with neuroendocrine tumor (NET) or may other hypervascular abdominal tumors IR can be used without scarifying diagnostic confidence. - Abstract: Objective: To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. Methods: A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDI vol ) of each scan was taken from the dose report. Results: ASIR 40% significantly reduced CTDI vol (10.17 ± 3.06 mGy [FBP], 6.34 ± 2.25 mGy [ASIR] (p < 0.001) by 37.6% and significantly increased CNRs (complete tumor-to-liver, 2.76 ± 1.87 [FBP], 3.2 ± 2.32 [ASIR]) (p < 0.05) (complete tumor-to-muscle, 2.74 ± 2.67 [FBP], 4.31 ± 4.61 [ASIR]) (p < 0.05) compared to FBP. Subjective scoring revealed no significant changes for diagnostic confidence (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]), visibility of suspicious lesion (4.8 ± 0.5 [FBP], 4.8 ± 0.5 [ASIR]) and artifacts (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3 ± 0.6 [FBP], 4.0 ± 0.8 [ASIR]) (p < 0.05), contrast (4.4 ± 0.6 [FBP], 4.1 ± 0.8 [ASIR]) (p < 0.001) and visibility of small structures (4.5 ± 0.7 [FBP], 4.3 ± 0.8 [ASIR]) (p < 0
Energy Technology Data Exchange (ETDEWEB)
Böning, G., E-mail: georg.boening@charite.de [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Schäfer, M.; Grupp, U. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Kaul, D. [Department of Radiation Oncology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Kahn, J. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Pavel, M. [Department of Gastroenterology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Maurer, M.; Denecke, T.; Hamm, B.; Streitparth, F. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany)
2015-08-15
Highlights: • Iterative reconstruction (IR) in staging CT provides equal objective image quality compared to filtered back projection (FBP). • IR delivers excellent subjective quality and reduces effective dose compared to FBP. • In patients with neuroendocrine tumor (NET) or may other hypervascular abdominal tumors IR can be used without scarifying diagnostic confidence. - Abstract: Objective: To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. Methods: A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDI{sub vol}) of each scan was taken from the dose report. Results: ASIR 40% significantly reduced CTDI{sub vol} (10.17 ± 3.06 mGy [FBP], 6.34 ± 2.25 mGy [ASIR] (p < 0.001) by 37.6% and significantly increased CNRs (complete tumor-to-liver, 2.76 ± 1.87 [FBP], 3.2 ± 2.32 [ASIR]) (p < 0.05) (complete tumor-to-muscle, 2.74 ± 2.67 [FBP], 4.31 ± 4.61 [ASIR]) (p < 0.05) compared to FBP. Subjective scoring revealed no significant changes for diagnostic confidence (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]), visibility of suspicious lesion (4.8 ± 0.5 [FBP], 4.8 ± 0.5 [ASIR]) and artifacts (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3 ± 0.6 [FBP], 4.0 ± 0.8 [ASIR]) (p < 0.05), contrast (4.4 ± 0.6 [FBP], 4.1 ± 0.8 [ASIR]) (p < 0.001) and visibility of small structures (4.5 ± 0.7 [FBP], 4.3 ± 0.8 [ASIR]) (p < 0
MR image reconstruction via guided filter.
Huang, Heyan; Yang, Hang; Wang, Kang
2018-04-01
Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.
Wenz, Holger; Maros, Máté E; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas
2015-01-01
To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (pspiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.
Heuristic optimization in penumbral image for high resolution reconstructed image
International Nuclear Information System (INIS)
Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.
2010-01-01
Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.
Computational acceleration for MR image reconstruction in partially parallel imaging.
Ye, Xiaojing; Chen, Yunmei; Huang, Feng
2011-05-01
In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images.
3-D image reconstruction in radiology
International Nuclear Information System (INIS)
Grangeat, P.
1999-01-01
In this course, we present highlights on fully 3-D image reconstruction algorithms used in 3-D X-ray Computed Tomography (3-D-CT) and 3-D Rotational Radiography (3-D-RR). We first consider the case of spiral CT with a one-row detector. Starting from the 2-D fan-beam inversion formula for a circular trajectory, we introduce spiral CT 3-D image reconstruction algorithm using axial interpolation for each transverse slice. In order to improve the X-ray detection efficiency and to speed the acquisition process, the future is to use multi-row detectors associated with small angle cone-beam geometry. The generalization of the 2-D fan-beam image reconstruction algorithm to cone beam defined direct inversion formula referred as Feldkamp's algorithm for a circular trajectory and Wang's algorithm for a spiral trajectory. However, large area detectors does exist such as Radiological Image Intensifiers or in a near future solid state detectors. To get a larger zoom effect, it defines a cone-beam geometry associated with a large aperture angle. For this case, we introduce indirect image reconstruction algorithm by plane re-binning in the Radon domain. We will present some results from a prototype MORPHOMETER device using the RADON reconstruction software. Lastly, we consider the special case of 3-D Rotational Digital Subtraction Angiography with a restricted number of views. We introduce constraint optimization algorithm using quadratic, entropic or half-quadratic constraints. Generalized ART (Algebraic Reconstruction Technique) iterative reconstruction algorithm can be derived from the Bregman algorithm. We present reconstructed vascular trees from a prototype MORPHOMETER device. (author)
Use of a model for 3D image reconstruction
International Nuclear Information System (INIS)
Delageniere, S.; Grangeat, P.
1991-01-01
We propose a software for 3D image reconstruction in transmission tomography. This software is based on the use of a model and of the RADON algorithm developed at LETI. The introduction of a markovian model helps us to enhance contrast and straitened the natural transitions existing in the objects studied, whereas standard transform methods smoothe them
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
Böning, G; Schäfer, M; Grupp, U; Kaul, D; Kahn, J; Pavel, M; Maurer, M; Denecke, T; Hamm, B; Streitparth, F
2015-08-01
To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDIvol) of each scan was taken from the dose report. ASIR 40% significantly reduced CTDIvol (10.17±3.06mGy [FBP], 6.34±2.25mGy [ASIR] (pASIR]) (pASIR]) (pASIR]), visibility of suspicious lesion (4.8±0.5 [FBP], 4.8±0.5 [ASIR]) and artifacts (5.0±0 [FBP], 5.0±0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3±0.6 [FBP], 4.0±0.8 [ASIR]) (pASIR]) (pASIR]) (pASIR can be used to reduce radiation dose without sacrificing image quality and diagnostic confidence in staging CT of NET patients. This may be beneficial for patients with frequent follow-up and significant cumulative radiation exposure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method
Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao
2017-03-01
Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.
Image reconstruction methods in positron tomography
International Nuclear Information System (INIS)
Townsend, D.W.; Defrise, M.
1993-01-01
In the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non-invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-ray but also for studies which explore the functional status of the body using positron-emitting radioisotopes. This report reviews the historical and physical basis of medical imaging techniques using positron-emitting radioisotopes. Mathematical methods which enable three-dimensional distributions of radioisotopes to be reconstructed from projection data (sinograms) acquired by detectors suitably positioned around the patient are discussed. The extension of conventional two-dimensional tomographic reconstruction algorithms to fully three-dimensional reconstruction is described in detail. (orig.)
Directory of Open Access Journals (Sweden)
Anna Lisa Stöckl
2015-09-01
Full Text Available In the study of insect neuroanatomy, three-dimensional reconstructions of neurons and neuropils have become a standard technique. As images have to be obtained from whole-mount brain preparations, pigmentation on the brain surface poses a serious challenge to imaging. In insects, this is a major problematic in the first visual neuropil of the optic lobe, the lamina, which is obstructed by the pigment of the retina as well as by the pigmented fenestration layer. This has prevented inclusion of this major processing center of the insect visual system into most neuroanatomical brain atlases and hinders imaging of neurons within the lamina by confocal microscopy. It has recently been shown that hydrogen peroxide bleaching is compatible with immunohistochemical labeling in insect brains, and we therefore developed a simple technique for removal of pigments on the surface of insect brains by chemical bleaching. We show that our technique enables imaging of the pigment-obstructed regions of insect brains when combined with standard protocols for both anti-synapsin-labeled as well as neurobiotin-injected samples. This method can be combined with different fixation procedures, as well as different fluorophore excitation wavelengths without negative effects on staining quality. It can therefore serve as an effective addition to most standard histology protocols used in insect neuroanatomy.
Imaging standards for smart cards
Ellson, Richard N.; Ray, Lawrence A.
1996-02-01
"Smart cards" are plastic cards the size of credit cards which contain integrated circuits for the storage of digital information. The applications of these cards for image storage has been growing as card data capacities have moved from tens of bytes to thousands of bytes. This has prompted the recommendation of standards by the X3B10 committee of ANSI for inclusion in ISO standards for card image storage of a variety of image data types including digitized signatures and color portrait images. This paper will review imaging requirements of the smart card industry, challenges of image storage for small memory devices, card image communications, and the present status of standards. The paper will conclude with recommendations for the evolution of smart card image standards towards image formats customized to the image content and more optimized for smart card memory constraints.
Energy Technology Data Exchange (ETDEWEB)
Becce, Fabio [University of Lausanne, Department of Diagnostic and Interventional Radiology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Universite Catholique Louvain, Department of Radiology, Cliniques Universitaires Saint-Luc, Brussels (Belgium); Ben Salah, Yosr; Berg, Bruno C. vande; Lecouvet, Frederic E.; Omoumi, Patrick [Universite Catholique Louvain, Department of Radiology, Cliniques Universitaires Saint-Luc, Brussels (Belgium); Verdun, Francis R. [University of Lausanne, Institute of Radiation Physics, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland); Meuli, Reto [University of Lausanne, Department of Diagnostic and Interventional Radiology, Centre Hospitalier Universitaire Vaudois, Lausanne (Switzerland)
2013-07-15
To compare image quality of a standard-dose (SD) and a low-dose (LD) cervical spine CT protocol using filtered back-projection (FBP) and iterative reconstruction (IR). Forty patients investigated by cervical spine CT were prospectively randomised into two groups: SD (120 kVp, 275 mAs) and LD (120 kVp, 150 mAs), both applying automatic tube current modulation. Data were reconstructed using both FBP and sinogram-affirmed IR. Image noise, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were measured. Two radiologists independently and blindly assessed the following anatomical structures at C3-C4 and C6-C7 levels, using a four-point scale: intervertebral disc, content of neural foramina and dural sac, ligaments, soft tissues and vertebrae. They subsequently rated overall image quality using a ten-point scale. For both protocols and at each disc level, IR significantly decreased image noise and increased SNR and CNR, compared with FBP. SNR and CNR were statistically equivalent in LD-IR and SD-FBP protocols. Regardless of the dose and disc level, the qualitative scores with IR compared with FBP, and with LD-IR compared with SD-FBP, were significantly higher or not statistically different for intervertebral discs, neural foramina and ligaments, while significantly lower or not statistically different for soft tissues and vertebrae. The overall image quality scores were significantly higher with IR compared with FBP, and with LD-IR compared with SD-FBP. LD-IR cervical spine CT provides better image quality for intervertebral discs, neural foramina and ligaments, and worse image quality for soft tissues and vertebrae, compared with SD-FBP, while reducing radiation dose by approximately 40 %. (orig.)
International Nuclear Information System (INIS)
Becce, Fabio; Ben Salah, Yosr; Berg, Bruno C. vande; Lecouvet, Frederic E.; Omoumi, Patrick; Verdun, Francis R.; Meuli, Reto
2013-01-01
To compare image quality of a standard-dose (SD) and a low-dose (LD) cervical spine CT protocol using filtered back-projection (FBP) and iterative reconstruction (IR). Forty patients investigated by cervical spine CT were prospectively randomised into two groups: SD (120 kVp, 275 mAs) and LD (120 kVp, 150 mAs), both applying automatic tube current modulation. Data were reconstructed using both FBP and sinogram-affirmed IR. Image noise, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were measured. Two radiologists independently and blindly assessed the following anatomical structures at C3-C4 and C6-C7 levels, using a four-point scale: intervertebral disc, content of neural foramina and dural sac, ligaments, soft tissues and vertebrae. They subsequently rated overall image quality using a ten-point scale. For both protocols and at each disc level, IR significantly decreased image noise and increased SNR and CNR, compared with FBP. SNR and CNR were statistically equivalent in LD-IR and SD-FBP protocols. Regardless of the dose and disc level, the qualitative scores with IR compared with FBP, and with LD-IR compared with SD-FBP, were significantly higher or not statistically different for intervertebral discs, neural foramina and ligaments, while significantly lower or not statistically different for soft tissues and vertebrae. The overall image quality scores were significantly higher with IR compared with FBP, and with LD-IR compared with SD-FBP. LD-IR cervical spine CT provides better image quality for intervertebral discs, neural foramina and ligaments, and worse image quality for soft tissues and vertebrae, compared with SD-FBP, while reducing radiation dose by approximately 40 %. (orig.)
Research of ART method in CT image reconstruction
International Nuclear Information System (INIS)
Li Zhipeng; Cong Peng; Wu Haifeng
2005-01-01
This paper studied Algebraic Reconstruction Technique (ART) in CT image reconstruction. Discussed the ray number influence on image quality. And the adopting of smooth method got high quality CT image. (authors)
Image reconstruction under non-Gaussian noise
DEFF Research Database (Denmark)
Sciacchitano, Federica
During acquisition and transmission, images are often blurred and corrupted by noise. One of the fundamental tasks of image processing is to reconstruct the clean image from a degraded version. The process of recovering the original image from the data is an example of inverse problem. Due...... to the ill-posedness of the problem, the simple inversion of the degradation model does not give any good reconstructions. Therefore, to deal with the ill-posedness it is necessary to use some prior information on the solution or the model and the Bayesian approach. Additive Gaussian noise has been......D thesis intends to solve some of the many open questions for image restoration under non-Gaussian noise. The two main kinds of noise studied in this PhD project are the impulse noise and the Cauchy noise. Impulse noise is due to for instance the malfunctioning pixel elements in the camera sensors, errors...
Proton computed tomography images with algebraic reconstruction
Energy Technology Data Exchange (ETDEWEB)
Bruzzi, M. [Physics and Astronomy Department, University of Florence, Florence (Italy); Civinini, C.; Scaringella, M. [INFN - Florence Division, Florence (Italy); Bonanno, D. [INFN - Catania Division, Catania (Italy); Brianzi, M. [INFN - Florence Division, Florence (Italy); Carpinelli, M. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Cirrone, G.A.P.; Cuttone, G. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Presti, D. Lo [INFN - Catania Division, Catania (Italy); Physics and Astronomy Department, University of Catania, Catania (Italy); Maccioni, G. [INFN – Cagliari Division, Cagliari (Italy); Pallotta, S. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Randazzo, N. [INFN - Catania Division, Catania (Italy); Romano, F. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Sipala, V. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Talamonti, C. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Vanzi, E. [Fisica Sanitaria, Azienda Ospedaliero-Universitaria Senese, Siena (Italy)
2017-02-11
A prototype of proton Computed Tomography (pCT) system for hadron-therapy has been manufactured and tested in a 175 MeV proton beam with a non-homogeneous phantom designed to simulate high-contrast material. BI-SART reconstruction algorithms have been implemented with GPU parallelism, taking into account of most likely paths of protons in matter. Reconstructed tomography images with density resolutions r.m.s. down to ~1% and spatial resolutions <1 mm, achieved within processing times of ~15′ for a 512×512 pixels image prove that this technique will be beneficial if used instead of X-CT in hadron-therapy.
Image reconstruction in computerized tomography using the convolution method
International Nuclear Information System (INIS)
Oliveira Rebelo, A.M. de.
1984-03-01
In the present work an algoritin was derived, using the analytical convolution method (filtered back-projection) for two-dimensional or three-dimensional image reconstruction in computerized tomography applied to non-destructive testing and to the medical use. This mathematical model is based on the analytical Fourier transform method for image reconstruction. This model consists of a discontinuous system formed by an NxN array of cells (pixels). The attenuation in the object under study of a colimated gamma ray beam has been determined for various positions and incidence angles (projections) in terms of the interaction of the beam with the intercepted pixels. The contribution of each pixel to beam attenuation was determined using the weight function W ij which was used for simulated tests. Simulated tests using standard objects with attenuation coefficients in the range of 0,2 to 0,7 cm -1 were carried out using cell arrays of up to 25x25. One application was carried out in the medical area simulating image reconstruction of an arm phantom with attenuation coefficients in the range of 0,2 to 0,5 cm -1 using cell arrays of 41x41. The simulated results show that, in objects with a great number of interfaces and great variations of attenuation coefficients at these interfaces, a good reconstruction is obtained with the number of projections equal to the reconstruction matrix dimension. A good reconstruction is otherwise obtained with fewer projections. (author) [pt
On an image reconstruction method for ECT
Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro
2007-04-01
An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.
3D EIT image reconstruction with GREIT.
Grychtol, Bartłomiej; Müller, Beat; Adler, Andy
2016-06-01
Most applications of thoracic EIT use a single plane of electrodes on the chest from which a transverse image 'slice' is calculated. However, interpretation of EIT images is made difficult by the large region above and below the electrode plane to which EIT is sensitive. Volumetric EIT images using two (or more) electrode planes should help compensate, but are little used currently. The Graz consensus reconstruction algorithm for EIT (GREIT) has become popular in lung EIT. One shortcoming of the original formulation of GREIT is its restriction to reconstruction onto a 2D planar image. We present an extension of the GREIT algorithm to 3D and develop open-source tools to evaluate its performance as a function of the choice of stimulation and measurement pattern. Results show 3D GREIT using two electrode layers has significantly more uniform sensitivity profiles through the chest region. Overall, the advantages of 3D EIT are compelling.
Reconstructing building mass models from UAV images
Li, Minglei; Nan, Liangliang; Smith, Neil; Wonka, Peter
2015-01-01
We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first
Connections model for tomographic images reconstruction
International Nuclear Information System (INIS)
Rodrigues, R.G.S.; Pela, C.A.; Roque, S.F. A.C.
1998-01-01
This paper shows an artificial neural network with an adequately topology for tomographic image reconstruction. The associated error function is derived and the learning algorithm is make. The simulated results are presented and demonstrate the existence of a generalized solution for nets with linear activation function. (Author)
Non-Cartesian parallel imaging reconstruction.
Wright, Katherine L; Hamilton, Jesse I; Griswold, Mark A; Gulani, Vikas; Seiberlich, Nicole
2014-11-01
Non-Cartesian parallel imaging has played an important role in reducing data acquisition time in MRI. The use of non-Cartesian trajectories can enable more efficient coverage of k-space, which can be leveraged to reduce scan times. These trajectories can be undersampled to achieve even faster scan times, but the resulting images may contain aliasing artifacts. Just as Cartesian parallel imaging can be used to reconstruct images from undersampled Cartesian data, non-Cartesian parallel imaging methods can mitigate aliasing artifacts by using additional spatial encoding information in the form of the nonhomogeneous sensitivities of multi-coil phased arrays. This review will begin with an overview of non-Cartesian k-space trajectories and their sampling properties, followed by an in-depth discussion of several selected non-Cartesian parallel imaging algorithms. Three representative non-Cartesian parallel imaging methods will be described, including Conjugate Gradient SENSE (CG SENSE), non-Cartesian generalized autocalibrating partially parallel acquisition (GRAPPA), and Iterative Self-Consistent Parallel Imaging Reconstruction (SPIRiT). After a discussion of these three techniques, several potential promising clinical applications of non-Cartesian parallel imaging will be covered. © 2014 Wiley Periodicals, Inc.
Software for 3D diagnostic image reconstruction and analysis
International Nuclear Information System (INIS)
Taton, G.; Rokita, E.; Sierzega, M.; Klek, S.; Kulig, J.; Urbanik, A.
2005-01-01
Recent advances in computer technologies have opened new frontiers in medical diagnostics. Interesting possibilities are the use of three-dimensional (3D) imaging and the combination of images from different modalities. Software prepared in our laboratories devoted to 3D image reconstruction and analysis from computed tomography and ultrasonography is presented. In developing our software it was assumed that it should be applicable in standard medical practice, i.e. it should work effectively with a PC. An additional feature is the possibility of combining 3D images from different modalities. The reconstruction and data processing can be conducted using a standard PC, so low investment costs result in the introduction of advanced and useful diagnostic possibilities. The program was tested on a PC using DICOM data from computed tomography and TIFF files obtained from a 3D ultrasound system. The results of the anthropomorphic phantom and patient data were taken into consideration. A new approach was used to achieve spatial correlation of two independently obtained 3D images. The method relies on the use of four pairs of markers within the regions under consideration. The user selects the markers manually and the computer calculates the transformations necessary for coupling the images. The main software feature is the possibility of 3D image reconstruction from a series of two-dimensional (2D) images. The reconstructed 3D image can be: (1) viewed with the most popular methods of 3D image viewing, (2) filtered and processed to improve image quality, (3) analyzed quantitatively (geometrical measurements), and (4) coupled with another, independently acquired 3D image. The reconstructed and processed 3D image can be stored at every stage of image processing. The overall software performance was good considering the relatively low costs of the hardware used and the huge data sets processed. The program can be freely used and tested (source code and program available at
Blockwise conjugate gradient methods for image reconstruction in volumetric CT.
Qiu, W; Titley-Peloquin, D; Soleimani, M
2012-11-01
Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
3-D Reconstruction From Satellite Images
DEFF Research Database (Denmark)
Denver, Troelz
1999-01-01
of planetary surfaces, but other purposes is considered as well. The system performance is measured with respect to the precision and the time consumption.The reconstruction process is divided into four major areas: Acquisition, calibration, matching/reconstruction and presentation. Each of these areas...... are treated individually. A detailed treatment of various lens distortions is required, in order to correct for these problems. This subject is included in the acquisition part. In the calibration part, the perspective distortion is removed from the images. Most attention has been paid to the matching problem...
Ellis, Sam; Reader, Andrew J
2018-04-26
Many clinical contexts require the acquisition of multiple positron emission tomography (PET) scans of a single subject, for example to observe and quantify changes in functional behaviour in tumours after treatment in oncology. Typically, the datasets from each of these scans are reconstructed individually, without exploiting the similarities between them. We have recently shown that sharing information between longitudinal PET datasets by penalising voxel-wise differences during image reconstruction can improve reconstructed images by reducing background noise and increasing the contrast-to-noise ratio of high activity lesions. Here we present two additional novel longitudinal difference-image priors and evaluate their performance using 2D simulation studies and a 3D real dataset case study. We have previously proposed a simultaneous difference-image-based penalised maximum likelihood (PML) longitudinal image reconstruction method that encourages sparse difference images (DS-PML), and in this work we propose two further novel prior terms. The priors are designed to encourage longitudinal images with corresponding differences which have i) low entropy (DE-PML), and ii) high sparsity in their spatial gradients (DTV-PML). These two new priors and the originally proposed longitudinal prior were applied to 2D simulated treatment response [ 18 F]fluorodeoxyglucose (FDG) brain tumour datasets and compared to standard maximum likelihood expectation-maximisation (MLEM) reconstructions. These 2D simulation studies explored the effects of penalty strengths, tumour behaviour, and inter-scan coupling on reconstructed images. Finally, a real two-scan longitudinal data series acquired from a head and neck cancer patient was reconstructed with the proposed methods and the results compared to standard reconstruction methods. Using any of the three priors with an appropriate penalty strength produced images with noise levels equivalent to those seen when using standard
Notohamiprodjo, S; Deak, Z; Meurer, F; Maertz, F; Mueck, F G; Geyer, L L; Wirth, S
2015-01-01
The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p ASiR was 2 (p ASiR (p ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. • Model-Based iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT. • MBIR reconstructed images were rated with significantly higher scores for image quality. • Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.
Reconstructing building mass models from UAV images
Li, Minglei
2015-07-26
We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.
Optimization of PET image quality by means of 3D data acquisition and iterative image reconstruction
International Nuclear Information System (INIS)
Doll, J.; Zaers, J.; Trojan, H.; Bellemann, M.E.; Adam, L.E.; Haberkorn, U.; Brix, G.
1998-01-01
The experiments were performed at the latest-generation whole-body PET system ECAT EXACT HR + . For 2D data acquisition, a collimator of thin tungsten septa was positioned in the field-of-view. Prior to image reconstruction, the measured 3D data were sorted into 2D sinograms by using the Fourier rebinning (FORE) algorithm developed by M. Defrise. The standard filtered backprojection (FBP) method and an optimized ML/EM algorithm with overrelaxation for accelerated convergence were employed for image reconstruction. The spatial resolution of both methods as well as the convergence and noise properties of the ML/EM algorithm were studied in phantom measurements. Furthermore, patient data were acquired in the 2D mode as well as in the 3D mode and reconstructed with both techniques. At the same spatial resolution, the ML/EM-reconstructed images showed fewer and less prominent artefacts than the FBP-reconstructed images. The resulting improved detail conspicuously was achieved for the data acquired in the 2D mode as well as in the 3D mode. The best image quality was obtained by iterative 2D reconstruction of 3D data sets which were previously rebinned into 2D sinograms with help of the FORE algorithm. The phantom measurements revealed that 50 iteration steps with the otpimized ML/EM algorithm were sufficient to keep the relative quantitation error below 5%. (orig./MG) [de
Homotopy Based Reconstruction from Acoustic Images
DEFF Research Database (Denmark)
Sharma, Ojaswa
of the inherent arrangement. The problem of reconstruction from arbitrary cross sections is a generic problem and is also shown to be solved here using the mathematical tool of continuous deformations. As part of a complete processing, segmentation using level set methods is explored for acoustic images and fast...... GPU (Graphics Processing Unit) based methods are suggested for a streaming computation on large volumes of data. Validation of results for acoustic images is not straightforward due to unavailability of ground truth. Accuracy figures for the suggested methods are provided using phantom object...
Image reconstruction of dynamic infrared single-pixel imaging system
Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin
2018-03-01
Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.
Image-reconstruction methods in positron tomography
Townsend, David W; CERN. Geneva
1993-01-01
Physics and mathematics for medical imaging In the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non-invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-rays but also for studies which explore the functional status of the body using positron-emitting radioisotopes and nuclear magnetic resonance. Mathematical methods which enable three-dimentional distributions to be reconstructed from projection data acquired by radiation detectors suitably positioned around the patient will be described in detail. The lectures will trace the development of medical imaging from simpleradiographs to the present-day non-invasive measurement of in vivo boichemistry. Powerful techniques to correlate anatomy and function that are cur...
Three-dimensional reconstruction of CT images
Energy Technology Data Exchange (ETDEWEB)
Watanabe, Toshiaki; Kattoh, Keiichi; Kawakami, Genichiroh; Igami, Isao; Mariya, Yasushi; Nakamura, Yasuhiko; Saitoh, Yohko; Tamura, Koreroku; Shinozaki, Tatsuyo
1986-09-01
Computed tomography (CT) has the ability to provide sensitive visualization of organs and lesions. Owing to the nature of CT to be transaxial images, a structure which is greater than a certain size appears as several serial CT images. Consequently each observer must reconstruct those images into a three-dimensional (3-D) form mentally. It has been supposed to be of great use if such a 3-D form can be described as a definite figure. A new computer program has been developed which can produce 3-D figures from the profiles of organs and lesions on CT images using spline curves. The figures obtained through this method are regarded to have practical applications.
Simulated annealing image reconstruction for positron emission tomography
Energy Technology Data Exchange (ETDEWEB)
Sundermann, E; Lemahieu, I; Desmedt, P [Department of Electronics and Information Systems, University of Ghent, St. Pietersnieuwstraat 41, B-9000 Ghent, Belgium (Belgium)
1994-12-31
In Positron Emission Tomography (PET) images have to be reconstructed from moisy projection data. The noise on the PET data can be modeled by a Poison distribution. In this paper, we present the results of using the simulated annealing technique to reconstruct PET images. Various parameter settings of the simulated annealing algorithm are discussed and optimized. The reconstructed images are of good quality and high contrast, in comparison to other reconstruction techniques. (authors). 11 refs., 2 figs.
Simulated annealing image reconstruction for positron emission tomography
International Nuclear Information System (INIS)
Sundermann, E.; Lemahieu, I.; Desmedt, P.
1994-01-01
In Positron Emission Tomography (PET) images have to be reconstructed from moisy projection data. The noise on the PET data can be modeled by a Poison distribution. In this paper, we present the results of using the simulated annealing technique to reconstruct PET images. Various parameter settings of the simulated annealing algorithm are discussed and optimized. The reconstructed images are of good quality and high contrast, in comparison to other reconstruction techniques. (authors)
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
Camargo, Gabriel C; Erthal, Fernanda; Sabioni, Leticia; Penna, Filipe; Strecker, Ralph; Schmidt, Michaela; Zenge, Michael O; Lima, Ronaldo de S L; Gottlieb, Ilan
2017-05-01
Segmented cine imaging with a steady-state free-precession sequence (Cine-SSFP) is currently the gold standard technique for measuring ventricular volumes and mass, but due to multi breath-hold (BH) requirements, it is prone to misalignment of consecutive slices, time consuming and dependent on respiratory capacity. Real-time cine avoids those limitations, but poor spatial and temporal resolution of conventional sequences has prevented its routine application. We sought to examine the accuracy and feasibility of a newly developed real-time sequence with aggressive under-sampling of k-space using sparse sampling and iterative reconstruction (Cine-RT). Stacks of short-axis cines were acquired covering both ventricles in a 1.5T system using gold standard Cine-SSFP and Cine-RT. Acquisition parameters for Cine-SSFP were: acquisition matrix of 224×196, temporal resolution of 39ms, retrospective gating, with an average of 8 heartbeats per slice and 1-2 slices/BH. For Cine-RT: acquisition matrix of 224×196, sparse sampling net acceleration factor of 11.3, temporal resolution of 41ms, prospective gating, real-time acquisition of 1 heart-beat/slice and all slices in one BH. LV contours were drawn at end diastole and systole to derive LV volumes and mass. Forty-one consecutive patients (15 male; 41±17years) in sinus rhythm were successfully included. All images from Cine-SSFP and Cine-RT were considered to have excellent quality. Cine-RT-derived LV volumes and mass were slightly underestimated but strongly correlated with gold standard Cine-SSFP. Inter- and intra-observer analysis presented similar results between both sequences. Cine-RT featuring sparse sampling and iterative reconstruction can achieve spatial and temporal resolution equivalent to Cine-SSFP, providing excellent image quality, with similar precision measurements and highly correlated and only slightly underestimated volume and mass values. Copyright © 2017 Elsevier Inc. All rights reserved.
Image reconstruction. Application to transverse axial tomography
International Nuclear Information System (INIS)
Aubry, Florent.
1977-09-01
A method of computerized tridimensional image reconstruction from their projection, especially in the computerized transverse axial tomography is suggested. First, the different techniques actually developped and presented in the literature are analyzed. Then, the equipment used is briefly described. The reconstruction algorithm developped is presented. This algorithm is based on the convolution method, well adapted to the real conditions of exploitation. It is an extension of SHEPP and LOGAN's algorithm. A correction of the self absorption and of the detector's response is proposed. Finally, the first results obtained which are satisfactory are given. The simplicity of the method which does not need a too long computation time makes possible the implementation of the algorithm on a mini-computer [fr
Reconstruction of Novel Viewpoint Image Using GRNN
Institute of Scientific and Technical Information of China (English)
李战委; 孙济洲; 张志强
2003-01-01
A neural-statistical approach to the reconstruction of novel viewpoint image using general regression neural networks(GRNN) is presented. Different color value will be obtained by watching the same surface point of an object from different viewpoints due to specular reflection, and the difference is related to the position of viewpoint. The relationship between the position of viewpoint and the color of image is non-linear, neural network is introduced to make curve fitting, where the inputs of neural network are only a few calibrated images with obvious specular reflection. By training the neural network, network model is obtained. By inputing an arbitrary virtual viewpoint to the model, the image of the virtual viewpoint can be computed. By using the method presented here, novel viewpoint image with photo-realistic property can be obtained, especially images with obvious specular reflection can accurately be generated. The method is an image-based rendering method, geometric model of the scene and position of lighting are not needed.
Image reconstruction in k-space from MR data encoded with ambiguous gradient fields.
Schultz, Gerrit; Gallichan, Daniel; Weber, Hans; Witschey, Walter R T; Honal, Matthias; Hennig, Jürgen; Zaitsev, Maxim
2015-02-01
In this work, the limits of image reconstruction in k-space are explored when non-bijective gradient fields are used for spatial encoding. The image space analogy between parallel imaging and imaging with non-bijective encoding fields is partially broken in k-space. As a consequence, it is hypothesized and proven that ambiguities can only be resolved partially in k-space, and not completely as is the case in image space. Image-space and k-space based reconstruction algorithms for multi-channel radiofrequency data acquisitions are programmed and tested using numerical simulations as well as in vivo measurement data. The hypothesis is verified based on an analysis of reconstructed images. It is found that non-bijective gradient fields have the effect that densely sampled autocalibration data, used for k-space reconstruction, provide less information than a separate scan of the receiver coil sensitivity maps, used for image space reconstruction. Consequently, in k-space only the undersampling artifact can be unfolded, whereas in image space, it is also possible to resolve aliasing that is caused by the non-bijectivity of the gradient fields. For standard imaging, reconstruction in image space and in k-space is nearly equivalent, whereas there is a fundamental difference with practical consequences for the selection of image reconstruction algorithms when non-bijective encoding fields are involved. © 2014 Wiley Periodicals, Inc.
An efficient simultaneous reconstruction technique for tomographic particle image velocimetry
Atkinson, Callum; Soria, Julio
2009-10-01
To date, Tomo-PIV has involved the use of the multiplicative algebraic reconstruction technique (MART), where the intensity of each 3D voxel is iteratively corrected to satisfy one recorded projection, or pixel intensity, at a time. This results in reconstruction times of multiple hours for each velocity field and requires considerable computer memory in order to store the associated weighting coefficients and intensity values for each point in the volume. In this paper, a rapid and less memory intensive reconstruction algorithm is presented based on a multiplicative line-of-sight (MLOS) estimation that determines possible particle locations in the volume, followed by simultaneous iterative correction. Reconstructions of simulated images are presented for two simultaneous algorithms (SART and SMART) as well as the now standard MART algorithm, which indicate that the same accuracy as MART can be achieved 5.5 times faster or 77 times faster with 15 times less memory if the processing and storage of the weighting matrix is considered. Application of MLOS-SMART and MART to a turbulent boundary layer at Re θ = 2200 using a 4 camera Tomo-PIV system with a volume of 1,000 × 1,000 × 160 voxels is discussed. Results indicate improvements in reconstruction speed of 15 times that of MART with precalculated weighting matrix, or 65 times if calculation of the weighting matrix is considered. Furthermore the memory needed to store a large weighting matrix and volume intensity is reduced by almost 40 times in this case.
Comparison of power spectra for tomosynthesis projections and reconstructed images
International Nuclear Information System (INIS)
Engstrom, Emma; Reiser, Ingrid; Nishikawa, Robert
2009-01-01
Burgess et al. [Med. Phys. 28, 419-437 (2001)] showed that the power spectrum of mammographic breast background follows a power law and that lesion detectability is affected by the power-law exponent β which measures the amount of structure in the background. Following the study of Burgess et al., the authors measured and compared the power-law exponent of mammographic backgrounds in tomosynthesis projections and reconstructed slices to investigate the effect of tomosynthesis imaging on background structure. Our data set consisted of 55 patient cases. For each case, regions of interest (ROIs) were extracted from both projection images and reconstructed slices. The periodogram of each ROI was computed by taking the squared modulus of the Fourier transform of the ROI. The power-law exponent was determined for each periodogram and averaged across all ROIs extracted from all projections or reconstructed slices for each patient data set. For the projections, the mean β averaged across the 55 cases was 3.06 (standard deviation of 0.21), while it was 2.87 (0.24) for the corresponding reconstructions. The difference in β for a given patient between the projection ROIs and the reconstructed ROIs averaged across the 55 cases was 0.194, which was statistically significant (p<0.001). The 95% CI for the difference between the mean value of β for the projections and reconstructions was [0.170, 0.218]. The results are consistent with the observation that the amount of breast structure in the tomosynthesis slice is reduced compared to projection mammography and that this may lead to improved lesion detectability.
International Nuclear Information System (INIS)
Parsons, G.; Ford, M.; Crisp, J.; Bernard, E.; Howman-Giles, R.
1997-01-01
Full text: DMSA renal scans are frequently requested for the diagnosis and follow-up of acute pyelonephritis and cortical scarring. This study was designed to:- 1. evaluate oblique reconstruction of DMSA SPECT over standard plane reconstruction and planar imaging; and 2. report on the technical aspects important in obtaining high quality DMSA SPECT, particularly in neonates. Over seven months, 210/231 (91 %) of DMSA scans were performed with SPECT on children from age nine days to 16 years, the median age being 2.5 years. 65 patients (31 %) were under one year and 39 (18%) were under six months. Planar and SPECT imaging with standard plane reconstruction and oblique reorientation was performed on the Siemens triple-headed gamma camera. High quality SPECT images were obtained on the smallest babies using a paediatric palette, and were of comparable quality to those of older children. At the time of reporting, the nuclear medicine physician assessed the diagnostic value of the three types of date presented: (1) planar images; (2) standard plane SPECT reconstruction; and (3) oblique SPECT reconstruction. Cortical defects were identified separately for upper, middle and lower poles. Three physicians concluded that high quality SPECT is superior to planar images when assessing the renal cortex. In addition, oblique reorientation is superior to standard reconstruction, particularly at the upper and lower poles. SPECT is now performed routinely on patients of all ages, and the oblique sagittal and coronal reorientation is now used in place of the standard reconstruction
Use of an object model in three dimensional image reconstruction. Application in medical imaging
International Nuclear Information System (INIS)
Delageniere-Guillot, S.
1993-02-01
Threedimensional image reconstruction from projections corresponds to a set of techniques which give information on the inner structure of the studied object. These techniques are mainly used in medical imaging or in non destructive evaluation. Image reconstruction is an ill-posed problem. So the inversion has to be regularized. This thesis deals with the introduction of a priori information within the reconstruction algorithm. The knowledge is introduced through an object model. The proposed scheme is applied to the medical domain for cone beam geometry. We address two specific problems. First, we study the reconstruction of high contrast objects. This can be applied to bony morphology (bone/soft tissue) or to angiography (vascular structures opacified by injection of contrast agent). With noisy projections, the filtering steps of standard methods tend to smooth the natural transitions of the investigated object. In order to regularize the reconstruction but to keep contrast, we introduce a model of classes which involves the Markov random fields theory. We develop a reconstruction scheme: analytic reconstruction-reprojection. Then, we address the case of an object changing during the acquisition. This can be applied to angiography when the contrast agent is moving through the vascular tree. The problem is then stated as a dynamic reconstruction. We define an evolution AR model and we use an algebraic reconstruction method. We represent the object at a particular moment as an intermediary state between the state of the object at the beginning and at the end of the acquisition. We test both methods on simulated and real data, and we prove how the use of an a priori model can improve the results. (author)
Prior image constrained image reconstruction in emerging computed tomography applications
Brunner, Stephen T.
Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation
Goebel, Juliane; Nensa, Felix; Bomas, Bettina; Schemuth, Haemi P; Maderwald, Stefan; Gratz, Marcel; Quick, Harald H; Schlosser, Thomas; Nassenstein, Kai
2016-12-01
Improved real-time cardiac magnetic resonance (CMR) sequences have currently been introduced, but so far only limited practical experience exists. This study aimed at image reconstruction optimization and clinical validation of a new highly accelerated real-time cine SPARSE-SENSE sequence. Left ventricular (LV) short-axis stacks of a real-time free-breathing SPARSE-SENSE sequence with high spatiotemporal resolution and of a standard segmented cine SSFP sequence were acquired at 1.5 T in 11 volunteers and 15 patients. To determine the optimal iterations, all volunteers' SPARSE-SENSE images were reconstructed using 10-200 iterations, and contrast ratios, image entropies, and reconstruction times were assessed. Subsequently, the patients' SPARSE-SENSE images were reconstructed with the clinically optimal iterations. LV volumetric values were evaluated and compared between both sequences. Sufficient image quality and acceptable reconstruction times were achieved when using 80 iterations. Bland-Altman plots and Passing-Bablok regression showed good agreement for all volumetric parameters. 80 iterations are recommended for iterative SPARSE-SENSE image reconstruction in clinical routine. Real-time cine SPARSE-SENSE yielded comparable volumetric results as the current standard SSFP sequence. Due to its intrinsic low image acquisition times, real-time cine SPARSE-SENSE imaging with iterative image reconstruction seems to be an attractive alternative for LV function analysis. • A highly accelerated real-time CMR sequence using SPARSE-SENSE was evaluated. • SPARSE-SENSE allows free breathing in real-time cardiac cine imaging. • For clinically optimal SPARSE-SENSE image reconstruction, 80 iterations are recommended. • Real-time SPARSE-SENSE imaging yielded comparable volumetric results as the reference SSFP sequence. • The fast SPARSE-SENSE sequence is an attractive alternative to standard SSFP sequences.
Image reconstruction design of industrial CT instrument for teaching
International Nuclear Information System (INIS)
Zou Yongning; Cai Yufang
2009-01-01
Industrial CT instrument for teaching is applied to teaching and study in field of physics and radiology major, image reconstruction is an important part of software on CT instrument. The paper expatiate on CT physical theory and first generation CT reconstruction algorithm, describe scan process of industrial CT instrument for teaching; analyze image artifact as result of displacement of rotation center, implement method of center displacement correcting, design and complete image reconstruction software, application shows that reconstructed image is very clear and qualitatively high. (authors)
Sparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.
She, Huajun; Chen, Rong-Rong; Liang, Dong; DiBella, Edward V R; Ying, Leslie
2014-02-01
To develop a sensitivity-based parallel imaging reconstruction method to reconstruct iteratively both the coil sensitivities and MR image simultaneously based on their prior information. Parallel magnetic resonance imaging reconstruction problem can be formulated as a multichannel sampling problem where solutions are sought analytically. However, the channel functions given by the coil sensitivities in parallel imaging are not known exactly and the estimation error usually leads to artifacts. In this study, we propose a new reconstruction algorithm, termed Sparse BLind Iterative Parallel, for blind iterative parallel imaging reconstruction using compressed sensing. The proposed algorithm reconstructs both the sensitivity functions and the image simultaneously from undersampled data. It enforces the sparseness constraint in the image as done in compressed sensing, but is different from compressed sensing in that the sensing matrix is unknown and additional constraint is enforced on the sensitivities as well. Both phantom and in vivo imaging experiments were carried out with retrospective undersampling to evaluate the performance of the proposed method. Experiments show improvement in Sparse BLind Iterative Parallel reconstruction when compared with Sparse SENSE, JSENSE, IRGN-TV, and L1-SPIRiT reconstructions with the same number of measurements. The proposed Sparse BLind Iterative Parallel algorithm reduces the reconstruction errors when compared to the state-of-the-art parallel imaging methods. Copyright © 2013 Wiley Periodicals, Inc.
Quantitative image reconstruction for total-body PET imaging using the 2-meter long EXPLORER scanner
Zhang, Xuezhu; Zhou, Jian; Cherry, Simon R.; Badawi, Ramsey D.; Qi, Jinyi
2017-03-01
The EXPLORER project aims to build a 2 meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20 min whole-body PET scan with an injection of 25 MBq 18F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.
Blind compressed sensing image reconstruction based on alternating direction method
Liu, Qinan; Guo, Shuxu
2018-04-01
In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.
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.
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 fast image reconstruction technique based on ART
International Nuclear Information System (INIS)
Zhang Shunli; Zhang Dinghua; Wang Kai; Huang Kuidong; Li Weibin
2007-01-01
Algebraic Reconstruction Technique (ART) is an iterative method for image reconstruction. Improving its reconstruction speed has been one of the important researching aspects of ART. For the simplified weight coefficients reconstruction model of ART, a fast grid traverse algorithm is proposed, which can determine the grid index by simple operations such as addition, subtraction and comparison. Since the weight coefficients are calculated at real time during iteration, large amount of storage is saved and the reconstruction speed is greatly increased. Experimental results show that the new algorithm is very effective and the reconstruction speed is improved about 10 times compared with the traditional algorithm. (authors)
Reconstruction from gamma radiography and ultrasonic images
International Nuclear Information System (INIS)
Gautier, S.; Lavayssiere, B.; Idier, J.; Mohammad-Djafari, A.
1998-02-01
This work deals with the three-dimensional reconstruction from gamma radiographic and ultrasonic images. Such an issue belongs to the field of data fusion since the data provide complementary information. The two sets of data are independently related to two sets of parameters: gamma ray attenuation and ultrasonic reflectivity. The fusion problem is addressed in a Bayesian framework; the kingpin of the task is then to define a joint a priori model for both attenuation and reflectivity. Thus, the developing of this model and the entailed joint estimation constitute the principal contribution of this work. The results of real data treatments demonstrate the validity of this method as compared to a sequential approach of the two sets of data
Simultaneous reconstruction and segmentation for dynamic SPECT imaging
International Nuclear Information System (INIS)
Burger, Martin; Rossmanith, Carolin; Zhang, Xiaoqun
2016-01-01
This work deals with the reconstruction of dynamic images that incorporate characteristic dynamics in certain subregions, as arising for the kinetics of many tracers in emission tomography (SPECT, PET). We make use of a basis function approach for the unknown tracer concentration by assuming that the region of interest can be divided into subregions with spatially constant concentration curves. Applying a regularised variational framework reminiscent of the Chan-Vese model for image segmentation we simultaneously reconstruct both the labelling functions of the subregions as well as the subconcentrations within each region. Our particular focus is on applications in SPECT with the Poisson noise model, resulting in a Kullback–Leibler data fidelity in the variational approach. We present a detailed analysis of the proposed variational model and prove existence of minimisers as well as error estimates. The latter apply to a more general class of problems and generalise existing results in literature since we deal with a nonlinear forward operator and a nonquadratic data fidelity. A computational algorithm based on alternating minimisation and splitting techniques is developed for the solution of the problem and tested on appropriately designed synthetic data sets. For those we compare the results to those of standard EM reconstructions and investigate the effects of Poisson noise in the data. (paper)
Model-Based Reconstructive Elasticity Imaging Using Ultrasound
Directory of Open Access Journals (Sweden)
Salavat R. Aglyamov
2007-01-01
Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.
An efficient algorithm for MR image reconstruction and compression
International Nuclear Information System (INIS)
Wang, Hang; Rosenfeld, D.; Braun, M.; Yan, Hong
1992-01-01
In magnetic resonance imaging (MRI), the original data are sampled in the spatial frequency domain. The sampled data thus constitute a set of discrete Fourier transform (DFT) coefficients. The image is usually reconstructed by taking inverse DFT. The image data may then be efficiently compressed using the discrete cosine transform (DCT). A method of using DCT to treat the sampled data is presented which combines two procedures, image reconstruction and data compression. This method may be particularly useful in medical picture archiving and communication systems where both image reconstruction and compression are important issues. 11 refs., 3 figs
TREE STEM RECONSTRUCTION USING VERTICAL FISHEYE IMAGES: A PRELIMINARY STUDY
Directory of Open Access Journals (Sweden)
A. Berveglieri
2016-06-01
Full Text Available A preliminary study was conducted to assess a tree stem reconstruction technique with panoramic images taken with fisheye lenses. The concept is similar to the Structure from Motion (SfM technique, but the acquisition and data preparation rely on fisheye cameras to generate a vertical image sequence with height variations of the camera station. Each vertical image is rectified to four vertical planes, producing horizontal lateral views. The stems in the lateral view are rectified to the same scale in the image sequence to facilitate image matching. Using bundle adjustment, the stems are reconstructed, enabling later measurement and extraction of several attributes. The 3D reconstruction was performed with the proposed technique and compared with SfM. The preliminary results showed that the stems were correctly reconstructed by using the lateral virtual images generated from the vertical fisheye images and with the advantage of using fewer images and taken from one single station.
MRI reconstruction of multi-image acquisitions using a rank regularizer with data reordering
Energy Technology Data Exchange (ETDEWEB)
Adluru, Ganesh, E-mail: gadluru@gmail.com; Anderson, Jeffrey [UCAIR, Department of Radiology, University of Utah, Salt Lake City, Utah 84108 (United States); Gur, Yaniv [IBM Almaden Research Center, San Jose, California 95120 (United States); Chen, Liyong; Feinberg, David [Advanced MRI Technologies, Sebastpool, California, 95472 (United States); DiBella, Edward V. R. [UCAIR, Department of Radiology, University of Utah, Salt Lake City, Utah 84108 and Department of Bioengineering, University of Utah, Salt Lake City, Utah 84112 (United States)
2015-08-15
Purpose: To improve rank constrained reconstructions for undersampled multi-image MRI acquisitions. Methods: Motivated by the recent developments in low-rank matrix completion theory and its applicability to rapid dynamic MRI, a new reordering-based rank constrained reconstruction of undersampled multi-image data that uses prior image information is proposed. Instead of directly minimizing the nuclear norm of a matrix of estimated images, the nuclear norm of reordered matrix values is minimized. The reordering is based on the prior image estimates. The method is tested on brain diffusion imaging data and dynamic contrast enhanced myocardial perfusion data. Results: Good quality images from data undersampled by a factor of three for diffusion imaging and by a factor of 3.5 for dynamic cardiac perfusion imaging with respiratory motion were obtained. Reordering gave visually improved image quality over standard nuclear norm minimization reconstructions. Root mean squared errors with respect to ground truth images were improved by ∼18% and ∼16% with reordering for diffusion and perfusion applications, respectively. Conclusions: The reordered low-rank constraint is a way to inject prior image information that offers improvements over a standard low-rank constraint for undersampled multi-image MRI reconstructions.
MRI reconstruction of multi-image acquisitions using a rank regularizer with data reordering
International Nuclear Information System (INIS)
Adluru, Ganesh; Anderson, Jeffrey; Gur, Yaniv; Chen, Liyong; Feinberg, David; DiBella, Edward V. R.
2015-01-01
Purpose: To improve rank constrained reconstructions for undersampled multi-image MRI acquisitions. Methods: Motivated by the recent developments in low-rank matrix completion theory and its applicability to rapid dynamic MRI, a new reordering-based rank constrained reconstruction of undersampled multi-image data that uses prior image information is proposed. Instead of directly minimizing the nuclear norm of a matrix of estimated images, the nuclear norm of reordered matrix values is minimized. The reordering is based on the prior image estimates. The method is tested on brain diffusion imaging data and dynamic contrast enhanced myocardial perfusion data. Results: Good quality images from data undersampled by a factor of three for diffusion imaging and by a factor of 3.5 for dynamic cardiac perfusion imaging with respiratory motion were obtained. Reordering gave visually improved image quality over standard nuclear norm minimization reconstructions. Root mean squared errors with respect to ground truth images were improved by ∼18% and ∼16% with reordering for diffusion and perfusion applications, respectively. Conclusions: The reordered low-rank constraint is a way to inject prior image information that offers improvements over a standard low-rank constraint for undersampled multi-image MRI reconstructions
Superiority of CT imaging reconstruction on Linux OS
International Nuclear Information System (INIS)
Lin Shaochun; Yan Xufeng; Wu Tengfang; Luo Xiaomei; Cai Huasong
2010-01-01
Objective: To compare the speed of CT reconstruction using the Linux and Windows OS. Methods: Shepp-Logan head phantom in different pixel size was projected to obtain the sinogram by using the inverse Fourier transformation, filtered back projection and Radon transformation on both Linux and Windows OS. Results: CT image reconstruction using the Linux operating system was significantly better and more efficient than Windows. Conclusion: CT image reconstruction using the Linux operating system is more efficient. (authors)
3D Reconstruction of NMR Images by LabVIEW
Directory of Open Access Journals (Sweden)
Peter IZAK
2007-01-01
Full Text Available This paper introduces the experiment of 3D reconstruction NMR images via virtual instrumentation - LabVIEW. The main idea is based on marching cubes algorithm and image processing implemented by module of Vision assistant. The two dimensional images shot by the magnetic resonance device provide information about the surface properties of human body. There is implemented algorithm which can be used for 3D reconstruction of magnetic resonance images in biomedical application.
Reconstruction of Optical Thickness from Hoffman Modulation Contrast Images
DEFF Research Database (Denmark)
Olsen, Niels Holm; Sporring, Jon; Nielsen, Mads
2003-01-01
Hoffman microscopy imaging systems are part of numerous fertility clinics world-wide. We discuss the physics of the Hoffman imaging system from optical thickness to image intensity, implement a simple, yet fast, reconstruction algorithm using Fast Fourier Transformation and discuss the usability...... of the method on a number of cells from a human embryo. Novelty is identifying the non-linearity of a typical Hoffman imaging system, and the application of Fourier Transformation to reconstruct the optical thickness....
International Nuclear Information System (INIS)
Walsh, C.; Johnston, C.; Sheehy, N.; Reilly, G. O.
2013-01-01
In this study the quantitative and qualitative image quality (IQ) measurements with clinical judgement of IQ in positron emission tomography (PET) were compared. The limitations of IQ metrics and the proposed criteria of acceptability for PET scanners are discussed. Phantom and patient images were reconstructed using seven different iterative reconstruction protocols. For each reconstructed set of images, IQ was scored based both on the visual analysis and on the quantitative metrics. The quantitative physics metrics did not rank the reconstruction protocols in the same order as the clinicians' scoring of perceived IQ (R s = -0.54). Better agreement was achieved when comparing the clinical perception of IQ to the physicist's visual assessment of IQ in the phantom images (R s = +0.59). The closest agreement was seen between the quantitative physics metrics and the measurement of the standard uptake values (SUVs) in small tumours (R s = +0.92). Given the disparity between the clinical perception of IQ and the physics metrics a cautious approach to use of IQ measurements for determining suspension levels is warranted. (authors)
3D reconstruction based on light field images
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.
Low dose reconstruction algorithm for differential phase contrast imaging.
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.
Longitudinal and transverse digital image reconstruction with a tomographic scanner
International Nuclear Information System (INIS)
Pickens, D.R.; Price, R.R.; Erickson, J.J.; Patton, J.A.; Partain, C.L.; Rollo, F.D.
1981-01-01
A Siemens Gammasonics PHO/CON-192 Multiplane Imager is interfaced to a digital computer for the purpose of performing tomographic reconstructions from the data collected during a single scan. Data from the two moving gamma cameras as well as camera position information are sent to the computer by an interface designed in the authors' laboratory. Backprojection reconstruction is implemented by the computer. Longitudinal images in whole-body format as well as smaller formats are reconstructed for up to six planes simultaneously from the list mode data. Transverse reconstructions are demonstrated for 201 T1 myocardial scans. Post-reconstruction deconvolution processing to remove the blur artifact (characteristic of focal plane tomography) is applied to a multiplane phantom. Digital data acquisition of data and reconstruction of images are practical, and can extend the usefulness of the machine when compared with the film output (author)
Gadgetron: An Open Source Framework for Medical Image Reconstruction
DEFF Research Database (Denmark)
Hansen, Michael Schacht; Sørensen, Thomas Sangild
2013-01-01
This work presents a new open source framework for medical image reconstruction called the “Gadgetron.” The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or “Gadgets” from raw data to reconstructed images...... with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its...
Reconstruction CT imaging of the hypopharynx and the larynx
International Nuclear Information System (INIS)
Okuno, Tetsuji; Fujimura, Akiko; Murakami, Yasushi; Shiga, Hayao
1986-01-01
The multiplanar reconstruction CT imaging of the hypopharynx and the larynx was performed on a total of 20 cases: 8 with laryngeal carcinomas, 6 with hypopharyngeal carcinomas, 4 with vocal cord paralyses due to various causes, 1 with laryngeal amyloidosis, 1 with inflammatory granuloma of the hypopharynx. Coronal, segittal, and parasagittal reconstruction images were obtained from either 1 or 2 mm overlapping axial scans with 4 or 5 mm slice thickness (3 cases) using 5 sec scan times during queit breathing. In 15 cases with coronal reconstruction imaging, the anatomical derangements of the laryngopharyngeal structures especially along the undersurface of the true vocal cord to the false cord level, the lateral wall of the pyriform sinus, and the paraglottic space were demonstrated more clearly than the axial CT imaging. In 5 cases with sagittal reconstruction imaging, the vertical extension of the lesions through the anterior commisure was more clearly depicted than the axial CT imaging. In 8 cases with parasagittal reconstruction imaging, which is along the vocal fold or across the aryepiglottic fold, pathological changes along the aryepiglottic fold, the arytenoid-corniculate cartilage complex, and the tip of the pyriform sinus were more clearly demonstrated than the axial CT imaging. In determining the feasibility of conservation surgery of the larynx and the hypopharynx, reconstruction CT imaging is recommended as the diagnostic procedure of a choice, which would supplement the findings of the routine axial CT imaging. (author)
Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU.
Arefan, D; Talebpour, A; Ahmadinejhad, N; Kamali Asl, A
2015-06-01
Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU). At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU) card and the Graphics Processing Unit (GPU). It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU).
Van de Casteele, Elke; Parizel, Paul; Sijbers, Jan
2012-03-01
Adaptive statistical iterative reconstruction (ASiR) is a new reconstruction algorithm used in the field of medical X-ray imaging. This new reconstruction method combines the idealized system representation, as we know it from the standard Filtered Back Projection (FBP) algorithm, and the strength of iterative reconstruction by including a noise model in the reconstruction scheme. It studies how noise propagates through the reconstruction steps, feeds this model back into the loop and iteratively reduces noise in the reconstructed image without affecting spatial resolution. In this paper the effect of ASiR on the contrast to noise ratio is studied using the low contrast module of the Catphan phantom. The experiments were done on a GE LightSpeed VCT system at different voltages and currents. The results show reduced noise and increased contrast for the ASiR reconstructions compared to the standard FBP method. For the same contrast to noise ratio the images from ASiR can be obtained using 60% less current, leading to a reduction in dose of the same amount.
A two-step Hilbert transform method for 2D image reconstruction
International Nuclear Information System (INIS)
Noo, Frederic; Clackdoyle, Rolf; Pack, Jed D
2004-01-01
The paper describes a new accurate two-dimensional (2D) image reconstruction method consisting of two steps. In the first step, the backprojected image is formed after taking the derivative of the parallel projection data. In the second step, a Hilbert filtering is applied along certain lines in the differentiated backprojection (DBP) image. Formulae for performing the DBP step in fan-beam geometry are also presented. The advantage of this two-step Hilbert transform approach is that in certain situations, regions of interest (ROIs) can be reconstructed from truncated projection data. Simulation results are presented that illustrate very similar reconstructed image quality using the new method compared to standard filtered backprojection, and that show the capability to correctly handle truncated projections. In particular, a simulation is presented of a wide patient whose projections are truncated laterally yet for which highly accurate ROI reconstruction is obtained
International Nuclear Information System (INIS)
Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc
2017-01-01
Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides
Energy Technology Data Exchange (ETDEWEB)
Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc [German Cancer Research Center, Heidelberg (Germany).
2017-10-01
Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides
Wavelet/scalar quantization compression standard for fingerprint images
Energy Technology Data Exchange (ETDEWEB)
Brislawn, C.M.
1996-06-12
US Federal Bureau of Investigation (FBI) has recently formulated a national standard for digitization and compression of gray-scale fingerprint images. Fingerprints are scanned at a spatial resolution of 500 dots per inch, with 8 bits of gray-scale resolution. The compression algorithm for the resulting digital images is based on adaptive uniform scalar quantization of a discrete wavelet transform subband decomposition (wavelet/scalar quantization method). The FBI standard produces archival-quality images at compression ratios of around 15 to 1 and will allow the current database of paper fingerprint cards to be replaced by digital imagery. The compression standard specifies a class of potential encoders and a universal decoder with sufficient generality to reconstruct compressed images produced by any compliant encoder, allowing flexibility for future improvements in encoder technology. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.
Accelerated gradient methods for total-variation-based CT image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Joergensen, Jakob H.; Hansen, Per Christian [Technical Univ. of Denmark, Lyngby (Denmark). Dept. of Informatics and Mathematical Modeling; Jensen, Tobias L.; Jensen, Soeren H. [Aalborg Univ. (Denmark). Dept. of Electronic Systems; Sidky, Emil Y.; Pan, Xiaochuan [Chicago Univ., Chicago, IL (United States). Dept. of Radiology
2011-07-01
Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-intensive methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits prohibitively slow convergence. In the present work we address the question of how to reduce the number of gradient method iterations needed to achieve a high-accuracy TV reconstruction. We consider the use of two accelerated gradient-based methods, GPBB and UPN, to solve the 3D-TV minimization problem in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the standard gradient method. (orig.)
Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)
McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian
2006-03-01
To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the
Directory of Open Access Journals (Sweden)
Oliver S Grosser
Full Text Available Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT or positron emission tomography (PET with computed tomography (CT. Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR on the image quality of the low-dose CT images.Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88 and the contrast-to-noise ratio (CNR was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04. In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001.In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.
Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging
International Nuclear Information System (INIS)
Virador, Patrick R.G.
2000-01-01
The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data
Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging
Energy Technology Data Exchange (ETDEWEB)
Virador, Patrick R.G. [Univ. of California, Berkeley, CA (United States)
2000-04-01
The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data
Simbol-X Formation Flight and Image Reconstruction
Civitani, M.; Djalal, S.; Le Duigou, J. M.; La Marle, O.; Chipaux, R.
2009-05-01
Simbol-X is the first operational mission relying on two satellites flying in formation. The dynamics of the telescope, due to the formation flight concept, raises a variety of problematic, like image reconstruction, that can be better evaluated via a simulation tools. We present here the first results obtained with Simulos, simulation tool aimed to study the relative spacecrafts navigation and the weight of the different parameters in image reconstruction and telescope performance evaluation. The simulation relies on attitude and formation flight sensors models, formation flight dynamics and control, mirror model and focal plane model, while the image reconstruction is based on the Line of Sight (LOS) concept.
International Nuclear Information System (INIS)
Chang, L.T.
1976-05-01
Two techniques for radionuclide imaging and reconstruction have been studied;; both are used for improvement of depth resolution. The first technique is called coded aperture imaging, which is a technique of tomographic imaging. The second technique is a special 3-D image reconstruction method which is introduced as an improvement to the so called focal-plane tomography
Surface Reconstruction and Image Enhancement via $L^1$-Minimization
Dobrev, Veselin
2010-01-01
A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright © by SIAM.
Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Weavers, Paul T; Huston, John; Gray, Erin M; Bernstein, Matt A
2016-06-01
To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction. Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data were performed to investigate the spatial resolution benefit of integrated GNL correction over conventional postreconstruction correction. Phantom and in vivo results demonstrate that the integrated GNL correction reduces the image blurring introduced by the conventional GNL correction, while still correcting GNL-induced coarse-scale geometrical distortion. Images generated from undersampled data using the proposed integrated GNL strategies offer superior depiction of fine image detail, for example, phantom resolution inserts and anatomical tissue boundaries. Noniterative partial Fourier and parallel imaging reconstruction methods with integrated GNL correction reduce the resolution loss that occurs during conventional postreconstruction GNL correction while preserving the computational efficiency of standard reconstruction techniques. Magn Reson Med 75:2534-2544, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm
Elahi, Sana; kaleem, Muhammad; Omer, Hammad
2018-01-01
Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.
Algorithms for Reconstruction of Undersampled Atomic Force Microscopy Images Supplementary Material
DEFF Research Database (Denmark)
2017-01-01
Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods.......Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods....
Total variation regularization in measurement and image space for PET reconstruction
Burger, M
2014-09-18
© 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.
A Kalman filter technique applied for medical image reconstruction
International Nuclear Information System (INIS)
Goliaei, S.; Ghorshi, S.; Manzuri, M. T.; Mortazavi, M.
2011-01-01
Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Image reconstruction is essential for medical images for some applications such as suppression of noise or de-blurring the image in order to provide images with better quality and contrast. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as the most popular one known as filtered back projection. In this paper we introduce a Kalman filter technique which is operated in time domain for medical image reconstruction. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of reconstructed image becomes better in terms of contract and transparency. It is also seen that as the number of projection increases the error index decreases.
CT Image Reconstruction in a Low Dimensional Manifold
Cong, Wenxiang; Wang, Ge; Yang, Qingsong; Hsieh, Jiang; Li, Jia; Lai, Rongjie
2017-01-01
Regularization methods are commonly used in X-ray CT image reconstruction. Different regularization methods reflect the characterization of different prior knowledge of images. In a recent work, a new regularization method called a low-dimensional manifold model (LDMM) is investigated to characterize the low-dimensional patch manifold structure of natural images, where the manifold dimensionality characterizes structural information of an image. In this paper, we propose a CT image reconstruc...
Sparse reconstruction by means of the standard Tikhonov regularization
International Nuclear Information System (INIS)
Lu Shuai; Pereverzev, Sergei V
2008-01-01
It is a common belief that Tikhonov scheme with || · ||L 2 -penalty fails in sparse reconstruction. We are going to show, however, that this standard regularization can help if the stability measured in L 1 -norm will be properly taken into account in the choice of the regularization parameter. The crucial point is that now a stability bound may depend on the bases with respect to which the solution of the problem is assumed to be sparse. We discuss how such a stability can be estimated numerically and present the results of computational experiments giving the evidence of the reliability of our approach.
1024 matrix image reconstruction: usefulness in high resolution chest CT
International Nuclear Information System (INIS)
Jeong, Sun Young; Chung, Myung Jin; Chong, Se Min; Sung, Yon Mi; Lee, Kyung Soo
2006-01-01
We tried to evaluate whether high resolution chest CT with a 1,024 matrix has a significant advantage in image quality compared to a 512 matrix. Each set of 512 and 1024 matrix high resolution chest CT scans with both 0.625 mm and 1.25 mm slice thickness were obtained from 26 patients. Seventy locations that contained twenty-four low density lesions without sharp boundary such as emphysema, and forty-six sharp linear densities such as linear fibrosis were selected; these were randomly displayed on a five mega pixel LCD monitor. All the images were masked for information concerning the matrix size and slice thickness. Two chest radiologists scored the image quality of each ar rowed lesion as follows: (1) undistinguishable, (2) poorly distinguishable, (3) fairly distinguishable, (4) well visible and (5) excellently visible. The scores were compared from the aspects of matrix size, slice thickness and the different observers by using ANOVA tests. The average and standard deviation of image quality were 3.09 (± .92) for the 0.625 mm x 512 matrix, 3.16 (± .84) for the 0.625 mm x 1024 matrix, 2.49 (± 1.02) for the 1.25 mm x 512 matrix, and 2.35 (± 1.02) for the 1.25 mm x 1024 matrix, respectively. The image quality on both matrices of the high resolution chest CT scans with a 0.625 mm slice thickness was significantly better than that on the 1.25 mm slice thickness (ρ < 0.001). However, the image quality on the 1024 matrix high resolution chest CT scans was not significantly different from that on the 512 matrix high resolution chest CT scans (ρ = 0.678). The interobserver variation between the two observers was not significant (ρ = 0.691). We think that 1024 matrix image reconstruction for high resolution chest CT may not be clinical useful
A study of transverse image reconstruction with digital subtraction angiography
International Nuclear Information System (INIS)
Sakamoto, Kiyoshi; Kotoura, Noriko; Terasawa, Yuuji; Oda, Masahiko; Gotou, Hiroshi; Nasada, Toshiya; Tanooka, Masao
1995-01-01
For digital subtraction angiography (DSA) with C-type equipment, it is possible to radiate an X-ray during rotation and to collect data at different angular settings. We tried to reconstruct transverse image from data obtained by scanning DSA images at different angular settings. 88 projection data were obtained by rotating the object at 180deg during radiation. Reconstruction was made using the convolution method with pixel value distribution for each projection. Similarly, the image quality of the reconstructed images were compared with the unsubtracted and subtracted ones. In case a part object was outside the calculating region, artifacts were generally produced. However, the artifacts were reduced by subtracting the background from the image. In addition, the cupping phenomenon caused by beam hardening was relaxed and high-quality imaging could be achieved. This method will become even more effective, if we will use it with selective angiography in which the limited area is enhanced. (author)
Super-Resolution Image Reconstruction Applied to Medical Ultrasound
Ellis, Michael
Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in
Energy Technology Data Exchange (ETDEWEB)
Notohamiprodjo, S.; Deak, Z.; Meurer, F.; Maertz, F.; Mueck, F.G.; Geyer, L.L.; Wirth, S. [Ludwig-Maximilians University Hospital of Munich, Institute for Clinical Radiology, Munich (Germany)
2015-01-15
The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. (orig.)
International Nuclear Information System (INIS)
Notohamiprodjo, S.; Deak, Z.; Meurer, F.; Maertz, F.; Mueck, F.G.; Geyer, L.L.; Wirth, S.
2015-01-01
The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. (orig.)
High spatial resolution CT image reconstruction using parallel computing
International Nuclear Information System (INIS)
Yin Yin; Liu Li; Sun Gongxing
2003-01-01
Using the PC cluster system with 16 dual CPU nodes, we accelerate the FBP and OR-OSEM reconstruction of high spatial resolution image (2048 x 2048). Based on the number of projections, we rewrite the reconstruction algorithms into parallel format and dispatch the tasks to each CPU. By parallel computing, the speedup factor is roughly equal to the number of CPUs, which can be up to about 25 times when 25 CPUs used. This technique is very suitable for real-time high spatial resolution CT image reconstruction. (authors)
Energy Technology Data Exchange (ETDEWEB)
Kuhnert, Georg; Sterzer, Sergej; Kahraman, Deniz; Dietlein, Markus; Drzezga, Alexander; Kobe, Carsten [University Hospital of Cologne, Department of Nuclear Medicine, Cologne (Germany); Boellaard, Ronald [VU University Medical Centre, Department of Radiology and Nuclear Medicine, Amsterdam (Netherlands); Scheffler, Matthias; Wolf, Juergen [University Hospital of Cologne, Lung Cancer Group Cologne, Department I of Internal Medicine, Center for Integrated Oncology Cologne Bonn, Cologne (Germany)
2016-02-15
In oncological imaging using PET/CT, the standardized uptake value has become the most common parameter used to measure tracer accumulation. The aim of this analysis was to evaluate ultra high definition (UHD) and ordered subset expectation maximization (OSEM) PET/CT reconstructions for their potential impact on quantification. We analyzed 40 PET/CT scans of lung cancer patients who had undergone PET/CT. Standardized uptake values corrected for body weight (SUV) and lean body mass (SUL) were determined in the single hottest lesion in the lung and normalized to the liver for UHD and OSEM reconstruction. Quantitative uptake values and their normalized ratios for the two reconstruction settings were compared using the Wilcoxon test. The distribution of quantitative uptake values and their ratios in relation to the reconstruction method used were demonstrated in the form of frequency distribution curves, box-plots and scatter plots. The agreement between OSEM and UHD reconstructions was assessed through Bland-Altman analysis. A significant difference was observed after OSEM and UHD reconstruction for SUV and SUL data tested (p < 0.0005 in all cases). The mean values of the ratios after OSEM and UHD reconstruction showed equally significant differences (p < 0.0005 in all cases). Bland-Altman analysis showed that the SUV and SUL and their normalized values were, on average, up to 60 % higher after UHD reconstruction as compared to OSEM reconstruction. OSEM and HD reconstruction brought a significant difference for SUV and SUL, which remained constantly high after normalization to the liver, indicating that standardization of reconstruction and the use of comparable SUV measurements are crucial when using PET/CT. (orig.)
Application of Super-Resolution Image Reconstruction to Digital Holography
Directory of Open Access Journals (Sweden)
Zhang Shuqun
2006-01-01
Full Text Available We describe a new application of super-resolution image reconstruction to digital holography which is a technique for three-dimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a high-resolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique.
Fingerprint image reconstruction for swipe sensor using Predictive Overlap Method
Directory of Open Access Journals (Sweden)
Mardiansyah Ahmad Zafrullah
2018-01-01
Full Text Available Swipe sensor is one of many biometric authentication sensor types that widely applied to embedded devices. The sensor produces an overlap on every pixel block of the image, so the picture requires a reconstruction process before heading to the feature extraction process. Conventional reconstruction methods require extensive computation, causing difficult to apply to embedded devices that have limited computing process. In this paper, image reconstruction is proposed using predictive overlap method, which determines the image block shift from the previous set of change data. The experiments were performed using 36 images generated by a swipe sensor with 128 x 8 pixels size of the area, where each image has an overlap in each block. The results reveal computation can increase up to 86.44% compared with conventional methods, with accuracy decreasing to 0.008% in average.
Quantitative reconstruction from a single diffraction-enhanced image
International Nuclear Information System (INIS)
Paganin, D.M.; Lewis, R.A.; Kitchen, M.
2003-01-01
Full text: We develop an algorithm for using a single diffraction-enhanced image (DEI) to obtain a quantitative reconstruction of the projected thickness of a single-material sample which is embedded within a substrate of approximately constant thickness. This algorithm is used to quantitatively map inclusions in a breast phantom, from a single synchrotron DEI image. In particular, the reconstructed images quantitatively represent the projected thickness in the bulk of the sample, in contrast to DEI images which greatly emphasise sharp edges (high spatial frequencies). In the context of an ultimate aim of improved methods for breast cancer detection, the reconstructions are potentially of greater diagnostic value compared to the DEI data. Lastly, we point out that the methods of analysis presented here are also applicable to the quantitative analysis of differential interference contrast (DIC) images
Matrix-based image reconstruction methods for tomography
International Nuclear Information System (INIS)
Llacer, J.; Meng, J.D.
1984-10-01
Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures
Egger, Robert; Narayanan, Rajeevan T.; Helmstaedter, Moritz; de Kock, Christiaan P. J.; Oberlaender, Marcel
2012-01-01
The three-dimensional (3D) structure of neural circuits is commonly studied by reconstructing individual or small groups of neurons in separate preparations. Investigation of structural organization principles or quantification of dendritic and axonal innervation thus requires integration of many reconstructed morphologies into a common reference frame. Here we present a standardized 3D model of the rat vibrissal cortex and introduce an automated registration tool that allows for precise placement of single neuron reconstructions. We (1) developed an automated image processing pipeline to reconstruct 3D anatomical landmarks, i.e., the barrels in Layer 4, the pia and white matter surfaces and the blood vessel pattern from high-resolution images, (2) quantified these landmarks in 12 different rats, (3) generated an average 3D model of the vibrissal cortex and (4) used rigid transformations and stepwise linear scaling to register 94 neuron morphologies, reconstructed from in vivo stainings, to the standardized cortex model. We find that anatomical landmarks vary substantially across the vibrissal cortex within an individual rat. In contrast, the 3D layout of the entire vibrissal cortex remains remarkably preserved across animals. This allows for precise registration of individual neuron reconstructions with approximately 30 µm accuracy. Our approach could be used to reconstruct and standardize other anatomically defined brain areas and may ultimately lead to a precise digital reference atlas of the rat brain. PMID:23284282
Three dimensional image reconstruction in the Fourier domain
International Nuclear Information System (INIS)
Stearns, C.W.; Chesler, D.A.; Brownell, G.L.
1987-01-01
Filtered backprojection reconstruction algorithms are based upon the relationship between the Fourier transform of the imaged object and the Fourier transforms of its projections. A new reconstruction algorithm has been developed which performs the image assembly operation in Fourier space, rather than in image space by backprojection. This represents a significant decrease in the number of operations required to assemble the image. The new Fourier domain algorithm has resolution comparable to the filtered backprojection algorithm, and, after correction by a pointwise multiplication, demonstrates proper recovery throughout image space. Although originally intended for three-dimensional imaging applications, the Fourier domain algorithm can also be developed for two-dimensional imaging applications such as planar positron imaging systems
Photoelectron holography with improved image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Matsushita, Tomohiro, E-mail: matusita@spring8.or.j [Japan Synchrotron Radiation Research Institute (JASRI), SPring-8, 1-1-1 Kouto, Sayo-cho, Sayo-gun Hyogo 679-5198 (Japan); Matsui, Fumihiko; Daimon, Hiroshi [Nara Institute of Science and Technology (NAIST), 8916-5 Takayama, Ikoma, Nara 630-0192 (Japan); Hayashi, Kouichi [Institute for Materials Research, Tohoku University, Sendai 980-8577 (Japan)
2010-05-15
Electron holography is a type of atomic structural analysis, and it has unique features such as element selectivity and the ability to analyze the structure around an impurity in a crystal. In this paper, we introduce the measurement system, electron holograms, a theory for the recording process of an electron hologram, and a theory for the reconstruction algorithm. We describe photoelectron holograms, Auger electron holograms, and the inverse mode of an electron hologram. The reconstruction algorithm, scattering pattern extraction algorithm (SPEA), the SPEA with maximum entropy method (SPEA-MEM), and SPEA-MEM with translational operation are also described.
Photoelectron holography with improved image reconstruction
International Nuclear Information System (INIS)
Matsushita, Tomohiro; Matsui, Fumihiko; Daimon, Hiroshi; Hayashi, Kouichi
2010-01-01
Electron holography is a type of atomic structural analysis, and it has unique features such as element selectivity and the ability to analyze the structure around an impurity in a crystal. In this paper, we introduce the measurement system, electron holograms, a theory for the recording process of an electron hologram, and a theory for the reconstruction algorithm. We describe photoelectron holograms, Auger electron holograms, and the inverse mode of an electron hologram. The reconstruction algorithm, scattering pattern extraction algorithm (SPEA), the SPEA with maximum entropy method (SPEA-MEM), and SPEA-MEM with translational operation are also described.
Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging
Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar
2015-01-01
Diffusion Spectrum Imaging (DSI) reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation (TV) transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using Matlab running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using Principal Component Analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466
Fast dictionary-based reconstruction for diffusion spectrum imaging.
Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar
2013-11-01
Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.
International Nuclear Information System (INIS)
Gerischer, R.
1987-01-01
The described technique for three-dimensional image reconstruction from ECT sections is based on a simple procedure, which can be carried out with the aid of any standard-type computer used in nuclear medicine and requires no sophisticated arithmetic approach. (TRV) [de
Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis
DEFF Research Database (Denmark)
Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan
2012-01-01
Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization s...
Analytic 3D image reconstruction using all detected events
International Nuclear Information System (INIS)
Kinahan, P.E.; Rogers, J.G.
1988-11-01
We present the results of testing a previously presented algorithm for three-dimensional image reconstruction that uses all gamma-ray coincidence events detected by a PET volume-imaging scanner. By using two iterations of an analytic filter-backprojection method, the algorithm is not constrained by the requirement of a spatially invariant detector point spread function, which limits normal analytic techniques. Removing this constraint allows the incorporation of all detected events, regardless of orientation, which improves the statistical quality of the final reconstructed image
Three-dimensional image reconstruction. I. Determination of pattern orientation
International Nuclear Information System (INIS)
Blankenbecler, Richard
2004-01-01
The problem of determining the Euler angles of a randomly oriented three-dimensional (3D) object from its 2D Fraunhofer diffraction patterns is discussed. This problem arises in the reconstruction of a positive semidefinite 3D object using oversampling techniques. In such a problem, the data consist of a measured set of magnitudes from 2D tomographic images of the object at several unknown orientations. After the orientation angles are determined, the object itself can then be reconstructed by a variety of methods using oversampling, the magnitude data from the 2D images, physical constraints on the image, and then iteration to determine the phases
Few-view image reconstruction with dual dictionaries
International Nuclear Information System (INIS)
Lu Yang; Zhao Jun; Wang Ge
2012-01-01
In this paper, we formulate the problem of computed tomography (CT) under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively. Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV. (paper)
Bayesian image reconstruction for improving detection performance of muon tomography.
Wang, Guobao; Schultz, Larry J; Qi, Jinyi
2009-05-01
Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.
A low-count reconstruction algorithm for Compton-based prompt gamma imaging
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.
Evaluation of aortocoronary bypass graft patency by reconstructed CT image
International Nuclear Information System (INIS)
Kawakita, Seizaburo; Koide, Takashi; Saito, Yoshio; Yamamoto, Tadao; Iwasaki, Tadaaki
1982-01-01
Ten patients were examined in the period of three months from January to March 1981. The patients were operated from 1 month to 7 years before CT. A bypass to the left anterior descending artery (LAD) was grafted in 10 cases, 2 to the right coronary artery (RCA), 4 to an obtuse marginal artery (OM), and 1 to a diagonal artery. Image reconstruction was performed in 10 cases by using an image analytical computer Evaluskop. Appropriate planes for reconstruction were selected by trial and error methods upon observation of CT images. When gained picture of a graft course coincided with surgical records or angiography, the work of building images was concluded. On cross section, grafts to LAD were visualized in all 10 cases: 9 in the entire course and 1 in a proximal part of the graft. Two to RCA, 4 to OM and 1 to a diagonal were also successfully visualized. Reconstruction of graft images succeeded in 9 grafts of 6 cases. The course of a graft could be pursued from the proximal to the distal end adjacent to the cardiac chamber. The picture of a bypass to LAD was visualized in 6 of 10 grafts. Two bypass to RCA could be depicted, and 1 to OM was also found. However 3 to OM and 1 to a diagonal failed to be visualized throughout their courses in reconstructed images. I think that the causes of faillure mainly depended upon the course of the graft. When a graft was running arc-like surrounding the heart chamber, it was very difficult to depict its entire length in reconstructed images, though the graft could be detected in cross sections. These preliminary studies indicated that reconstruction of CT images had some benefits for the pursuit of graft courses. (J.P.N.)
3.5D dynamic PET image reconstruction incorporating kinetics-based clusters
International Nuclear Information System (INIS)
Lu Lijun; Chen Wufan; Karakatsanis, Nicolas A; Rahmim, Arman; Tang Jing
2012-01-01
Standard 3D dynamic positron emission tomographic (PET) imaging consists of independent image reconstructions of individual frames followed by application of appropriate kinetic model to the time activity curves at the voxel or region-of-interest (ROI). The emerging field of 4D PET reconstruction, by contrast, seeks to move beyond this scheme and incorporate information from multiple frames within the image reconstruction task. Here we propose a novel reconstruction framework aiming to enhance quantitative accuracy of parametric images via introduction of priors based on voxel kinetics, as generated via clustering of preliminary reconstructed dynamic images to define clustered neighborhoods of voxels with similar kinetics. This is then followed by straightforward maximum a posteriori (MAP) 3D PET reconstruction as applied to individual frames; and as such the method is labeled ‘3.5D’ image reconstruction. The use of cluster-based priors has the advantage of further enhancing quantitative performance in dynamic PET imaging, because: (a) there are typically more voxels in clusters than in conventional local neighborhoods, and (b) neighboring voxels with distinct kinetics are less likely to be clustered together. Using realistic simulated 11 C-raclopride dynamic PET data, the quantitative performance of the proposed method was investigated. Parametric distribution-volume (DV) and DV ratio (DVR) images were estimated from dynamic image reconstructions using (a) maximum-likelihood expectation maximization (MLEM), and MAP reconstructions using (b) the quadratic prior (QP-MAP), (c) the Green prior (GP-MAP) and (d, e) two proposed cluster-based priors (CP-U-MAP and CP-W-MAP), followed by graphical modeling, and were qualitatively and quantitatively compared for 11 ROIs. Overall, the proposed dynamic PET reconstruction methodology resulted in substantial visual as well as quantitative accuracy improvements (in terms of noise versus bias performance) for parametric DV
A neural network image reconstruction technique for electrical impedance tomography
International Nuclear Information System (INIS)
Adler, A.; Guardo, R.
1994-01-01
Reconstruction of Images in Electrical Impedance Tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically ill-conditioned and requires either simplifying assumptions or regularization based on a priori knowledge. This paper presents a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse problem directly from finite element simulations of the forward problem. This inverse is adapted to the geometry of the medium and the signal-to-noise ratio (SNR) used during network training. Results show good conductivity reconstruction where measurement SNR is similar to the training conditions. The advantages of this method are its conceptual simplicity and ease of implementation, and the ability to control the compromise between the noise performance and resolution of the image reconstruction
Biologically inspired EM image alignment and neural reconstruction.
Knowles-Barley, Seymour; Butcher, Nancy J; Meinertzhagen, Ian A; Armstrong, J Douglas
2011-08-15
Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden. Here, we present an alternative computational approach for ssTEM image analysis. We have used biologically inspired receptive fields as a basis for a ridge detection algorithm to identify cell membranes, synaptic contacts and mitochondria. Detected line segments are used to improve alignment between consecutive images and we have joined small segments of membrane into cell surfaces using a dynamic programming algorithm similar to the Needleman-Wunsch and Smith-Waterman DNA sequence alignment procedures. A shortest path-based approach has been used to close edges and achieve image segmentation. Partial reconstructions were automatically generated and used as a basis for semi-automatic reconstruction of neural tissue. The accuracy of partial reconstructions was evaluated and 96% of membrane could be identified at the cost of 13% false positive detections. An open-source reference implementation is available in the Supplementary information. seymour.kb@ed.ac.uk; douglas.armstrong@ed.ac.uk Supplementary data are available at Bioinformatics online.
Prospective regularization design in prior-image-based reconstruction
International Nuclear Information System (INIS)
Dang, Hao; Siewerdsen, Jeffrey H; Stayman, J Webster
2015-01-01
Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in
Image interface in Java for tomographic reconstruction in nuclear medicine
International Nuclear Information System (INIS)
Andrade, M.A.; Silva, A.M. Marques da
2004-01-01
The aim of this study is to implement a software for tomographic reconstruction of SPECT data from Nuclear Medicine with a flexible interface design, cross-platform, written in Java. Validation tests were performed based on SPECT simulated data. The results showed that the implemented algorithms and filters agree with the theoretical context. We intend to extend the system by implementing additional tomographic reconstruction techniques and Java threads, in order to provide simultaneously image processing. (author)
Image Reconstruction For Bioluminescence Tomography From Partial Measurement
Jiang, M.; Zhou, T.; Cheng, J. T.; Cong, W. X.; Wang, Ge
2007-01-01
The bioluminescence tomography is a novel molecular imaging technology for small animal studies. Known reconstruction methods require the completely measured data on the external surface, although only partially measured data is available in practice. In this work, we formulate a mathematical model for BLT from partial data and generalize our previous results on the solution uniqueness to the partial data case. Then we extend two of our reconstruction methods for BLT to this case. The first m...
Sun, Guangling
2012-01-01
A framework of demosaicing and superresolution for color filter array (CFA) via residual image reconstruction and sparse representation is presented.Given the intermediate image produced by certain demosaicing and interpolation technique, a residual image between the final reconstruction image and the intermediate image is reconstructed using sparse representation.The final reconstruction image has richer edges and details than that of the intermediate image. Specifically, a generic dictionar...
International Nuclear Information System (INIS)
Mueck, F.G.; Koerner, M.; Scherr, M.K.; Geyer, L.L.; Deak, Z.; Linsenmaier, U.; Reiser, M.; Wirth, S.
2012-01-01
To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (-2: diagnostically inferior, -1: inferior, 0: equal, +1: superior, +2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 ± 5.5 to 12.2 ± 4.7 mGy (p 0.10). Volume mode performed 73 % slower than slice mode (p < 0.01). After the system upgrade, the vendor recommendation of ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. (orig.)
Reconstructing flaw image using dataset of full matrix capture technique
Energy Technology Data Exchange (ETDEWEB)
Lee, Tae Hun; Kim, Yong Sik; Lee, Jeong Seok [KHNP Central Research Institute, Daejeon (Korea, Republic of)
2017-02-15
A conventional phased array ultrasonic system offers the ability to steer an ultrasonic beam by applying independent time delays of individual elements in the array and produce an ultrasonic image. In contrast, full matrix capture (FMC) is a data acquisition process that collects a complete matrix of A-scans from every possible independent transmit-receive combination in a phased array transducer and makes it possible to reconstruct various images that cannot be produced by conventional phased array with the post processing as well as images equivalent to a conventional phased array image. In this paper, a basic algorithm based on the LLL mode total focusing method (TFM) that can image crack type flaws is described. And this technique was applied to reconstruct flaw images from the FMC dataset obtained from the experiments and ultrasonic simulation.
Isotope specific resolution recovery image reconstruction in high resolution PET imaging
Kotasidis Fotis A.; Kotasidis Fotis A.; Angelis Georgios I.; Anton-Rodriguez Jose; Matthews Julian C.; Reader Andrew J.; Reader Andrew J.; Zaidi Habib; Zaidi Habib; Zaidi Habib
2014-01-01
Purpose: Measuring and incorporating a scanner specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However due to the short half life of clinically used isotopes other long lived isotopes not used in clinical practice are used to perform the PSF measurements. As such non optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction usuall...
3D widefield light microscope image reconstruction without dyes
Larkin, S.; Larson, J.; Holmes, C.; Vaicik, M.; Turturro, M.; Jurkevich, A.; Sinha, S.; Ezashi, T.; Papavasiliou, G.; Brey, E.; Holmes, T.
2015-03-01
3D image reconstruction using light microscope modalities without exogenous contrast agents is proposed and investigated as an approach to produce 3D images of biological samples for live imaging applications. Multimodality and multispectral imaging, used in concert with this 3D optical sectioning approach is also proposed as a way to further produce contrast that could be specific to components in the sample. The methods avoid usage of contrast agents. Contrast agents, such as fluorescent or absorbing dyes, can be toxic to cells or alter cell behavior. Current modes of producing 3D image sets from a light microscope, such as 3D deconvolution algorithms and confocal microscopy generally require contrast agents. Zernike phase contrast (ZPC), transmitted light brightfield (TLB), darkfield microscopy and others can produce contrast without dyes. Some of these modalities have not previously benefitted from 3D image reconstruction algorithms, however. The 3D image reconstruction algorithm is based on an underlying physical model of scattering potential, expressed as the sample's 3D absorption and phase quantities. The algorithm is based upon optimizing an objective function - the I-divergence - while solving for the 3D absorption and phase quantities. Unlike typical deconvolution algorithms, each microscope modality, such as ZPC or TLB, produces two output image sets instead of one. Contrast in the displayed image and 3D renderings is further enabled by treating the multispectral/multimodal data as a feature set in a mathematical formulation that uses the principal component method of statistics.
Reconstruction of CT images by the Bayes- back projection method
Haruyama, M; Takase, M; Tobita, H
2002-01-01
In the course of research on quantitative assay of non-destructive measurement of radioactive waste, the have developed a unique program based on the Bayesian theory for reconstruction of transmission computed tomography (TCT) image. The reconstruction of cross-section images in the CT technology usually employs the Filtered Back Projection method. The new imaging reconstruction program reported here is based on the Bayesian Back Projection method, and it has a function of iterative improvement images by every step of measurement. Namely, this method has the capability of prompt display of a cross-section image corresponding to each angled projection data from every measurement. Hence, it is possible to observe an improved cross-section view by reflecting each projection data in almost real time. From the basic theory of Baysian Back Projection method, it can be not only applied to CT types of 1st, 2nd, and 3rd generation. This reported deals with a reconstruction program of cross-section images in the CT of ...
Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU
Directory of Open Access Journals (Sweden)
Arefan D
2015-06-01
Full Text Available Digital Breast Tomosynthesis (DBT is a technology that creates three dimensional (3D images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU. At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU card and the Graphics Processing Unit (GPU. It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU.
Image reconstruction technique using projection data from neutron tomography system
Directory of Open Access Journals (Sweden)
Waleed Abd el Bar
2015-12-01
Full Text Available Neutron tomography is a very powerful technique for nondestructive evaluation of heavy industrial components as well as for soft hydrogenous materials enclosed in heavy metals which are usually difficult to image using X-rays. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. This paper gives a description of a filter back projection (FBP technique, which is used for reconstruction of projected data obtained from transmission measurements by neutron tomography system We demonstrated the use of spatial Discrete Fourier Transform (DFT and the 2D Inverse DFT in the formulation of the method, and outlined the theory of reconstruction of a 2D neutron image from a sequence of 1D projections taken at different angles between 0 and π in MATLAB environment. Projections are generated by applying the Radon transform to the original image at different angles.
Optical image reconstruction using DC data: simulations and experiments
International Nuclear Information System (INIS)
Huabei Jiang; Paulsen, K.D.; Oesterberg, U.L.
1996-01-01
In this paper, we explore optical image formation using a diffusion approximation of light propagation in tissue which is modelled with a finite-element method for optically heterogeneous media. We demonstrate successful image reconstruction based on absolute experimental DC data obtained with a continuous wave 633 nm He-Ne laser system and a 751 nm diode laser system in laboratory phantoms having two optically distinct regions. The experimental systems used exploit a tomographic type of data collection scheme that provides information from which a spatially variable optical property map is deduced. Reconstruction of scattering coefficient only and simultaneous reconstruction of both scattering and absorption profiles in tissue-like phantoms are obtained from measured and simulated data. Images with different contrast levels between the heterogeneity and the background are also reported and the results show that although it is possible to obtain qualitative visual information on the location and size of a heterogeneity, it may not be possible to quantitatively resolve contrast levels or optical properties using reconstructions from DC data only. Sensitivity of image reconstruction to noise in the measurement data is investigated through simulations. The application of boundary constraints has also been addressed. (author)
Block Compressed Sensing of Images Using Adaptive Granular Reconstruction
Directory of Open Access Journals (Sweden)
Ran Li
2016-01-01
Full Text Available In the framework of block Compressed Sensing (CS, the reconstruction algorithm based on the Smoothed Projected Landweber (SPL iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.
International Nuclear Information System (INIS)
Hofmann, Christian; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc
2014-01-01
Purpose: Iterative image reconstruction gains more and more interest in clinical routine, as it promises to reduce image noise (and thereby patient dose), to reduce artifacts, or to improve spatial resolution. Among vendors and researchers, however, there is no consensus of how to best achieve these aims. The general approach is to incorporatea priori knowledge into iterative image reconstruction, for example, by adding additional constraints to the cost function, which penalize variations between neighboring voxels. However, this approach to regularization in general poses a resolution noise trade-off because the stronger the regularization, and thus the noise reduction, the stronger the loss of spatial resolution and thus loss of anatomical detail. The authors propose a method which tries to improve this trade-off. The proposed reconstruction algorithm is called alpha image reconstruction (AIR). One starts with generating basis images, which emphasize certain desired image properties, like high resolution or low noise. The AIR algorithm reconstructs voxel-specific weighting coefficients that are applied to combine the basis images. By combining the desired properties of each basis image, one can generate an image with lower noise and maintained high contrast resolution thus improving the resolution noise trade-off. Methods: All simulations and reconstructions are performed in native fan-beam geometry. A water phantom with resolution bar patterns and low contrast disks is simulated. A filtered backprojection (FBP) reconstruction with a Ram-Lak kernel is used as a reference reconstruction. The results of AIR are compared against the FBP results and against a penalized weighted least squares reconstruction which uses total variation as regularization. The simulations are based on the geometry of the Siemens Somatom Definition Flash scanner. To quantitatively assess image quality, the authors analyze line profiles through resolution patterns to define a contrast
Adaptive reconstructions for magnetic resonance imaging of moving organs
International Nuclear Information System (INIS)
Lohezic, Maelene
2011-01-01
Magnetic resonance imaging (MRI) is a valuable tool for the clinical diagnosis for brain imaging as well as cardiac and abdominal imaging. For instance, MRI is the only modality that enables the visualization and characterization myocardial edema. However, motion remains a challenging problem for cardiac MRI. Breathing as well as cardiac beating have to be carefully handled during patient examination. Moreover they limit the achievable temporal and spatial resolution of the images. In this work an approach that takes these physiological motions into account during image reconstruction process has been proposed. It allows performing cardiac examination while breathing freely. First, an iterative reconstruction algorithm, that compensates motion estimated from a motion model constrained by physiological signals, is applied to morphological cardiac imaging. A semi-automatic method for edema detection has been tested on reconstructed images. It has also been associated with an adaptive acquisition strategy which enables free-breathing end-systolic imaging. This reconstruction has then been extended to the assessment of transverse relaxation times T2, which is used for myocardial edema characterization. The proposed method, ARTEMIS, enables free-breathing T2 mapping without additional acquisition time. The proposed free breathing approaches take advantage of physiological signals to estimate the motion that occurs during MR acquisitions. Several solutions have been tested to measure this information. Among them, accelerometer-based external sensors allow local measurements at several locations. Another approach consists in the use of k-space based measurements, which are 'embedded' inside the MRI pulse sequence (navigator) and prevent from the requirement of additional recording hardware. Hence, several adaptive reconstruction algorithms were developed to obtain diagnostic information from free breathing acquisitions. These works allow performing efficient and accurate
Improving parallel imaging by jointly reconstructing multi-contrast data.
Bilgic, Berkin; Kim, Tae Hyung; Liao, Congyu; Manhard, Mary Kate; Wald, Lawrence L; Haldar, Justin P; Setsompop, Kawin
2018-08-01
To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition. We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction. We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error. JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.
Filter and slice thickness selection in SPECT image reconstruction
International Nuclear Information System (INIS)
Ivanovic, M.; Weber, D.A.; Wilson, G.A.; O'Mara, R.E.
1985-01-01
The choice of filter and slice thickness in SPECT image reconstruction as function of activity and linear and angular sampling were investigated in phantom and patient imaging studies. Reconstructed transverse and longitudinal spatial resolution of the system were measured using a line source in a water filled phantom. Phantom studies included measurements of the Data Spectrum phantom; clinical studies included tomographic procedures in 40 patients undergoing imaging of the temporomandibular joint. Slices of the phantom and patient images were evaluated for spatial of the phantom and patient images were evaluated for spatial resolution, noise, and image quality. Major findings include; spatial resolution and image quality improve with increasing linear sampling frequencies over the range of 4-8 mm/p in the phantom images, best spatial resolution and image quality in clinical images were observed at a linear sampling frequency of 6mm/p, Shepp and Logan filter gives the best spatial resolution for phantom studies at the lowest linear sampling frequency; smoothed Shepp and Logan filter provides best quality images without loss of resolution at higher frequencies and, spatial resolution and image quality improve with increased angular sampling frequency in the phantom at 40 c/p but appear to be independent of angular sampling frequency at 400 c/p
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
Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.
2017-06-01
This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.
High-order noise analysis for low dose iterative image reconstruction methods: ASIR, IRIS, and MBAI
Do, Synho; Singh, Sarabjeet; Kalra, Mannudeep K.; Karl, W. Clem; Brady, Thomas J.; Pien, Homer
2011-03-01
Iterative reconstruction techniques (IRTs) has been shown to suppress noise significantly in low dose CT imaging. However, medical doctors hesitate to accept this new technology because visual impression of IRT images are different from full-dose filtered back-projection (FBP) images. Most common noise measurements such as the mean and standard deviation of homogeneous region in the image that do not provide sufficient characterization of noise statistics when probability density function becomes non-Gaussian. In this study, we measure L-moments of intensity values of images acquired at 10% of normal dose and reconstructed by IRT methods of two state-of-art clinical scanners (i.e., GE HDCT and Siemens DSCT flash) by keeping dosage level identical to each other. The high- and low-dose scans (i.e., 10% of high dose) were acquired from each scanner and L-moments of noise patches were calculated for the comparison.
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)
International Nuclear Information System (INIS)
Koo, Young Baek; Kim, Suk; Lee, Jun Woo; Kim, Soo Jin; Choo, Ki Seok; Lee, Tae Hong; Moon, Tae Yong; Lee, Suk Hong; Jeon, Tae Yong
2004-01-01
The purpose of this study was to evaluate the performance of multidetector-row CT (MDCT) in the preoperative T-staging of patients with advanced gastric cancer. A total of 65 patients with an established diagnosis of advanced gastric cancer (T2 or more) were evaluated with MDCT. The protocol of MDCT consisted of high-quality (HQ) mode helical scanning with a slice thickness of 2.5 mm. The axial CT images were reconstructed with a slice thickness of 5 mm. MPR images were reconstructed from the raw axial data with a slice thickness of 5 mm. A comparison between the standard axial and axial MPR images was performed by two radiologists with regard to the evaluation of the tumor location and T-stage. These findings were compared with the pathologic and surgical findings. T-staging of the advanced stomach cancer was correct in 89% (58/65) and 69% (45/65) of the MPR images and axial images, respectively. The MPR images improved the detection rate (5 lesions) of the tumors and increased the accuracy of the T-staging (13 lesions) in comparison with the axial images. The MPR images are of greater diagnostic value for the evaluation of omental seeding (5 lesions: axial images, 9 lesions: MPR images), tumor location and extension. Multiplanar reconstruction (MPR) images provide increased confidence in the location and T-staging of certain cases of advanced gastric cancer, such as those in locations where CT images are susceptible to be affected by the difficulties associated with partial volume averaging. In this study, the MPR images provided more precise information about the tumor location and T-staging than the standard axial images in the preoperative evaluation of advanced gastric cancer
International Nuclear Information System (INIS)
Sato, Jiro; Akahane, Masaaki; Inano, Sachiko; Terasaki, Mariko; Akai, Hiroyuki; Katsura, Masaki; Matsuda, Izuru; Kunimatsu, Akira; Ohtomo, Kuni
2012-01-01
The purpose of this study was to assess the effects of dose and adaptive statistical iterative reconstruction (ASIR) on image quality of pulmonary computed tomography (CT). Inflated and fixed porcine lungs were scanned with a 64-slice CT system at 10, 20, 40 and 400 mAs. Using automatic exposure control, 40 mAs was chosen as standard dose. Scan data were reconstructed with filtered back projection (FBP) and ASIR. Image pairs were obtained by factorial combination of images at a selected level. Using a 21-point scale, three experienced radiologists independently rated differences in quality between adjacently displayed paired images for image noise, image sharpness and conspicuity of tiny nodules. A subjective quality score (SQS) for each image was computed based on Anderson's functional measurement theory. The standard deviation was recorded as a quantitative noise measurement. At all doses examined, SQSs improved with ASIR for all evaluation items. No significant differences were noted between the SQSs for 40%-ASIR images obtained at 20 mAs and those for FBP images at 40 mAs. Compared to the FBP algorithm, ASIR for lung CT can enable an approximately 50% dose reduction from the standard dose while preserving visualization of small structures. (author)
Dictionary Approaches to Image Compression and Reconstruction
Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.
1998-01-01
This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.
Kishimoto, Junichi; Ohta, Yasutoshi; Kitao, Shinichiro; Watanabe, Tomomi; Ogawa, Toshihide
2018-04-01
Single-source dual-energy CT (ssDECT) allows the reconstruction of iodine density images (IDIs) from projection based computing. We hypothesized that adding adaptive statistical iterative reconstruction (ASiR) could improve image quality. The aim of our study was to evaluate the effect and determine the optimal blend percentages of ASiR for IDI of myocardial late iodine enhancement (LIE) in the evaluation of chronic myocardial infarction using ssDECT. A total of 28 patients underwent cardiac LIE using a ssDECT scanner. IDIs between 0 and 100% of ASiR contributions in 10% increments were reconstructed. The signal-to-noise ratio (SNR) of remote myocardia and the contrast-to-noise ratio (CNR) of infarcted myocardia were measured. Transmural extent of infarction was graded using a 5-point scale. The SNR, CNR, and transmural extent were assessed for each ASiR contribution ratio. The transmural extents were compared with MRI as a reference standard. Compared to 0% ASiR, the use of 20-100% ASiR resulted in a reduction of image noise (p ASiR images, reconstruction with 100% ASiR image showed the highest improvement in SNR (229%; p ASiR above 80% showed the highest ratio (73.7%) of accurate transmural extent classification. In conclusion, ASiR intensity of 80-100% in IDIs can improve image quality without changes in signal and maximizes the accuracy of transmural extent in infarcted myocardium.
System and method for three-dimensional image reconstruction using an absolute orientation sensor
Giancola, Silvio; Ghanem, Bernard; Schneider, Jens; Wonka, Peter
2018-01-01
A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image
Joint model of motion and anatomy for PET image reconstruction
International Nuclear Information System (INIS)
Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama
2007-01-01
Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem
Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.
Fromm, S A; Sachse, C
2016-01-01
Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method. © 2016 Elsevier Inc. All rights reserved.
CT image reconstruction system based on hardware implementation
International Nuclear Information System (INIS)
Silva, Hamilton P. da; Evseev, Ivan; Schelin, Hugo R.; Paschuk, Sergei A.; Milhoretto, Edney; Setti, Joao A.P.; Zibetti, Marcelo; Hormaza, Joel M.; Lopes, Ricardo T.
2009-01-01
Full text: The timing factor is very important for medical imaging systems, which can nowadays be synchronized by vital human signals, like heartbeats or breath. The use of hardware implemented devices in such a system has advantages considering the high speed of information treatment combined with arbitrary low cost on the market. This article refers to a hardware system which is based on electronic programmable logic called FPGA, model Cyclone II from ALTERA Corporation. The hardware was implemented on the UP3 ALTERA Kit. A partially connected neural network with unitary weights was programmed. The system was tested with 60 topographic projections, 100 points in each, of the Shepp and Logan phantom created by MATLAB. The main restriction was found to be the memory size available on the device: the dynamic range of reconstructed image was limited to 0 65535. Also, the normalization factor must be observed in order to do not saturate the image during the reconstruction and filtering process. The test shows a principal possibility to build CT image reconstruction systems for any reasonable amount of input data by arranging the parallel work of the hardware units like we have tested. However, further studies are necessary for better understanding of the error propagation from topographic projections to reconstructed image within the implemented method. (author)
PET image reconstruction: mean, variance, and optimal minimax criterion
International Nuclear Information System (INIS)
Liu, Huafeng; Guo, Min; Gao, Fei; Shi, Pengcheng; Xue, Liying; Nie, Jing
2015-01-01
Given the noise nature of positron emission tomography (PET) measurements, it is critical to know the image quality and reliability as well as expected radioactivity map (mean image) for both qualitative interpretation and quantitative analysis. While existing efforts have often been devoted to providing only the reconstructed mean image, we present a unified framework for joint estimation of the mean and corresponding variance of the radioactivity map based on an efficient optimal min–max criterion. The proposed framework formulates the PET image reconstruction problem to be a transformation from system uncertainties to estimation errors, where the minimax criterion is adopted to minimize the estimation errors with possibly maximized system uncertainties. The estimation errors, in the form of a covariance matrix, express the measurement uncertainties in a complete way. The framework is then optimized by ∞-norm optimization and solved with the corresponding H ∞ filter. Unlike conventional statistical reconstruction algorithms, that rely on the statistical modeling methods of the measurement data or noise, the proposed joint estimation stands from the point of view of signal energies and can handle from imperfect statistical assumptions to even no a priori statistical assumptions. The performance and accuracy of reconstructed mean and variance images are validated using Monte Carlo simulations. Experiments on phantom scans with a small animal PET scanner and real patient scans are also conducted for assessment of clinical potential. (paper)
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
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
Pogue, Brian W; Song, Xiaomei; Tosteson, Tor D; McBride, Troy O; Jiang, Shudong; Paulsen, Keith D
2002-07-01
Near-infrared (NIR) diffuse tomography is an emerging method for imaging the interior of tissues to quantify concentrations of hemoglobin and exogenous chromophores non-invasively in vivo. It often exploits an optical diffusion model-based image reconstruction algorithm to estimate spatial property values from measurements of the light flux at the surface of the tissue. In this study, mean-squared error (MSE) over the image is used to evaluate methods for regularizing the ill-posed inverse image reconstruction problem in NIR tomography. Estimates of image bias and image standard deviation were calculated based upon 100 repeated reconstructions of a test image with randomly distributed noise added to the light flux measurements. It was observed that the bias error dominates at high regularization parameter values while variance dominates as the algorithm is allowed to approach the optimal solution. This optimum does not necessarily correspond to the minimum projection error solution, but typically requires further iteration with a decreasing regularization parameter to reach the lowest image error. Increasing measurement noise causes a need to constrain the minimum regularization parameter to higher values in order to achieve a minimum in the overall image MSE.
Parametric image reconstruction using spectral analysis of PET projection data
International Nuclear Information System (INIS)
Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat
1998-01-01
Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)
Generalized Fourier slice theorem for cone-beam image reconstruction.
Zhao, Shuang-Ren; Jiang, Dazong; Yang, Kevin; Yang, Kang
2015-01-01
The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is O(N^4), which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).
An image correlation procedure for digitally reconstructed radiographs and electronic portal images
International Nuclear Information System (INIS)
Dong, Lei; Boyer, Arthur L.
1995-01-01
Purpose: To study a procedure that uses megavoltage digitally reconstructed radiographs (DRRs) calculated from patient's three-dimensional (3D) computed tomography (CT) data as a reference image for correlation with on-line electronic portal images (EPIs) to detect patient setup errors. Methods and Materials: Megavoltage DRRs were generated by ray tracing through a modified volumetric CT data set in which CT numbers were converted into linear attenuation coefficients for the therapeutic beam energy. The DRR transmission image was transformed to the grayscale window of the EPI by a histogram-matching technique. An alternative approach was to calibrate the transmission DRR using a measured response curve of the electronic portal imaging device (EPID). This forces the calculated transmission fluence values to be distributed in the same range as that of the EPID image. A cross-correlation technique was used to determine the degree of alignment of the patient anatomy found in the EPID image relative to the reference DRR. Results: Phantom studies demonstrated that the correlation procedure had a standard deviation of 0.5 mm and 0.5 deg. in aligning translational shifts and in-plane rotations. Systematic errors were found between a reference DRR and a reference EPID image. The automated grayscale image-correlation process was completed within 3 s on a workstation computer or 12 s on a PC. Conclusion: The alignment procedure allows the direct comparison of a patient's treatment portal designed with a 3D planning computer with a patient's on-line portal image acquired at the treatment unit. The image registration process is automated to the extent that it requires minimal user intervention, and it is fast and accurate enough for on-line clinical applications
Jha, Abhinav K; Song, Na; Caffo, Brian; Frey, Eric C
2015-04-13
Quantitative single-photon emission computed tomography (SPECT) imaging is emerging as an important tool in clinical studies and biomedical research. There is thus a need for optimization and evaluation of systems and algorithms that are being developed for quantitative SPECT imaging. An appropriate objective method to evaluate these systems is by comparing their performance in the end task that is required in quantitative SPECT imaging, such as estimating the mean activity concentration in a volume of interest (VOI) in a patient image. This objective evaluation can be performed if the true value of the estimated parameter is known, i.e. we have a gold standard. However, very rarely is this gold standard known in human studies. Thus, no-gold-standard techniques to optimize and evaluate systems and algorithms in the absence of gold standard are required. In this work, we developed a no-gold-standard technique to objectively evaluate reconstruction methods used in quantitative SPECT when the parameter to be estimated is the mean activity concentration in a VOI. We studied the performance of the technique with realistic simulated image data generated from an object database consisting of five phantom anatomies with all possible combinations of five sets of organ uptakes, where each anatomy consisted of eight different organ VOIs. Results indicate that the method provided accurate ranking of the reconstruction methods. We also demonstrated the application of consistency checks to test the no-gold-standard output.
Fast image reconstruction for Compton camera using stochastic origin ensemble approach.
Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna
2011-01-01
Compton camera has been proposed as a potential imaging tool in astronomy, industry, homeland security, and medical diagnostics. Due to the inherent geometrical complexity of Compton camera data, image reconstruction of distributed sources can be ineffective and/or time-consuming when using standard techniques such as filtered backprojection or maximum likelihood-expectation maximization (ML-EM). In this article, the authors demonstrate a fast reconstruction of Compton camera data using a novel stochastic origin ensembles (SOE) approach based on Markov chains. During image reconstruction, the origins of the measured events are randomly assigned to locations on conical surfaces, which are the Compton camera analogs of lines-of-responses in PET. Therefore, the image is defined as an ensemble of origin locations of all possible event origins. During the course of reconstruction, the origins of events are stochastically moved and the acceptance of the new event origin is determined by the predefined acceptance probability, which is proportional to the change in event density. For example, if the event density at the new location is higher than in the previous location, the new position is always accepted. After several iterations, the reconstructed distribution of origins converges to a quasistationary state which can be voxelized and displayed. Comparison with the list-mode ML-EM reveals that the postfiltered SOE algorithm has similar performance in terms of image quality while clearly outperforming ML-EM in relation to reconstruction time. In this study, the authors have implemented and tested a new image reconstruction algorithm for the Compton camera based on the stochastic origin ensembles with Markov chains. The algorithm uses list-mode data, is parallelizable, and can be used for any Compton camera geometry. SOE algorithm clearly outperforms list-mode ML-EM for simple Compton camera geometry in terms of reconstruction time. The difference in computational time
Practical considerations for image-based PSF and blobs reconstruction in PET
International Nuclear Information System (INIS)
Stute, Simon; Comtat, Claude
2013-01-01
Iterative reconstructions in positron emission tomography (PET) need a model relating the recorded data to the object/patient being imaged, called the system matrix (SM). The more realistic this model, the better the spatial resolution in the reconstructed images. However, a serious concern when using a SM that accurately models the resolution properties of the PET system is the undesirable edge artefact, visible through oscillations near sharp discontinuities in the reconstructed images. This artefact is a natural consequence of solving an ill-conditioned inverse problem, where the recorded data are band-limited. In this paper, we focus on practical aspects when considering image-based point-spread function (PSF) reconstructions. To remove the edge artefact, we propose to use a particular case of the method of sieves (Grenander 1981 Abstract Inference New York: Wiley), which simply consists in performing a standard PSF reconstruction, followed by a post-smoothing using the PSF as the convolution kernel. Using analytical simulations, we investigate the impact of different reconstruction and PSF modelling parameters on the edge artefact and its suppression, in the case of noise-free data and an exactly known PSF. Using Monte-Carlo simulations, we assess the proposed method of sieves with respect to the choice of the geometric projector and the PSF model used in the reconstruction. When the PSF model is accurately known, we show that the proposed method of sieves succeeds in completely suppressing the edge artefact, though after a number of iterations higher than typically used in practice. When applying the method to realistic data (i.e. unknown true SM and noisy data), we show that the choice of the geometric projector and the PSF model does not impact the results in terms of noise and contrast recovery, as long as the PSF has a width close to the true PSF one. Equivalent results were obtained using either blobs or voxels in the same conditions (i.e. the blob
The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation
International Nuclear Information System (INIS)
Zhao, Zhanqi; Möller, Knut; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich
2014-01-01
Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton–Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR C ) and (4) GREIT with individual thorax geometry (GR T ). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal–Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms. (paper)
The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.
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.
Energy Technology Data Exchange (ETDEWEB)
Park, Yeonok; Park, Chulkyu; Cho, Hyosung; Je, Uikyu; Hong, Daeki; Lee, Minsik; Cho, Heemoon; Choi, Sungil; Koo, Yangseo [Yonsei University, Wonju (Korea, Republic of)
2014-09-15
Digital breast tomosynthesis (DBT) is considered in clinics as a standard three-dimensional imaging modality, allowing the earlier detection of cancer. It typically acquires only 10-30 projections over a limited angle range of 15 - 60 .deg. with a stationary detector and typically uses a computationally-efficient filtered-backprojection (FBP) algorithm for image reconstruction. However, a common FBP algorithm yields poor image quality resulting from the loss of average image value and the presence of severe image artifacts due to the elimination of the dc component of the image by the ramp filter and to the incomplete data, respectively. As an alternative, iterative reconstruction methods are often used in DBT to overcome these difficulties, even though they are still computationally expensive. In this study, as a compromise, we considered a projection-angle dependent filtering method in which one-dimensional geometry-adapted filter kernels are computed with the aid of a conjugate-gradient method and are incorporated into the standard FBP framework. We implemented the proposed algorithm and performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the proposed method is superior to a conventional FBP method for DBT imaging and has a comparable computational cost, while preserving good image homogeneity and edge sharpening with no serious image artifacts.
Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges
2013-10-01
Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.
Image Reconstruction of Metal Pipe in Electrical Resistance Tomography
Directory of Open Access Journals (Sweden)
Suzanna RIDZUAN AW
2017-02-01
Full Text Available This paper demonstrates a Linear Back Projection (LBP algorithm based on the reconstruction of conductivity distributions to identify different sizes and locations of bubble phantoms in a metal pipe. Both forward and inverse problems are discussed. Reconstructed images of the phantoms under test conditions are presented. From the results, it was justified that the sensitivity maps of the conducting boundary strategy can be applied successfully in identifying the location for the phantom of interest using LBP algorithm. Additionally, the number and spatial distribution of the bubble phantoms can be clearly distinguished at any location in the pipeline. It was also shown that the reconstructed images agree well with the bubble phantoms.
The feasibility of images reconstructed with the method of sieves
International Nuclear Information System (INIS)
Veklerov, E.; Llacer, J.
1990-01-01
The concept of sieves has been applied with the maximum likelihood estimator (MLE) to image reconstruction. While it makes it possible to recover smooth images consistent with the data, the degree of smoothness provided by it is arbitrary. It is shown that the concept of feasibility is able to resolve this arbitrariness. By varying the values of parameters determining the degree of smoothness, one can generate images on both sides of the feasibility region, as well as within the region. Feasible images recovered by using different sieve parameters are compared with feasible results of other procedures. One- and two-dimensional examples using both simulated and real data sets are considered
Electron image reconstruction of helical protein assemblies
International Nuclear Information System (INIS)
Cremers, A.F.M.
1980-01-01
The analysis of projections of large ordered biological systems obtained by electron microscopy of negatively stained specimens is described. The biological structures amenable to this approach are constructed from a large number of identical protein molecules, which are arranged according to helical symmetry. Electron images of these structures generally contain sufficient information in order to calculate a three-dimensional density map. (Auth.)
Single Image Super Resolution via Sparse Reconstruction
Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.
2012-01-01
High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms.
Realise : reconstruction of reality from image sequences
Leymarie, F.; de la Fortelle, A.; Koenderink, Jan J.; Kappers, A. M L; Stavridi, M.; van Ginneken, B.; Muller, S.; Krake, S.; Faugeras, O.; Robert, L.; Gauclin, C.; Laveau, S.; Zeller, C.; Anon,
1996-01-01
REALISE has for principal goals to extract from sequences of images, acquired with a moving camera, information necessary for determining the 3D (CAD-like) structure of a real-life scene together with information about the radiometric signatures of surfaces bounding the extracted 3D objects (e.g.
DEFF Research Database (Denmark)
Enevoldsen, Lotte H; Menashi, Changez A K; Andersen, Ulrik B
2013-01-01
time (HT) protocols and Evolution for Cardiac Software. METHODS: We studied 45 consecutive, non-selected patients referred for a clinically indicated routine 2-day stress/rest (99m)Tc-Sestamibi myocardial perfusion SPECT. All patients underwent an FT and an HT scan. Both FT and HT scans were processed......-RR) and for quantitative analysis (FT-FBP, HT-FBP, and HT-RR). The datasets were analyzed using commercially available QGS/QPS software and read by two observers evaluating image quality and clinical interpretation. Image quality was assessed on a 10-cm visual analog scale score. RESULTS: HT imaging was associated......: Use of RR reconstruction algorithms compensates for loss of image quality associated with reduced scan time. Both HT acquisition and RR reconstruction algorithm had significant effects on motion and perfusion parameters obtained with standard software, but these effects were relatively small...
Fluorescence Image Segmentation by using Digitally Reconstructed Fluorescence Images
Blumer, Clemens; Vivien, Cyprien; Oertner, Thomas G; Vetter, Thomas
2011-01-01
In biological experiments fluorescence imaging is used to image living and stimulated neurons. But the analysis of fluorescence images is a difficult task. It is not possible to conclude the shape of an object from fluorescence images alone. Therefore, it is not feasible to get good manual segmented nor ground truth data from fluorescence images. Supervised learning approaches are not possible without training data. To overcome this issues we propose to synthesize fluorescence images and call...
RECONSTRUCTION OF HUMAN LUNG MORPHOLOGY MODELS FROM MAGNETIC RESONANCE IMAGES
Reconstruction of Human Lung Morphology Models from Magnetic Resonance ImagesT. B. Martonen (Experimental Toxicology Division, U.S. EPA, Research Triangle Park, NC 27709) and K. K. Isaacs (School of Public Health, University of North Carolina, Chapel Hill, NC 27514)
Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric
2018-02-01
Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a
Honda, O; Yanagawa, M; Inoue, A; Kikuyama, A; Yoshida, S; Sumikawa, H; Tobino, K; Koyama, M; Tomiyama, N
2011-04-01
We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). Inflated and fixed lungs were scanned with a garnet detector CT in high-resolution mode (HR mode) or non-high-resolution (HR) mode, and MPR images were then reconstructed. Observers compared 15 MPR images of ASIR (40%) and ASIR (80%) with those of ASIR (0%), and assessed image quality using a visual five-point scale (1, definitely inferior; 5, definitely superior), with particular emphasis on normal pulmonary structures, artefacts, noise and overall image quality. The mean overall image quality scores in HR mode were 3.67 with ASIR (40%) and 4.97 with ASIR (80%). Those in non-HR mode were 3.27 with ASIR (40%) and 3.90 with ASIR (80%). The mean artefact scores in HR mode were 3.13 with ASIR (40%) and 3.63 with ASIR (80%), but those in non-HR mode were 2.87 with ASIR (40%) and 2.53 with ASIR (80%). The mean scores of the other parameters were greater than 3, whereas those in HR mode were higher than those in non-HR mode. There were significant differences between ASIR (40%) and ASIR (80%) in overall image quality (pASIR did not suppress the severe artefacts of contrast medium. In general, MPR image quality with ASIR (80%) was superior to that with ASIR (40%). However, there was an increased incidence of artefacts by ASIR when CT images were obtained in non-HR mode.
Bayesian PET image reconstruction incorporating anato-functional joint entropy
International Nuclear Information System (INIS)
Tang Jing; Rahmim, Arman
2009-01-01
We developed a maximum a posterior (MAP) reconstruction method for positron emission tomography (PET) image reconstruction incorporating magnetic resonance (MR) image information, with the joint entropy between the PET and MR image features serving as the regularization constraint. A non-parametric method was used to estimate the joint probability density of the PET and MR images. Using realistically simulated PET and MR human brain phantoms, the quantitative performance of the proposed algorithm was investigated. Incorporation of the anatomic information via this technique, after parameter optimization, was seen to dramatically improve the noise versus bias tradeoff in every region of interest, compared to the result from using conventional MAP reconstruction. In particular, hot lesions in the FDG PET image, which had no anatomical correspondence in the MR image, also had improved contrast versus noise tradeoff. Corrections were made to figures 3, 4 and 6, and to the second paragraph of section 3.1 on 13 November 2009. The corrected electronic version is identical to the print version.
An automated 3D reconstruction method of UAV images
Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping
2015-10-01
In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.
International Nuclear Information System (INIS)
Ahn, Sangtae; Asma, Evren; Cheng, Lishui; Manjeshwar, Ravindra M; Ross, Steven G; Miao, Jun; Jin, Xiao; Wollenweber, Scott D
2015-01-01
Ordered subset expectation maximization (OSEM) is the most widely used algorithm for clinical PET image reconstruction. OSEM is usually stopped early and post-filtered to control image noise and does not necessarily achieve optimal quantitation accuracy. As an alternative to OSEM, we have recently implemented a penalized likelihood (PL) image reconstruction algorithm for clinical PET using the relative difference penalty with the aim of improving quantitation accuracy without compromising visual image quality. Preliminary clinical studies have demonstrated visual image quality including lesion conspicuity in images reconstructed by the PL algorithm is better than or at least as good as that in OSEM images. In this paper we evaluate lesion quantitation accuracy of the PL algorithm with the relative difference penalty compared to OSEM by using various data sets including phantom data acquired with an anthropomorphic torso phantom, an extended oval phantom and the NEMA image quality phantom; clinical data; and hybrid clinical data generated by adding simulated lesion data to clinical data. We focus on mean standardized uptake values and compare them for PL and OSEM using both time-of-flight (TOF) and non-TOF data. The results demonstrate improvements of PL in lesion quantitation accuracy compared to OSEM with a particular improvement in cold background regions such as lungs. (paper)
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.)
Fahrbach, Florian O; Rohrbach, Alexander
2012-01-17
Laser beams that can self-reconstruct their initial beam profile even in the presence of massive phase perturbations are able to propagate deeper into inhomogeneous media. This ability has crucial advantages for light sheet-based microscopy in thick media, such as cell clusters, embryos, skin or brain tissue or plants, as well as scattering synthetic materials. A ring system around the central intensity maximum of a Bessel beam enables its self-reconstruction, but at the same time illuminates out-of-focus regions and deteriorates image contrast. Here we present a detection method that minimizes the negative effect of the ring system. The beam's propagation stability along one straight line enables the use of a confocal line principle, resulting in a significant increase in image contrast. The axial resolution could be improved by nearly 100% relative to the standard light-sheet techniques using scanned Gaussian beams, while demonstrating self-reconstruction also for high propagation depths.
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
Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction
Yin, Xiaoxia; Abbott, Derek
2012-01-01
Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...
Three-dimensional reconstruction of functional brain images
International Nuclear Information System (INIS)
Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao
1999-01-01
We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface
Three-dimensional reconstruction of functional brain images
Energy Technology Data Exchange (ETDEWEB)
Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao [Kyoto Univ. (Japan)
1999-08-01
We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface
Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging
Desmal, Abdulla
2016-03-01
Electromagnetic imaging is the problem of determining material properties from scattered fields measured away from the domain under investigation. Solving this inverse problem is a challenging task because (i) it is ill-posed due to the presence of (smoothing) integral operators used in the representation of scattered fields in terms of material properties, and scattered fields are obtained at a finite set of points through noisy measurements; and (ii) it is nonlinear simply due the fact that scattered fields are nonlinear functions of the material properties. The work described in this thesis tackles the ill-posedness of the electromagnetic imaging problem using sparsity-based regularization techniques, which assume that the scatterer(s) occupy only a small fraction of the investigation domain. More specifically, four novel imaging methods are formulated and implemented. (i) Sparsity-regularized Born iterative method iteratively linearizes the nonlinear inverse scattering problem and each linear problem is regularized using an improved iterative shrinkage algorithm enforcing the sparsity constraint. (ii) Sparsity-regularized nonlinear inexact Newton method calls for the solution of a linear system involving the Frechet derivative matrix of the forward scattering operator at every iteration step. For faster convergence, the solution of this matrix system is regularized under the sparsity constraint and preconditioned by leveling the matrix singular values. (iii) Sparsity-regularized nonlinear Tikhonov method directly solves the nonlinear minimization problem using Landweber iterations, where a thresholding function is applied at every iteration step to enforce the sparsity constraint. (iv) This last scheme is accelerated using a projected steepest descent method when it is applied to three-dimensional investigation domains. Projection replaces the thresholding operation and enforces the sparsity constraint. Numerical experiments, which are carried out using
A novel data processing technique for image reconstruction of penumbral imaging
Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin
2011-06-01
CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.
Scattering calculation and image reconstruction using elevation-focused beams.
Duncan, David P; Astheimer, Jeffrey P; Waag, Robert C
2009-05-01
Pressure scattered by cylindrical and spherical objects with elevation-focused illumination and reception has been analytically calculated, and corresponding cross sections have been reconstructed with a two-dimensional algorithm. Elevation focusing was used to elucidate constraints on quantitative imaging of three-dimensional objects with two-dimensional algorithms. Focused illumination and reception are represented by angular spectra of plane waves that were efficiently computed using a Fourier interpolation method to maintain the same angles for all temporal frequencies. Reconstructions were formed using an eigenfunction method with multiple frequencies, phase compensation, and iteration. The results show that the scattered pressure reduces to a two-dimensional expression, and two-dimensional algorithms are applicable when the region of a three-dimensional object within an elevation-focused beam is approximately constant in elevation. The results also show that energy scattered out of the reception aperture by objects contained within the focused beam can result in the reconstructed values of attenuation slope being greater than true values at the boundary of the object. Reconstructed sound speed images, however, appear to be relatively unaffected by the loss in scattered energy. The broad conclusion that can be drawn from these results is that two-dimensional reconstructions require compensation to account for uncaptured three-dimensional scattering.
Three-dimensional image reconstruction from stereo DSA
International Nuclear Information System (INIS)
Sakamoto, Kiyoshi; Kotoura, Noriko; Umehara, Takayoshi; Yamada, Eiji; Inaba, Tomohiro; Itou, Hiroshi
1999-01-01
The technique of interventional radiology has spread rapidly in recent years, and three-dimensional information from blood vessel images is being sought to enhance examinations. Stereo digital subtraction angiography (DSA) and rotational DSA were developed for that purpose. However, it is difficult with stereo DSA to observe the image pair during examination and to obtain positional information on blood vessels. Further, the exposure dose is increased in rotational DSA when many mask images need to be collected, and the patient is required to hold his or her breath for a long duration. We therefore devised a technique to construct three-dimensional blood vessel images by employing geometrical information extracted from stereo DSA images using the right and left images. We used a judgment method based on the correlation coefficient, although we had to extract an equal blood vessel from the right and left images to determine the three-dimensional coordinates of the blood vessel. The reconstructed three-dimensional blood vessels were projected from various angles, again by using a virtual focus, and new images were created. These image groups were displayed as rotational images by the animation display function incorporated in the DSA device. This system can observe blood vessel images of the same phase at a free angle, although the image quality is inferior to that of rotational DSA. In addition, because collection of the mask images is reduced, exposure dose can be decreased. Further, the system offers enhanced safety because no mechanical movement of the imaging system is involved. (author)
Improved compressed sensing-based cone-beam CT reconstruction using adaptive prior image constraints
Lee, Ho; Xing, Lei; Davidi, Ran; Li, Ruijiang; Qian, Jianguo; Lee, Rena
2012-04-01
Volumetric cone-beam CT (CBCT) images are acquired repeatedly during a course of radiation therapy and a natural question to ask is whether CBCT images obtained earlier in the process can be utilized as prior knowledge to reduce patient imaging dose in subsequent scans. The purpose of this work is to develop an adaptive prior image constrained compressed sensing (APICCS) method to solve this problem. Reconstructed images using full projections are taken on the first day of radiation therapy treatment and are used as prior images. The subsequent scans are acquired using a protocol of sparse projections. In the proposed APICCS algorithm, the prior images are utilized as an initial guess and are incorporated into the objective function in the compressed sensing (CS)-based iterative reconstruction process. Furthermore, the prior information is employed to detect any possible mismatched regions between the prior and current images for improved reconstruction. For this purpose, the prior images and the reconstructed images are classified into three anatomical regions: air, soft tissue and bone. Mismatched regions are identified by local differences of the corresponding groups in the two classified sets of images. A distance transformation is then introduced to convert the information into an adaptive voxel-dependent relaxation map. In constructing the relaxation map, the matched regions (unchanged anatomy) between the prior and current images are assigned with smaller weight values, which are translated into less influence on the CS iterative reconstruction process. On the other hand, the mismatched regions (changed anatomy) are associated with larger values and the regions are updated more by the new projection data, thus avoiding any possible adverse effects of prior images. The APICCS approach was systematically assessed by using patient data acquired under standard and low-dose protocols for qualitative and quantitative comparisons. The APICCS method provides an
Surface topography characterization using 3D stereoscopic reconstruction of SEM images
Vedantha Krishna, Amogh; Flys, Olena; Reddy, Vijeth V.; Rosén, B. G.
2018-06-01
A major drawback of the optical microscope is its limitation to resolve finer details. Many microscopes have been developed to overcome the limitations set by the diffraction of visible light. The scanning electron microscope (SEM) is one such alternative: it uses electrons for imaging, which have much smaller wavelength than photons. As a result high magnification with superior image resolution can be achieved. However, SEM generates 2D images which provide limited data for surface measurements and analysis. Often many research areas require the knowledge of 3D structures as they contribute to a comprehensive understanding of microstructure by allowing effective measurements and qualitative visualization of the samples under study. For this reason, stereo photogrammetry technique is employed to convert SEM images into 3D measurable data. This paper aims to utilize a stereoscopic reconstruction technique as a reliable method for characterization of surface topography. Reconstructed results from SEM images are compared with coherence scanning interferometer (CSI) results obtained by measuring a roughness reference standard sample. This paper presents a method to select the most robust/consistent surface texture parameters that are insensitive to the uncertainties involved in the reconstruction technique itself. Results from the two-stereoscopic reconstruction algorithms are also documented in this paper.
Optimized 3D Street Scene Reconstruction from Driving Recorder Images
Directory of Open Access Journals (Sweden)
Yongjun Zhang
2015-07-01
Full Text Available The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are included in the collected data because the typical recorders are often mounted in the front of moving vehicles and face the forward direction, which can make matching points on vehicles and guardrails unreliable. Believing that utilizing these image data can reduce street scene reconstruction and updating costs because of their low price, wide use, and extensive shooting coverage, we therefore proposed a new method, which is called the Mask automatic detecting method, to improve the structure results from the motion reconstruction. Note that we define vehicle and guardrail regions as “mask” in this paper since the features on them should be masked out to avoid poor matches. After removing the feature points in our new method, the camera poses and sparse 3D points that are reconstructed with the remaining matches. Our contrast experiments with the typical pipeline of structure from motion (SfM reconstruction methods, such as Photosynth and VisualSFM, demonstrated that the Mask decreased the root-mean-square error (RMSE of the pairwise matching results, which led to more accurate recovering results from the camera-relative poses. Removing features from the Mask also increased the accuracy of point clouds by nearly 30%–40% and corrected the problems of the typical methods on repeatedly reconstructing several buildings when there was only one target building.
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
Analyser-based phase contrast image reconstruction using geometrical optics
International Nuclear Information System (INIS)
Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A
2007-01-01
Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 μm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser
Robust linearized image reconstruction for multifrequency EIT of the breast.
Boverman, Gregory; Kao, Tzu-Jen; Kulkarni, Rujuta; Kim, Bong Seok; Isaacson, David; Saulnier, Gary J; Newell, Jonathan C
2008-10-01
Electrical impedance tomography (EIT) is a developing imaging modality that is beginning to show promise for detecting and characterizing tumors in the breast. At Rensselaer Polytechnic Institute, we have developed a combined EIT-tomosynthesis system that allows for the coregistered and simultaneous analysis of the breast using EIT and X-ray imaging. A significant challenge in EIT is the design of computationally efficient image reconstruction algorithms which are robust to various forms of model mismatch. Specifically, we have implemented a scaling procedure that is robust to the presence of a thin highly-resistive layer of skin at the boundary of the breast and we have developed an algorithm to detect and exclude from the image reconstruction electrodes that are in poor contact with the breast. In our initial clinical studies, it has been difficult to ensure that all electrodes make adequate contact with the breast, and thus procedures for the use of data sets containing poorly contacting electrodes are particularly important. We also present a novel, efficient method to compute the Jacobian matrix for our linearized image reconstruction algorithm by reducing the computation of the sensitivity for each voxel to a quadratic form. Initial clinical results are presented, showing the potential of our algorithms to detect and localize breast tumors.
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
3D Tomographic Image Reconstruction using CUDA C
International Nuclear Information System (INIS)
Dominguez, J. S.; Assis, J. T.; Oliveira, L. F. de
2011-01-01
This paper presents the study and implementation of a software for three dimensional reconstruction of images obtained with a tomographic system using the capabilities of Graphic Processing Units(GPU). The reconstruction by filtered back-projection method was developed using the CUDA C, for maximum utilization of the processing capabilities of GPUs to solve computational problems with large computational cost and highly parallelizable. It was discussed the potential of GPUs and shown its advantages to solving this kind of problems. The results in terms of runtime will be compared with non-parallelized implementations and must show a great reduction of processing time. (Author)
Scattering Correction For Image Reconstruction In Flash Radiography
International Nuclear Information System (INIS)
Cao, Liangzhi; Wang, Mengqi; Wu, Hongchun; Liu, Zhouyu; Cheng, Yuxiong; Zhang, Hongbo
2013-01-01
Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency
Scattering Correction For Image Reconstruction In Flash Radiography
Energy Technology Data Exchange (ETDEWEB)
Cao, Liangzhi; Wang, Mengqi; Wu, Hongchun; Liu, Zhouyu; Cheng, Yuxiong; Zhang, Hongbo [Xi' an Jiaotong Univ., Xi' an (China)
2013-08-15
Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.
Tomographic Image Reconstruction Using Training Images with Matrix and Tensor Formulations
DEFF Research Database (Denmark)
Soltani, Sara
the image resolution compared to a classical reconstruction method such as Filtered Back Projection (FBP). Some priors for the tomographic reconstruction take the form of cross-section images of similar objects, providing a set of the so-called training images, that hold the key to the structural......Reducing X-ray exposure while maintaining the image quality is a major challenge in computed tomography (CT); since the imperfect data produced from the few view and/or low intensity projections results in low-quality images that are suffering from severe artifacts when using conventional...... information about the solution. The training images must be reliable and application-specific. This PhD project aims at providing a mathematical and computational framework for the use of training sets as non-parametric priors for the solution in tomographic image reconstruction. Through an unsupervised...
Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography
International Nuclear Information System (INIS)
Gillam, John E.; Rafecas, Magdalena
2016-01-01
Emission imaging incorporates both the development of dedicated devices for data acquisition as well as algorithms for recovering images from that data. Emission tomography is an indirect approach to imaging. The effect of device modification on the final image can be understood through both the way in which data are gathered, using simulation, and the way in which the image is formed from that data, or image reconstruction. When developing novel devices, systems and imaging tasks, accurate simulation and image reconstruction allow performance to be estimated, and in some cases optimized, using computational methods before or during the process of physical construction. However, there are a vast range of approaches, algorithms and pre-existing computational tools that can be exploited and the choices made will affect the accuracy of the in silico results and quality of the reconstructed images. On the one hand, should important physical effects be neglected in either the simulation or reconstruction steps, specific enhancements provided by novel devices may not be represented in the results. On the other hand, over-modeling of device characteristics in either step leads to large computational overheads that can confound timely results. Here, a range of simulation methodologies and toolkits are discussed, as well as reconstruction algorithms that may be employed in emission imaging. The relative advantages and disadvantages of a range of options are highlighted using specific examples from current research scenarios.
Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography
Energy Technology Data Exchange (ETDEWEB)
Gillam, John E. [The University of Sydney, Faculty of Health Sciences and The Brain and Mind Centre, Camperdown (Australia); Rafecas, Magdalena, E-mail: rafecas@imt.uni-luebeck.de [University of Lubeck, Institute of Medical Engineering, Ratzeburger Allee 160, 23538 Lübeck (Germany)
2016-02-11
Emission imaging incorporates both the development of dedicated devices for data acquisition as well as algorithms for recovering images from that data. Emission tomography is an indirect approach to imaging. The effect of device modification on the final image can be understood through both the way in which data are gathered, using simulation, and the way in which the image is formed from that data, or image reconstruction. When developing novel devices, systems and imaging tasks, accurate simulation and image reconstruction allow performance to be estimated, and in some cases optimized, using computational methods before or during the process of physical construction. However, there are a vast range of approaches, algorithms and pre-existing computational tools that can be exploited and the choices made will affect the accuracy of the in silico results and quality of the reconstructed images. On the one hand, should important physical effects be neglected in either the simulation or reconstruction steps, specific enhancements provided by novel devices may not be represented in the results. On the other hand, over-modeling of device characteristics in either step leads to large computational overheads that can confound timely results. Here, a range of simulation methodologies and toolkits are discussed, as well as reconstruction algorithms that may be employed in emission imaging. The relative advantages and disadvantages of a range of options are highlighted using specific examples from current research scenarios.
Energy Technology Data Exchange (ETDEWEB)
Mueck, F.G.; Koerner, M.; Scherr, M.K.; Geyer, L.L.; Deak, Z.; Linsenmaier, U.; Reiser, M.; Wirth, S. [Ludwig-Maximilians-Univ. Muenchen (Germany). Inst. fuer Klinische Radiologie
2012-03-15
To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (-2: diagnostically inferior, -1: inferior, 0: equal, +1: superior, +2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 {+-} 5.5 to 12.2 {+-} 4.7 mGy (p < 0.001). The ICC was 0.861. The total image quality of the dose-reduced ASIR studies was comparable to the baseline at ASIR 50 % in slice (p = 0.18) and ASIR 50 - 100 % in volume mode (p > 0.10). Volume mode performed 73 % slower than slice mode (p < 0.01). After the system upgrade, the vendor recommendation of ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. (orig.)
Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib
2016-01-01
Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the
Clinical evaluation of PET image reconstruction using a spatial resolution model
DEFF Research Database (Denmark)
Andersen, Flemming Littrup; Klausen, Thomas Levin; Loft, Annika
2013-01-01
PURPOSE: PET image resolution is variable across the measured field-of-view and described by the point spread function (PSF). When accounting for the PSF during PET image reconstruction image resolution is improved and partial volume effects are reduced. Here, we evaluate the effect of PSF......-based reconstruction on lesion quantification in routine clinical whole-body (WB) PET/CT imaging. MATERIALS AND METHODS: 41 oncology patients were referred for a WB-PET/CT examination (Biograph 40 TruePoint). Emission data were acquired at 2.5min/bed at 1hpi of 400 MBq [18F]-FDG. Attenuation-corrected PET images were...... reconstructed on 336×336-matrices using: (R1) standard AW-OSEM (4 iter, 8 subsets, 4mm Gaussian) and (R2) AW-OSEM with PSF (3 iter, 21 subsets, 2mm). Blinded and randomised reading of R1- and R2-PET images was performed. Individual lesions were located and counted independently on both sets of images...
SIRFING: Sparse Image Reconstruction For INterferometry using GPUs
Cranmer, Miles; Garsden, Hugh; Mitchell, Daniel A.; Greenhill, Lincoln
2018-01-01
We present a deconvolution code for radio interferometric imaging based on the compressed sensing algorithms in Garsden et al. (2015). Being computationally intensive, compressed sensing is ripe for parallelization over GPUs. Our compressed sensing implementation generates images using wavelets, and we have ported the underlying wavelet library to CUDA, targeting the spline filter reconstruction part of the algorithm. The speedup achieved is almost an order of magnitude. The code is modular but is also being integrated into the calibration and imaging pipeline in use by the LEDA project at the Long Wavelength Array (LWA) as well as by the Murchinson Widefield Array (MWA).
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
LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation
International Nuclear Information System (INIS)
Li, Yusheng; Matej, Samuel; Karp, Joel S; Metzler, Scott D
2015-01-01
Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which
X-ray computed tomography reconstruction on non-standard trajectories for robotized inspection
International Nuclear Information System (INIS)
Banjak, Hussein
2016-01-01
The number of industrial applications of computed tomography (CT) is large and rapidly increasing with typical areas of use in the aerospace, automotive and transport industry. To support this growth of CT in the industrial field, the identified requirements concern firstly software development to improve the reconstruction algorithms and secondly the automation of the inspection process. Indeed, the use of robots gives more flexibility in the acquisition trajectory and allows the control of large and complex objects, which cannot be inspected using classical CT systems. In this context of new CT trend, a robotic platform has been installed at CEA LIST to better understand and solve specific challenges linked to the robotization of the CT process. The considered system integrates two robots that move the X-ray generator and detector. This thesis aims at achieving this new development. In particular, the objective is to develop and implement analytical and iterative reconstruction algorithms adapted to such robotized trajectories. The main focus of this thesis is concerned with helical-like scanning trajectories. We consider two main problems that could occur during acquisition process: truncated and limited-angle data. We present in this work experimental results for reconstruction on such non-standard trajectories. CIVA software is used to simulate these complex inspections and our developed algorithms are integrated as reconstruction tools. This thesis contains three parts. In the first part, we introduce the basic principles of CT and we present an overview of existing analytical and iterative algorithms for non-standard trajectories. In the second part, we modify the approximate helical FDK algorithm to deal with transversely truncated data and we propose a modified FDK algorithm adapted to reverse helical trajectory with the scan range less than 360 degrees. For iterative reconstruction, we propose two algebraic methods named SART-FISTA-TV and DART
D Reconstruction from Uav-Based Hyperspectral Images
Liu, L.; Xu, L.; Peng, J.
2018-04-01
Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.
International Nuclear Information System (INIS)
Park, Justin C.; Kim, Jin Sung; Park, Sung Ho; Liu, Zhaowei; Song, Bongyong; Song, William Y.
2013-01-01
Purpose: Utilization of respiratory correlated four-dimensional cone-beam computed tomography (4DCBCT) has enabled verification of internal target motion and volume immediately prior to treatment. However, with current standard CBCT scan, 4DCBCT poses challenge for reconstruction due to the fact that multiple phase binning leads to insufficient number of projection data to reconstruct and thus cause streaking artifacts. The purpose of this study is to develop a novel 4DCBCT reconstruction algorithm framework called motion-map constrained image reconstruction (MCIR), that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose as well as projections used in a standard free breathing 3DCBCT (FB-3DCBCT) scan.Methods: The unknown 4DCBCT volume at each phase was mathematically modeled as a combination of FB-3DCBCT and phase-specific update vector which has an associated motion-map matrix. The motion-map matrix, which is the key innovation of the MCIR algorithm, was defined as the matrix that distinguishes voxels that are moving from stationary ones. This 4DCBCT model was then reconstructed with compressed sensing (CS) reconstruction framework such that the voxels with high motion would be aggressively updated by the phase-wise sorted projections and the voxels with less motion would be minimally updated to preserve the FB-3DCBCT. To evaluate the performance of our proposed MCIR algorithm, we evaluated both numerical phantoms and a lung cancer patient. The results were then compared with the (1) clinical FB-3DCBCT reconstructed using the FDK, (2) 4DCBCT reconstructed using the FDK, and (3) 4DCBCT reconstructed using the well-known prior image constrained compressed sensing (PICCS).Results: Examination of the MCIR algorithm showed that high phase-resolved 4DCBCT with sets of up to 20 phases using a typical FB-3DCBCT scan could be reconstructed without compromising the image quality. Moreover, in comparison with
Energy Technology Data Exchange (ETDEWEB)
Park, Justin C. [Center for Advanced Radiotherapy Technologies and Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 and Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093 (United States); Kim, Jin Sung [Department of Radiation Oncology, Samsung Medical Center, Seoul 135-710 (Korea, Republic of); Park, Sung Ho [Department of Medical Physics, Asan Medical Center, College of Medicine, University of Ulsan, Seoul 138-736 (Korea, Republic of); Liu, Zhaowei [Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, California 92093 (United States); Song, Bongyong; Song, William Y. [Center for Advanced Radiotherapy Technologies and Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States)
2013-12-15
Purpose: Utilization of respiratory correlated four-dimensional cone-beam computed tomography (4DCBCT) has enabled verification of internal target motion and volume immediately prior to treatment. However, with current standard CBCT scan, 4DCBCT poses challenge for reconstruction due to the fact that multiple phase binning leads to insufficient number of projection data to reconstruct and thus cause streaking artifacts. The purpose of this study is to develop a novel 4DCBCT reconstruction algorithm framework called motion-map constrained image reconstruction (MCIR), that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose as well as projections used in a standard free breathing 3DCBCT (FB-3DCBCT) scan.Methods: The unknown 4DCBCT volume at each phase was mathematically modeled as a combination of FB-3DCBCT and phase-specific update vector which has an associated motion-map matrix. The motion-map matrix, which is the key innovation of the MCIR algorithm, was defined as the matrix that distinguishes voxels that are moving from stationary ones. This 4DCBCT model was then reconstructed with compressed sensing (CS) reconstruction framework such that the voxels with high motion would be aggressively updated by the phase-wise sorted projections and the voxels with less motion would be minimally updated to preserve the FB-3DCBCT. To evaluate the performance of our proposed MCIR algorithm, we evaluated both numerical phantoms and a lung cancer patient. The results were then compared with the (1) clinical FB-3DCBCT reconstructed using the FDK, (2) 4DCBCT reconstructed using the FDK, and (3) 4DCBCT reconstructed using the well-known prior image constrained compressed sensing (PICCS).Results: Examination of the MCIR algorithm showed that high phase-resolved 4DCBCT with sets of up to 20 phases using a typical FB-3DCBCT scan could be reconstructed without compromising the image quality. Moreover, in comparison with
Graph-cut based discrete-valued image reconstruction.
Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim
2015-05-01
Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.
Missing data reconstruction using Gaussian mixture models for fingerprint images
Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary
2016-05-01
Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.
GPU based Monte Carlo for PET image reconstruction: parameter optimization
International Nuclear Information System (INIS)
Cserkaszky, Á; Légrády, D.; Wirth, A.; Bükki, T.; Patay, G.
2011-01-01
This paper presents the optimization of a fully Monte Carlo (MC) based iterative image reconstruction of Positron Emission Tomography (PET) measurements. With our MC re- construction method all the physical effects in a PET system are taken into account thus superior image quality is achieved in exchange for increased computational effort. The method is feasible because we utilize the enormous processing power of Graphical Processing Units (GPUs) to solve the inherently parallel problem of photon transport. The MC approach regards the simulated positron decays as samples in mathematical sums required in the iterative reconstruction algorithm, so to complement the fast architecture, our work of optimization focuses on the number of simulated positron decays required to obtain sufficient image quality. We have achieved significant results in determining the optimal number of samples for arbitrary measurement data, this allows to achieve the best image quality with the least possible computational effort. Based on this research recommendations can be given for effective partitioning of computational effort into the iterations in limited time reconstructions. (author)
Hierarchical Bayesian sparse image reconstruction with application to MRFM.
Dobigeon, Nicolas; Hero, Alfred O; Tourneret, Jean-Yves
2009-09-01
This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gaussian noise. Our hierarchical Bayes model is well suited to such naturally sparse image applications as it seamlessly accounts for properties such as sparsity and positivity of the image via appropriate Bayes priors. We propose a prior that is based on a weighted mixture of a positive exponential distribution and a mass at zero. The prior has hyperparameters that are tuned automatically by marginalization over the hierarchical Bayesian model. To overcome the complexity of the posterior distribution, a Gibbs sampling strategy is proposed. The Gibbs samples can be used to estimate the image to be recovered, e.g., by maximizing the estimated posterior distribution. In our fully Bayesian approach, the posteriors of all the parameters are available. Thus, our algorithm provides more information than other previously proposed sparse reconstruction methods that only give a point estimate. The performance of the proposed hierarchical Bayesian sparse reconstruction method is illustrated on synthetic data and real data collected from a tobacco virus sample using a prototype MRFM instrument.
Tomographic image reconstruction and rendering with texture-mapping hardware
International Nuclear Information System (INIS)
Azevedo, S.G.; Cabral, B.K.; Foran, J.
1994-07-01
The image reconstruction problem, also known as the inverse Radon transform, for x-ray computed tomography (CT) is found in numerous applications in medicine and industry. The most common algorithm used in these cases is filtered backprojection (FBP), which, while a simple procedure, is time-consuming for large images on any type of computational engine. Specially-designed, dedicated parallel processors are commonly used in medical CT scanners, whose results are then passed to graphics workstation for rendering and analysis. However, a fast direct FBP algorithm can be implemented on modern texture-mapping hardware in current high-end workstation platforms. This is done by casting the FBP algorithm as an image warping operation with summing. Texture-mapping hardware, such as that on the Silicon Graphics Reality Engine (TM), shows around 600 times speedup of backprojection over a CPU-based implementation (a 100 Mhz R4400 in this case). This technique has the further advantages of flexibility and rapid programming. In addition, the same hardware can be used for both image reconstruction and for volumetric rendering. The techniques can also be used to accelerate iterative reconstruction algorithms. The hardware architecture also allows more complex operations than straight-ray backprojection if they are required, including fan-beam, cone-beam, and curved ray paths, with little or no speed penalties
Image reconstruction from limited angle Compton camera data
International Nuclear Information System (INIS)
Tomitani, T.; Hirasawa, M.
2002-01-01
The Compton camera is used for imaging the distributions of γ ray direction in a γ ray telescope for astrophysics and for imaging radioisotope distributions in nuclear medicine without the need for collimators. The integration of γ rays on a cone is measured with the camera, so that some sort of inversion method is needed. Parra found an analytical inversion algorithm based on spherical harmonics expansion of projection data. His algorithm is applicable to the full set of projection data. In this paper, six possible reconstruction algorithms that allow image reconstruction from projections with a finite range of scattering angles are investigated. Four algorithms have instability problems and two others are practical. However, the variance of the reconstructed image diverges in these two cases, so that window functions are introduced with which the variance becomes finite at a cost of spatial resolution. These two algorithms are compared in terms of variance. The algorithm based on the inversion of the summed back-projection is superior to the algorithm based on the inversion of the summed projection. (author)
Complications of anterior cruciate ligament reconstruction: MR imaging
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Papakonstantinou, Olympia; Chung, Christine B.; Chanchairujira, Kullanuch; Resnick, Donald L. [Department of Radiology, Veterans Affairs Medical Center, University of California, 3350 La Jolla Village Dr., San Diego, CA 92161 (United States)
2003-05-01
Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation. (orig.)
Complications of anterior cruciate ligament reconstruction: MR imaging
International Nuclear Information System (INIS)
Papakonstantinou, Olympia; Chung, Christine B.; Chanchairujira, Kullanuch; Resnick, Donald L.
2003-01-01
Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation. (orig.)
Analyser-based phase contrast image reconstruction using geometrical optics.
Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A
2007-07-21
Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser.
Holographic images reconstructed from GMR-based fringe pattern
Directory of Open Access Journals (Sweden)
Kikuchi Hiroshi
2013-01-01
Full Text Available We have developed a magneto-optical spatial light modulator (MOSLM using giant magneto-resistance (GMR structures for realizing a holographic three-dimensional (3D display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.
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.
Reconstruction of hyperspectral image using matting model for classification
Xie, Weiying; Li, Yunsong; Ge, Chiru
2016-05-01
Although hyperspectral images (HSIs) captured by satellites provide much information in spectral regions, some bands are redundant or have large amounts of noise, which are not suitable for image analysis. To address this problem, we introduce a method for reconstructing the HSI with noise reduction and contrast enhancement using a matting model for the first time. The matting model refers to each spectral band of an HSI that can be decomposed into three components, i.e., alpha channel, spectral foreground, and spectral background. First, one spectral band of an HSI with more refined information than most other bands is selected, and is referred to as an alpha channel of the HSI to estimate the hyperspectral foreground and hyperspectral background. Finally, a combination operation is applied to reconstruct the HSI. In addition, the support vector machine (SVM) classifier and three sparsity-based classifiers, i.e., orthogonal matching pursuit (OMP), simultaneous OMP, and OMP based on first-order neighborhood system weighted classifiers, are utilized on the reconstructed HSI and the original HSI to verify the effectiveness of the proposed method. Specifically, using the reconstructed HSI, the average accuracy of the SVM classifier can be improved by as much as 19%.
Parallel MR image reconstruction using augmented Lagrangian methods.
Ramani, Sathish; Fessler, Jeffrey A
2011-03-01
Magnetic resonance image (MRI) reconstruction using SENSitivity Encoding (SENSE) requires regularization to suppress noise and aliasing effects. Edge-preserving and sparsity-based regularization criteria can improve image quality, but they demand computation-intensive nonlinear optimization. In this paper, we present novel methods for regularized MRI reconstruction from undersampled sensitivity encoded data--SENSE-reconstruction--using the augmented Lagrangian (AL) framework for solving large-scale constrained optimization problems. We first formulate regularized SENSE-reconstruction as an unconstrained optimization task and then convert it to a set of (equivalent) constrained problems using variable splitting. We then attack these constrained versions in an AL framework using an alternating minimization method, leading to algorithms that can be implemented easily. The proposed methods are applicable to a general class of regularizers that includes popular edge-preserving (e.g., total-variation) and sparsity-promoting (e.g., l(1)-norm of wavelet coefficients) criteria and combinations thereof. Numerical experiments with synthetic and in vivo human data illustrate that the proposed AL algorithms converge faster than both general-purpose optimization algorithms such as nonlinear conjugate gradient (NCG) and state-of-the-art MFISTA.
Digital filtering and reconstruction of coded aperture images
International Nuclear Information System (INIS)
Tobin, K.W. Jr.
1987-01-01
The real-time neutron radiography facility at the University of Virginia has been used for both transmission radiography and computed tomography. Recently, a coded aperture system has been developed to permit the extraction of three dimensional information from a low intensity field of radiation scattered by an extended object. Short wave-length radiations (e.g. neutrons) are not easily image because of the difficulties in achieving diffraction and refraction with a conventional lens imaging system. By using a coded aperture approach, an imaging system has been developed that records and reconstructs an object from an intensity distribution. This system has a signal-to-noise ratio that is proportional to the total open area of the aperture making it ideal for imaging with a limiting intensity radiation field. The main goal of this research was to develope and implement the digital methods and theory necessary for the reconstruction process. Several real-time video systems, attached to an Intellect-100 image processor, a DEC PDP-11 micro-computer, and a Convex-1 parallel processing mainframe were employed. This system, coupled with theoretical extensions and improvements, allowed for retrieval of information previously unobtainable by earlier optical methods. The effect of thermal noise, shot noise, and aperture related artifacts were examined so that new digital filtering techniques could be constructed and implemented. Results of image data filtering prior to and following the reconstruction process are reported. Improvements related to the different signal processing methods are emphasized. The application and advantages of this imaging technique to the field of non-destructive testing are also discussed
PHOTOGRAMMETRIC 3D BUILDING RECONSTRUCTION FROM THERMAL IMAGES
Directory of Open Access Journals (Sweden)
E. Maset
2017-08-01
Full Text Available This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.
3D Point Cloud Reconstruction from Single Plenoptic Image
Directory of Open Access Journals (Sweden)
F. Murgia
2016-06-01
Full Text Available Novel plenoptic cameras sample the light field crossing the main camera lens. The information available in a plenoptic image must be processed, in order to create the depth map of the scene from a single camera shot. In this paper a novel algorithm, for the reconstruction of 3D point cloud of the scene from a single plenoptic image, taken with a consumer plenoptic camera, is proposed. Experimental analysis is conducted on several test images, and results are compared with state of the art methodologies. The results are very promising, as the quality of the 3D point cloud from plenoptic image, is comparable with the quality obtained with current non-plenoptic methodologies, that necessitate more than one image.
International Nuclear Information System (INIS)
Michel, Eric; Hernandez, Daniel; Cho, Min Hyoung; Lee, Soo Yeol
2014-01-01
Purpose: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B 1 + maps in electrical properties tomography (EPT). Methods: In EPT, electrical property images are computed by taking Laplacian of the B 1 + maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B 1 + maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. Results: In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. Conclusions: The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T
Mueck, F G; Körner, M; Scherr, M K; Geyer, L L; Deak, Z; Linsenmaier, U; Reiser, M; Wirth, S
2012-03-01
To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (- 2: diagnostically inferior, - 1: inferior, 0: equal, + 1: superior, + 2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 ± 5.5 to 12.2 ± 4.7 mGy (p ASIR studies was comparable to the baseline at ASIR 50 % in slice (p = 0.18) and ASIR 50 - 100 % in volume mode (p > 0.10). Volume mode performed 73 % slower than slice mode (p ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. © Georg Thieme Verlag KG Stuttgart · New York.
Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies
Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong
2017-05-01
Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other
Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in-vivo studies
Petibon, Yoann; Rakvongthai, Yothin; Fakhri, Georges El; Ouyang, Jinsong
2017-01-01
Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves -TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in-vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans - each containing 1/8th of the total number of events - were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard Ordered Subset Expectation Maximization (OSEM) reconstruction algorithm on one side, and the One-Step Late Maximum a Posteriori (OSL-MAP) algorithm on the other
Stokes image reconstruction for two-color microgrid polarization imaging systems.
Lemaster, Daniel A
2011-07-18
The Air Force Research Laboratory has developed a new microgrid polarization imaging system capable of simultaneously reconstructing linear Stokes parameter images in two colors on a single focal plane array. In this paper, an effective method for extracting Stokes images is presented for this type of camera system. It is also shown that correlations between the color bands can be exploited to significantly increase overall spatial resolution. Test data is used to show the advantages of this approach over bilinear interpolation. The bounds (in terms of available reconstruction bandwidth) on image resolution are also provided.
Model-based microwave image reconstruction: simulations and experiments
International Nuclear Information System (INIS)
Ciocan, Razvan; Jiang Huabei
2004-01-01
We describe an integrated microwave imaging system that can provide spatial maps of dielectric properties of heterogeneous media with tomographically collected data. The hardware system (800-1200 MHz) was built based on a lock-in amplifier with 16 fixed antennas. The reconstruction algorithm was implemented using a Newton iterative method with combined Marquardt-Tikhonov regularizations. System performance was evaluated using heterogeneous media mimicking human breast tissue. Finite element method coupled with the Bayliss and Turkel radiation boundary conditions were applied to compute the electric field distribution in the heterogeneous media of interest. The results show that inclusions embedded in a 76-diameter background medium can be quantitatively reconstructed from both simulated and experimental data. Quantitative analysis of the microwave images obtained suggests that an inclusion of 14 mm in diameter is the smallest object that can be fully characterized presently using experimental data, while objects as small as 10 mm in diameter can be quantitatively resolved with simulated data
A maximum entropy reconstruction technique for tomographic particle image velocimetry
International Nuclear Information System (INIS)
Bilsky, A V; Lozhkin, V A; Markovich, D M; Tokarev, M P
2013-01-01
This paper studies a novel approach for reducing tomographic PIV computational complexity. The proposed approach is an algebraic reconstruction technique, termed MENT (maximum entropy). This technique computes the three-dimensional light intensity distribution several times faster than SMART, using at least ten times less memory. Additionally, the reconstruction quality remains nearly the same as with SMART. This paper presents the theoretical computation performance comparison for MENT, SMART and MART, followed by validation using synthetic particle images. Both the theoretical assessment and validation of synthetic images demonstrate significant computational time reduction. The data processing accuracy of MENT was compared to that of SMART in a slot jet experiment. A comparison of the average velocity profiles shows a high level of agreement between the results obtained with MENT and those obtained with SMART. (paper)
ASTM reference radiologic digital image standards
International Nuclear Information System (INIS)
Wysnewski, R.; Wysnewski, D.
1996-01-01
ASTM Reference Radiographs have been essential in defining industry's material defect grade levels for many years. ASTM Reference Radiographs are used extensively as even the American Society for Metals Nondestructive Inspection and Quality Control Metals Handbook, Volume 11, eighth edition refers to ASTM Standard Reference Radiographs. The recently published E 1648 Standard Reference Radiographs for Examination of Aluminum Fusion Welds is a prime example of the on-going need for these references. To date, 14 Standard Reference Radiographs have been published to characterize material defects. Standard Reference Radiographs do not adequately address film-less radiologic methods. There are differences in mediums to content with. On a computer CRT defect indications appear differently when compared to indications viewed in a radiograph on a view box. Industry that uses non-film radiologic methods of inspection can be burdened with additional time and money developing internal standard reference radiologic images. These references may be deemed necessary for grading levels of product defects. Because there are no ASTM Standard Reference Radiologic data files for addressing this need in the industry, the authors of this paper suggested implementing a method for their creation under ASTM supervision. ASTM can assure continuity to those users making the transition from analog radiographic images to digital image data by swiftly addressing the requirements for reference digital image standards. The current status and possible future activities regarding a method to create digital data files is presented in this paper summary
International Nuclear Information System (INIS)
Bastarrika, Gorka; Arraiza, Maria; Pueyo, Jesus C.; Cecco, Carlo N. de; Ubilla, Matias; Mastrobuoni, Stefano; Rabago, Gregorio
2008-01-01
The image quality and optimal reconstruction interval for coronary arteries in heart transplant recipients undergoing non-invasive dual-source computed tomography (DSCT) coronary angiography was evaluated. Twenty consecutive heart transplant recipients who underwent DSCT coronary angiography were included (19 male, one female; mean age 63.1±10.7 years). Data sets were reconstructed in 5% steps from 30% to 80% of the R-R interval. Two blinded independent observers assessed the image quality of each coronary segments using a five-point scale (from 0 = not evaluative to 4=excellent quality). A total of 289 coronary segments in 20 heart transplant recipients were evaluated. Mean heart rate during the scan was 89.1±10.4 bpm. At the best reconstruction interval, diagnostic image quality (score ≥2) was obtained in 93.4% of the coronary segments (270/289) with a mean image quality score of 3.04± 0.63. Systolic reconstruction intervals provided better image quality scores than diastolic reconstruction intervals (overall mean quality scores obtained with the systolic and diastolic reconstructions 3.03±1.06 and 2.73±1.11, respectively; P<0.001). Different systolic reconstruction intervals (35%, 40%, 45% of RR interval) did not yield to significant differences in image quality scores for the coronary segments (P=0.74). Reconstructions obtained at the systolic phase of the cardiac cycle allowed excellent diagnostic image quality coronary angiograms in heart transplant recipients undergoing DSCT coronary angiography. (orig.)
Pöhlmann, Stefanie T L; Harkness, Elaine; Taylor, Christopher J; Gandhi, Ashu; Astley, Susan M
2017-08-01
This study aimed to investigate whether breast volume measured preoperatively using a Kinect 3D sensor could be used to determine the most appropriate implant size for reconstruction. Ten patients underwent 3D imaging before and after unilateral implant-based reconstruction. Imaging used seven configurations, varying patient pose and Kinect location, which were compared regarding suitability for volume measurement. Four methods of defining the breast boundary for automated volume calculation were compared, and repeatability assessed over five repetitions. The most repeatable breast boundary annotation used an ellipse to track the inframammary fold and a plane describing the chest wall (coefficient of repeatability: 70 ml). The most reproducible imaging position comparing pre- and postoperative volume measurement of the healthy breast was achieved for the sitting patient with elevated arms and Kinect centrally positioned (coefficient of repeatability: 141 ml). Optimal implant volume was calculated by correcting used implant volume by the observed postoperative asymmetry. It was possible to predict implant size using a linear model derived from preoperative volume measurement of the healthy breast (coefficient of determination R 2 = 0.78, standard error of prediction 120 ml). Mastectomy specimen weight and experienced surgeons' choice showed similar predictive ability (both: R 2 = 0.74, standard error: 141/142 ml). A leave one-out validation showed that in 61% of cases, 3D imaging could predict implant volume to within 10%; however for 17% of cases it was >30%. This technology has the potential to facilitate reconstruction surgery planning and implant procurement to maximise symmetry after unilateral reconstruction. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Mieville, Frederic A.; Gudinchet, Francois; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Bochud, Francois O.; Verdun, Francis R.
2011-01-01
Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI vol 4.8-7.9 mGy, DLP 37.1-178.9 mGy.cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Mieville, Frederic A. [University Hospital Center and University of Lausanne, Institute of Radiation Physics, Lausanne (Switzerland); University Hospital Center and University of Lausanne, Institute of Radiation Physics - Medical Radiology, Lausanne (Switzerland); Gudinchet, Francois; Rizzo, Elena [University Hospital Center and University of Lausanne, Department of Radiology, Lausanne (Switzerland); Ou, Phalla; Brunelle, Francis [Necker Children' s Hospital, Department of Radiology, Paris (France); Bochud, Francois O.; Verdun, Francis R. [University Hospital Center and University of Lausanne, Institute of Radiation Physics, Lausanne (Switzerland)
2011-09-15
Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI{sub vol} 4.8-7.9 mGy, DLP 37.1-178.9 mGy.cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone. (orig.)
GPU based Monte Carlo for PET image reconstruction: detector modeling
International Nuclear Information System (INIS)
Légrády; Cserkaszky, Á; Lantos, J.; Patay, G.; Bükki, T.
2011-01-01
Monte Carlo (MC) calculations and Graphical Processing Units (GPUs) are almost like the dedicated hardware designed for the specific task given the similarities between visible light transport and neutral particle trajectories. A GPU based MC gamma transport code has been developed for Positron Emission Tomography iterative image reconstruction calculating the projection from unknowns to data at each iteration step taking into account the full physics of the system. This paper describes the simplified scintillation detector modeling and its effect on convergence. (author)
Image reconstruction using Monte Carlo simulation and artificial neural networks
International Nuclear Information System (INIS)
Emert, F.; Missimner, J.; Blass, W.; Rodriguez, A.
1997-01-01
PET data sets are subject to two types of distortions during acquisition: the imperfect response of the scanner and attenuation and scattering in the active distribution. In addition, the reconstruction of voxel images from the line projections composing a data set can introduce artifacts. Monte Carlo simulation provides a means for modeling the distortions and artificial neural networks a method for correcting for them as well as minimizing artifacts. (author) figs., tab., refs
Total variation superiorized conjugate gradient method for image reconstruction
Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.
2018-03-01
The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise; due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Non-linear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG); one of its input parameters is a positive number ɛ. It is proved that, for any given ɛ that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ɛ. Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value ɛ of the half-squared residual.
Fan beam image reconstruction with generalized Fourier slice theorem.
Zhao, Shuangren; Yang, Kang; Yang, Kevin
2014-01-01
For parallel beam geometry the Fourier reconstruction works via the Fourier slice theorem (or central slice theorem, projection slice theorem). For fan beam situation, Fourier slice can be extended to a generalized Fourier slice theorem (GFST) for fan-beam image reconstruction. We have briefly introduced this method in a conference. This paper reintroduces the GFST method for fan beam geometry in details. The GFST method can be described as following: the Fourier plane is filled by adding up the contributions from all fanbeam projections individually; thereby the values in the Fourier plane are directly calculated for Cartesian coordinates such avoiding the interpolation from polar to Cartesian coordinates in the Fourier domain; inverse fast Fourier transform is applied to the image in Fourier plane and leads to a reconstructed image in spacial domain. The reconstructed image is compared between the result of the GFST method and the result from the filtered backprojection (FBP) method. The major differences of the GFST and the FBP methods are: (1) The interpolation process are at different data sets. The interpolation of the GFST method is at projection data. The interpolation of the FBP method is at filtered projection data. (2) The filtering process are done in different places. The filtering process of the GFST is at Fourier domain. The filtering process of the FBP method is the ramp filter which is done at projections. The resolution of ramp filter is variable with different location but the filter in the Fourier domain lead to resolution invariable with location. One advantage of the GFST method over the FBP method is in short scan situation, an exact solution can be obtained with the GFST method, but it can not be obtained with the FBP method. The calculation of both the GFST and the FBP methods are at O(N^3), where N is the number of pixel in one dimension.
The gridding method for image reconstruction by Fourier transformation
International Nuclear Information System (INIS)
Schomberg, H.; Timmer, J.
1995-01-01
This paper explores a computational method for reconstructing an n-dimensional signal f from a sampled version of its Fourier transform f. The method involves a window function w and proceeds in three steps. First, the convolution g = w * f is computed numerically on a Cartesian grid, using the available samples of f. Then, g = wf is computed via the inverse discrete Fourier transform, and finally f is obtained as g/w. Due to the smoothing effect of the convolution, evaluating w * f is much less error prone than merely interpolating f. The method was originally devised for image reconstruction in radio astronomy, but is actually applicable to a broad range of reconstructive imaging methods, including magnetic resonance imaging and computed tomography. In particular, it provides a fast and accurate alternative to the filtered backprojection. The basic method has several variants with other applications, such as the equidistant resampling of arbitrarily sampled signals or the fast computation of the Radon (Hough) transform
Radiation dose reduction in cerebral CT perfusion imaging using iterative reconstruction
International Nuclear Information System (INIS)
Niesten, Joris M.; Schaaf, Irene C. van der; Riordan, Alan J.; Jong, Hugo W.A.M. de; Eijspaart, Daniel; Smit, Ewoud J.; Mali, Willem P.T.M.; Velthuis, Birgitta K.; Horsch, Alexander D.
2014-01-01
To investigate whether iterative reconstruction (IR) in cerebral CT perfusion (CTP) allows for 50 % dose reduction while maintaining image quality (IQ). A total of 48 CTP examinations were reconstructed into a standard dose (150 mAs) with filtered back projection (FBP) and half-dose (75 mAs) with two strengths of IR (middle and high). Objective IQ (quantitative perfusion values, contrast-to-noise ratio (CNR), penumbra, infarct area and penumbra/infarct (P/I) index) and subjective IQ (diagnostic IQ on a four-point Likert scale and overall IQ binomial) were compared among the reconstructions. Half-dose CTP with high IR level had, compared with standard dose with FBP, similar objective (grey matter cerebral blood volume (CBV) 4.4 versus 4.3 mL/100 g, CNR 1.59 versus 1.64 and P/I index 0.74 versus 0.73, respectively) and subjective diagnostic IQ (mean Likert scale 1.42 versus 1.49, respectively). The overall IQ in half-dose with high IR level was scored lower in 26-31 %. Half-dose with FBP and with the middle IR level were inferior to standard dose with FBP. With the use of IR in CTP imaging it is possible to examine patients with a half dose without significantly altering the objective and diagnostic IQ. The standard dose with FBP is still preferable in terms of subjective overall IQ in about one quarter of patients. (orig.)
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.
Specialized Color Targets for Spectral Reflectance Reconstruction of Magnified Images
Kruschwitz, Jennifer D. T.
Digital images are used almost exclusively instead of film to capture visual information across many scientific fields. The colorimetric color representation within these digital images can be relayed from the digital counts produced by the camera with the use of a known color target. In image capture of magnified images, there is currently no reliable color target that can be used at multiple magnifications and give the user a solid understanding of the color ground truth within those images. The first part of this dissertation included the design, fabrication, and testing of a color target produced with optical interference coated microlenses for use in an off-axis illumination, compound microscope. An ideal target was designed to increase the color gamut for colorimetric imaging and provide the necessary "Block Dye" spectral reflectance profiles across the visible spectrum to reduce the number of color patches necessary for multiple filter imaging systems that rely on statistical models for spectral reflectance reconstruction. There are other scientific disciplines that can benefit from a specialized color target to determine the color ground truth in their magnified images and perform spectral estimation. Not every discipline has the luxury of having a multi-filter imaging system. The second part of this dissertation developed two unique ways of using an interference coated color mirror target: one that relies on multiple light-source angles, and one that leverages a dynamic color change with time. The source multi-angle technique would be used for the microelectronic discipline where the reconstructed spectral reflectance would be used to determine a dielectric film thickness on a silicon substrate, and the time varying technique would be used for a biomedical example to determine the thickness of human tear film.
A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging.
Yan, Hao; Zhen, Xin; Folkerts, Michael; Li, Yongbao; Pan, Tinsu; Cervino, Laura; Jiang, Steve B; Jia, Xun
2014-07-01
4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3-0.5 mm for patients 1-3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1-1.5 min per phase. High-quality 4D-CBCT imaging based
A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging
Energy Technology Data Exchange (ETDEWEB)
Yan, Hao; Folkerts, Michael; Jiang, Steve B., E-mail: xun.jia@utsouthwestern.edu, E-mail: steve.jiang@UTSouthwestern.edu; Jia, Xun, E-mail: xun.jia@utsouthwestern.edu, E-mail: steve.jiang@UTSouthwestern.edu [Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390 (United States); Zhen, Xin [Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515 (China); Li, Yongbao [Department of Radiation Oncology, The University of Texas, Southwestern Medical Center, Dallas, Texas 75390 and Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Pan, Tinsu [Department of Imaging Physics, The University of Texas, MD Anderson Cancer Center, Houston, Texas 77030 (United States); Cervino, Laura [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States)
2014-07-15
Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3–0.5 mm for patients 1–3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1–1.5 min per phase
Fast nonconvex nonsmooth minimization methods for image restoration and reconstruction.
Nikolova, Mila; Ng, Michael K; Tam, Chi-Pan
2010-12-01
Nonconvex nonsmooth regularization has advantages over convex regularization for restoring images with neat edges. However, its practical interest used to be limited by the difficulty of the computational stage which requires a nonconvex nonsmooth minimization. In this paper, we deal with nonconvex nonsmooth minimization methods for image restoration and reconstruction. Our theoretical results show that the solution of the nonconvex nonsmooth minimization problem is composed of constant regions surrounded by closed contours and neat edges. The main goal of this paper is to develop fast minimization algorithms to solve the nonconvex nonsmooth minimization problem. Our experimental results show that the effectiveness and efficiency of the proposed algorithms.
Task-based optimization of image reconstruction in breast CT
Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan
2014-03-01
We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.
Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification
Zhu, Xiaofeng; Xie, Qing; Zhu, Yonghua; Liu, Xingyi; Zhang, Shichao
2015-01-01
This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple
Effects of illumination on image reconstruction via Fourier ptychography
Cao, Xinrui; Sinzinger, Stefan
2017-12-01
The Fourier ptychographic microscopy (FPM) technique provides high-resolution images by combining a traditional imaging system, e.g. a microscope or a 4f-imaging system, with a multiplexing illumination system, e.g. an LED array and numerical image processing for enhanced image reconstruction. In order to numerically combine images that are captured under varying illumination angles, an iterative phase-retrieval algorithm is often applied. However, in practice, the performance of the FPM algorithm degrades due to the imperfections of the optical system, the image noise caused by the camera, etc. To eliminate the influence of the aberrations of the imaging system, an embedded pupil function recovery (EPRY)-FPM algorithm has been proposed [Opt. Express 22, 4960-4972 (2014)]. In this paper, we study how the performance of FPM and EPRY-FPM algorithms are affected by imperfections of the illumination system using both numerical simulations and experiments. The investigated imperfections include varying and non-uniform intensities, and wavefront aberrations. Our study shows that the aberrations of the illumination system significantly affect the performance of both FPM and EPRY-FPM algorithms. Hence, in practice, aberrations in the illumination system gain significant influence on the resulting image quality.
Sub-Angstrom microscopy through incoherent imaging and image reconstruction
International Nuclear Information System (INIS)
Pennycook, S.J.; Jesson, D.E.; Chisholm, M.F.; Ferridge, A.G.; Seddon, M.J.
1992-03-01
Z-contrast scanning transmission electron microscopy (STEM) with a high-angle annular detector breaks the coherence of the imaging process, and provides an incoherent image of a crystal projection. Even in the presence of strong dynamical diffraction, the image can be accurately described as a convolution between an object function, sharply peaked at the projected atomic sites, and the probe intensity profile. Such an image can be inverted intuitively without the need for model structures, and therefore provides the important capability to reveal unanticipated interfacial arrangements. It represents a direct image of the crystal projection, revealing the location of the atomic columns and their relative high-angle scattering power. Since no phase is associated with a peak in the object function or the contrast transfer function, extension to higher resolution is also straightforward. Image restoration techniques such as maximum entropy, in conjunction with the 1.3 Angstrom probe anticipated for a 300 kV STEM, appear to provide a simple and robust route to the achievement of sub-Angstrom resolution electron microscopy
Multiresolution 3-D reconstruction from side-scan sonar images.
Coiras, Enrique; Petillot, Yvan; Lane, David M
2007-02-01
In this paper, a new method for the estimation of seabed elevation maps from side-scan sonar images is presented. The side-scan image formation process is represented by a Lambertian diffuse model, which is then inverted by a multiresolution optimization procedure inspired by expectation-maximization to account for the characteristics of the imaged seafloor region. On convergence of the model, approximations for seabed reflectivity, side-scan beam pattern, and seabed altitude are obtained. The performance of the system is evaluated against a real structure of known dimensions. Reconstruction results for images acquired by different sonar sensors are presented. Applications to augmented reality for the simulation of targets in sonar imagery are also discussed.
A Novel Kernel-Based Regularization Technique for PET Image Reconstruction
Directory of Open Access Journals (Sweden)
Abdelwahhab Boudjelal
2017-06-01
Full Text Available Positron emission tomography (PET is an imaging technique that generates 3D detail of physiological processes at the cellular level. The technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of “image reconstruction from projection”. This paper proposes a novel kernel-based regularization technique for maximum-likelihood expectation-maximization ( κ -MLEM to reconstruct the image. Compared to standard MLEM, the proposed algorithm is more robust and is more effective in removing background noise, whilst preserving the edges; this suppresses image artifacts, such as out-of-focus slice blur.
Fast gradient-based methods for Bayesian reconstruction of transmission and emission PET images
International Nuclear Information System (INIS)
Mumcuglu, E.U.; Leahy, R.; Zhou, Z.; Cherry, S.R.
1994-01-01
The authors describe conjugate gradient algorithms for reconstruction of transmission and emission PET images. The reconstructions are based on a Bayesian formulation, where the data are modeled as a collection of independent Poisson random variables and the image is modeled using a Markov random field. A conjugate gradient algorithm is used to compute a maximum a posteriori (MAP) estimate of the image by maximizing over the posterior density. To ensure nonnegativity of the solution, a penalty function is used to convert the problem to one of unconstrained optimization. Preconditioners are used to enhance convergence rates. These methods generally achieve effective convergence in 15--25 iterations. Reconstructions are presented of an 18 FDG whole body scan from data collected using a Siemens/CTI ECAT931 whole body system. These results indicate significant improvements in emission image quality using the Bayesian approach, in comparison to filtered backprojection, particularly when reprojections of the MAP transmission image are used in place of the standard attenuation correction factors
Qualitative and quantitative analysis of reconstructed images using projections with noises
International Nuclear Information System (INIS)
Lopes, R.T.; Assis, J.T. de
1988-01-01
The reconstruction of a two-dimencional image from one-dimensional projections in an analytic algorithm ''convolution method'' is simulated on a microcomputer. In this work it was analysed the effects caused in the reconstructed image in function of the number of projections and noise level added to the projection data. Qualitative and quantitative (distortion and image noise) comparison were done with the original image and the reconstructed images. (author) [pt
Standard digital reference images for titanium castings
American Society for Testing and Materials. Philadelphia
2010-01-01
1.1 The digital reference images provided in the adjunct to this standard illustrate various types and degrees of discontinuities occurring in titanium castings. Use of this standard for the specification or grading of castings requires procurement of the adjunct digital reference images, which illustrate the discontinuity types and severity levels. They are intended to provide the following: 1.1.1 A guide enabling recognition of titanium casting discontinuities and their differentiation both as to type and degree through digital radiographic examination. 1.1.2 Example digital radiographic illustrations of discontinuities and a nomenclature for reference in acceptance standards, specifications and drawings. 1.2 The digital reference images consist of seventeen digital files each illustrating eight grades of increasing severity. The files illustrate seven common discontinuity types representing casting sections up to 1-in. (25.4-mm). 1.3 The reference radiographs were developed for casting sections up to 1...
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
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
International Nuclear Information System (INIS)
Katsura, Masaki; Sato, Jiro; Akahane, Masaaki; Matsuda, Izuru; Ishida, Masanori; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni
2013-01-01
Objectives: To evaluate the impact on image quality of three different image reconstruction techniques in the cervicothoracic region: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). Methods: Forty-four patients underwent unenhanced standard-of-care clinical computed tomography (CT) examinations which included the cervicothoracic region with a 64-row multidetector CT scanner. Images were reconstructed with FBP, 50% ASIR-FBP blending (ASIR50), and MBIR. Two radiologists assessed the cervicothoracic region in a blinded manner for streak artifacts, pixilated blotchy appearances, critical reproduction of visually sharp anatomical structures (thyroid gland, common carotid artery, and esophagus), and overall diagnostic acceptability. Objective image noise was measured in the internal jugular vein. Data were analyzed using the sign test and pair-wise Student's t-test. Results: MBIR images had significant lower quantitative image noise (8.88 ± 1.32) compared to ASIR images (18.63 ± 4.19, P 0.9 for ASIR vs. FBP for both readers). MBIR images were all diagnostically acceptable. Unique features of MBIR images included pixilated blotchy appearances, which did not adversely affect diagnostic acceptability. Conclusions: MBIR significantly improves image noise and streak artifacts of the cervicothoracic region over ASIR and FBP. MBIR is expected to enhance the value of CT examinations for areas where image noise and streak artifacts are problematic
Isotope specific resolution recovery image reconstruction in high resolution PET imaging
Energy Technology Data Exchange (ETDEWEB)
Kotasidis, Fotis A. [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland and Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, M20 3LJ, Manchester (United Kingdom); Angelis, Georgios I. [Faculty of Health Sciences, Brain and Mind Research Institute, University of Sydney, NSW 2006, Sydney (Australia); Anton-Rodriguez, Jose; Matthews, Julian C. [Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Reader, Andrew J. [Montreal Neurological Institute, McGill University, Montreal QC H3A 2B4, Canada and Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King' s College London, St. Thomas’ Hospital, London SE1 7EH (United Kingdom); Zaidi, Habib [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva (Switzerland); Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30 001, Groningen 9700 RB (Netherlands)
2014-05-15
Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution
Isotope specific resolution recovery image reconstruction in high resolution PET imaging
International Nuclear Information System (INIS)
Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib
2014-01-01
Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution
Isotope specific resolution recovery image reconstruction in high resolution PET imaging.
Kotasidis, Fotis A; Angelis, Georgios I; Anton-Rodriguez, Jose; Matthews, Julian C; Reader, Andrew J; Zaidi, Habib
2014-05-01
Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution recovery image reconstruction. The
Pragmatic fully 3D image reconstruction for the MiCES mouse imaging PET scanner
International Nuclear Information System (INIS)
Lee, Kisung; Kinahan, Paul E; Fessler, Jeffrey A; Miyaoka, Robert S; Janes, Marie; Lewellen, Tom K
2004-01-01
We present a pragmatic approach to image reconstruction for data from the micro crystal elements system (MiCES) fully 3D mouse imaging positron emission tomography (PET) scanner under construction at the University of Washington. Our approach is modelled on fully 3D image reconstruction used in clinical PET scanners, which is based on Fourier rebinning (FORE) followed by 2D iterative image reconstruction using ordered-subsets expectation-maximization (OSEM). The use of iterative methods allows modelling of physical effects (e.g., statistical noise, detector blurring, attenuation, etc), while FORE accelerates the reconstruction process by reducing the fully 3D data to a stacked set of independent 2D sinograms. Previous investigations have indicated that non-stationary detector point-spread response effects, which are typically ignored for clinical imaging, significantly impact image quality for the MiCES scanner geometry. To model the effect of non-stationary detector blurring (DB) in the FORE+OSEM(DB) algorithm, we have added a factorized system matrix to the ASPIRE reconstruction library. Initial results indicate that the proposed approach produces an improvement in resolution without an undue increase in noise and without a significant increase in the computational burden. The impact on task performance, however, remains to be evaluated
Structure Assisted Compressed Sensing Reconstruction of Undersampled AFM Images
DEFF Research Database (Denmark)
Oxvig, Christian Schou; Arildsen, Thomas; Larsen, Torben
2017-01-01
reconstruction algorithms that enables the use of our proposed structure model in the reconstruction process. Through a large set of reconstructions, the general reconstruction capability improvement achievable using our structured model is shown both quantitatively and qualitatively. Specifically, our...
3D surface reconstruction using optical flow for medical imaging
International Nuclear Information System (INIS)
Weng, Nan; Yang, Yee-Hong; Pierson, R.
1996-01-01
The recovery of a 3D model from a sequence of 2D images is very useful in medical image analysis. Image sequences obtained from the relative motion between the object and the camera or the scanner contain more 3D information than a single image. Methods to visualize the computed tomograms can be divided into two approaches: the surface rendering approach and the volume rendering approach. A new surface rendering method using optical flow is proposed. Optical flow is the apparent motion in the image plane produced by the projection of the real 3D motion onto 2D image. In this paper, the object remains stationary while the scanner undergoes translational motion. The 3D motion of an object can be recovered from the optical flow field using additional constraints. By extracting the surface information from 3D motion, it is possible to get an accurate 3D model of the object. Both synthetic and real image sequences have been used to illustrate the feasibility of the proposed method. The experimental results suggest that the proposed method is suitable for the reconstruction of 3D models from ultrasound medical images as well as other computed tomograms
Image reconstruction methods for the PBX-M pinhole camera
International Nuclear Information System (INIS)
Holland, A.; Powell, E.T.; Fonck, R.J.
1990-03-01
This paper describes two methods which have been used to reconstruct the soft x-ray emission profile of the PBX-M tokamak from the projected images recorded by the PBX-M pinhole camera. Both methods must accurately represent the shape of the reconstructed profile while also providing a degree of immunity to noise in the data. The first method is a simple least squares fit to the data. This has the advantage of being fast and small, and thus easily implemented on the PDP-11 computer used to control the video digitizer for the pinhole camera. The second method involves the application of a maximum entropy algorithm to an overdetermined system. This has the advantage of allowing the use of a default profile. This profile contains additional knowledge about the plasma shape which can be obtained from equilibrium fits to the external magnetic measurements. Additionally the reconstruction is guaranteed positive, and the fit to the data can be relaxed by specifying both the amount and distribution of noise in the image. The algorithm described has the advantage of being considerably faster, for an overdetermined system, than the usual Lagrange multiplier approach to finding the maximum entropy solution. 13 refs., 24 figs
A filtering approach to image reconstruction in 3D SPECT
International Nuclear Information System (INIS)
Bronnikov, Andrei V.
2000-01-01
We present a new approach to three-dimensional (3D) image reconstruction using analytical inversion of the exponential divergent beam transform, which can serve as a mathematical model for cone-beam 3D SPECT imaging. We apply a circular cone-beam scan and assume constant attenuation inside a convex area with a known boundary, which is satisfactory in brain imaging. The reconstruction problem is reduced to an image restoration problem characterized by a shift-variant point spread function which is given analytically. The method requires two computation steps: backprojection and filtering. The modulation transfer function (MTF) of the filter is derived by means of an original methodology using the 2D Laplace transform. The filter is implemented in the frequency domain and requires 2D Fourier transform of transverse slices. In order to obtain a shift-invariant cone-beam projection-backprojection operator we resort to an approximation, assuming that the collimator has a relatively large focal length. Nevertheless, numerical experiments demonstrate surprisingly good results for detectors with relatively short focal lengths. The use of a wavelet-based filtering algorithm greatly improves the stability to Poisson noise. (author)
Application of DIRI dynamic infrared imaging in reconstructive surgery
Pawlowski, Marek; Wang, Chengpu; Jin, Feng; Salvitti, Matthew; Tenorio, Xavier
2006-04-01
We have developed the BioScanIR System based on QWIP (Quantum Well Infrared Photodetector). Data collected by this sensor are processed using the DIRI (Dynamic Infrared Imaging) algorithms. The combination of DIRI data processing methods with the unique characteristics of the QWIP sensor permit the creation of a new imaging modality capable of detecting minute changes in temperature at the surface of the tissue and organs associated with blood perfusion due to certain diseases such as cancer, vascular disease and diabetes. The BioScanIR System has been successfully applied in reconstructive surgery to localize donor flap feeding vessels (perforators) during the pre-surgical planning stage. The device is also used in post-surgical monitoring of skin flap perfusion. Since the BioScanIR is mobile; it can be moved to the bedside for such monitoring. In comparison to other modalities, the BioScanIR can localize perforators in a single, 20 seconds scan with definitive results available in minutes. The algorithms used include (FFT) Fast Fourier Transformation, motion artifact correction, spectral analysis and thermal image scaling. The BioScanIR is completely non-invasive and non-toxic, requires no exogenous contrast agents and is free of ionizing radiation. In addition to reconstructive surgery applications, the BioScanIR has shown promise as a useful functional imaging modality in neurosurgery, drug discovery in pre-clinical animal models, wound healing and peripheral vascular disease management.
Improved proton computed tomography by dual modality image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Hansen, David C., E-mail: dch@ki.au.dk; Bassler, Niels [Experimental Clinical Oncology, Aarhus University, 8000 Aarhus C (Denmark); Petersen, Jørgen Breede Baltzer [Medical Physics, Aarhus University Hospital, 8000 Aarhus C (Denmark); Sørensen, Thomas Sangild [Computer Science, Aarhus University, 8000 Aarhus C, Denmark and Clinical Medicine, Aarhus University, 8200 Aarhus N (Denmark)
2014-03-15
Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360
Improved proton computed tomography by dual modality image reconstruction
International Nuclear Information System (INIS)
Hansen, David C.; Bassler, Niels; Petersen, Jørgen Breede Baltzer; Sørensen, Thomas Sangild
2014-01-01
Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360
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
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
Clinical applications of imaging reconstruction by virtual sonography
International Nuclear Information System (INIS)
Mori, Akihiro; Oohashi, Noritsugu; Maruyama, Takako; Tatebe, Hideharu; Fushimi, Nobutoshi; Asano, Takayuki; Inoue, Hiroshi; Okuno, Masataka
2008-01-01
One of the pitfalls in managing multiple liver tumors is the difficulty in identifying individual tumors on ultrasonography. Computed tomography (CT)-assisted virtual sonography has been shown to improve sonographic diagnosis, however it requires additional equipment and software. We have developed a simple reconstruction method of virtual sonography (SRVS). We reconstructed SRVS mimicking ultrasonographic images, utilizing a workstation software attached to a multi-detector row CT system without any additional program. We have performed SRVS in 32 patients with 41 liver tumors that could hardly be identify on ultrasonography. SRVS assisted the identification of malignant form non-pathologic ones and thereby contributed to the appropriate clinical strategy including radiofrequency ablation (RFA) (18 tumors), liver biopsy (2 tumors), other therapies (4 tumors) and follow-up (17 tumors). We have developed virtual sonography using conventional CT software. SRVS seems useful in the clinical practice in managing liver tumors. (author)
Image reconstruction from multiple fan-beam projections
International Nuclear Information System (INIS)
Jelinek, J.; Overton, T.R.
1984-01-01
Special-purpose third-generation fan-beam CT systems can be greatly simplified by limiting the number of detectors, but this requires a different mode of data collection to provide a set of projections appropriate to the required spatial resolution in the reconstructed image. Repeated rotation of the source-detector fan, combined with shift of the detector array and perhaps offset of the source with respect to the fan's axis after each 360 0 rotation(cycle), provides a fairly general pattern of projection space filling. The authors' investigated the problem of optimal data-collection geometry for a multiple-rotation fan-beam scanner and of corresponding reconstruction algorithm
Spectral image reconstruction using an edge preserving spatio-spectral Wiener estimation.
Urban, Philipp; Rosen, Mitchell R; Berns, Roy S
2009-08-01
Reconstruction of spectral images from camera responses is investigated using an edge preserving spatio-spectral Wiener estimation. A Wiener denoising filter and a spectral reconstruction Wiener filter are combined into a single spatio-spectral filter using local propagation of the noise covariance matrix. To preserve edges the local mean and covariance matrix of camera responses is estimated by bilateral weighting of neighboring pixels. We derive the edge-preserving spatio-spectral Wiener estimation by means of Bayesian inference and show that it fades into the standard Wiener reflectance estimation shifted by a constant reflectance in case of vanishing noise. Simulation experiments conducted on a six-channel camera system and on multispectral test images show the performance of the filter, especially for edge regions. A test implementation of the method is provided as a MATLAB script at the first author's website.
A Case Series of Rapid Prototyping and Intraoperative Imaging in Orbital Reconstruction
Lim, Christopher G.T.; Campbell, Duncan I.; Cook, Nicholas; Erasmus, Jason
2014-01-01
In Christchurch Hospital, rapid prototyping (RP) and intraoperative imaging are the standard of care in orbital trauma and has been used since February 2013. RP allows the fabrication of an anatomical model to visualize complex anatomical structures which is dimensionally accurate and cost effective. This assists diagnosis, planning, and preoperative implant adaptation for orbital reconstruction. Intraoperative imaging involves a computed tomography scan during surgery to evaluate surgical implants and restored anatomy and allows the clinician to correct errors in implant positioning that may occur during the same procedure. This article aims to demonstrate the potential clinical and cost saving benefits when both these technologies are used in orbital reconstruction which minimize the need for revision surgery. PMID:26000080
A case series of rapid prototyping and intraoperative imaging in orbital reconstruction.
Lim, Christopher G T; Campbell, Duncan I; Cook, Nicholas; Erasmus, Jason
2015-06-01
In Christchurch Hospital, rapid prototyping (RP) and intraoperative imaging are the standard of care in orbital trauma and has been used since February 2013. RP allows the fabrication of an anatomical model to visualize complex anatomical structures which is dimensionally accurate and cost effective. This assists diagnosis, planning, and preoperative implant adaptation for orbital reconstruction. Intraoperative imaging involves a computed tomography scan during surgery to evaluate surgical implants and restored anatomy and allows the clinician to correct errors in implant positioning that may occur during the same procedure. This article aims to demonstrate the potential clinical and cost saving benefits when both these technologies are used in orbital reconstruction which minimize the need for revision surgery.
Dillman, Jonathan R.; Goodsitt, Mitchell M.; Christodoulou, Emmanuel G.; Keshavarzi, Nahid; Strouse, Peter J.
2014-01-01
Purpose To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection. Materials and Methods Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDIvol) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis. Results In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDIvol was 46% (range, 19%–65%) and mean decrease in SSDE was 44% (range, 19%–64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P ASIR. Conclusion CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality. © RSNA, 2013 Online supplemental material is available for this article. PMID:24091359
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
parallel to the image plane. This effect decreases the sum of the image, thereby also affecting the mean, standard deviation, and SNR of the image. All back-projected events associated with a simulated point source intersected the voxel containing the source and the FWHM of the back-projected image was similar to that obtained from the marching method. Conclusions: The slight deficit to image quality observed with the threshold-based back-projection algorithm described here is outweighed by the 75% reduction in computation time. The implementation of this method requires the development of an optimum threshold function, which determines the overall accuracy of the method. This makes the algorithm well-suited to applications involving the reconstruction of many large images, where the time invested in threshold development is offset by the decreased image reconstruction time. Implemented in a parallel-computing environment, the threshold-based algorithm has the potential to provide real-time dose verification for radiation therapy.
The quest for standards in medical imaging
Energy Technology Data Exchange (ETDEWEB)
Gibaud, Bernard, E-mail: bernard.gibaud@irisa.fr [INSERM, VisAGeS U746 Unit/Project, Faculty of Medicine, Campus de Villejean, F-35043 Rennes (France); INRIA, VisAGeS U746 Unit/Project, IRISA, Campus de Beaulieu, F-35042 Rennes (France); University of Rennes I-CNRS UMR 6074, IRISA, Campus de Beaulieu, F-35042 Rennes (France)
2011-05-15
This article focuses on standards supporting interoperability and system integration in the medical imaging domain. We introduce the basic concepts and actors and we review the most salient achievements in this domain, especially with the DICOM standard, and the definition of IHE integration profiles. We analyze and discuss what was successful, and what could still be more widely adopted by industry. We then sketch out a perspective of what should be done next, based on our vision of new requirements for the next decade. In particular, we discuss the challenges of a more explicit sharing of image and image processing semantics, and we discuss the help that semantic web technologies (and especially ontologies) may bring to achieving this goal.
The quest for standards in medical imaging
International Nuclear Information System (INIS)
Gibaud, Bernard
2011-01-01
This article focuses on standards supporting interoperability and system integration in the medical imaging domain. We introduce the basic concepts and actors and we review the most salient achievements in this domain, especially with the DICOM standard, and the definition of IHE integration profiles. We analyze and discuss what was successful, and what could still be more widely adopted by industry. We then sketch out a perspective of what should be done next, based on our vision of new requirements for the next decade. In particular, we discuss the challenges of a more explicit sharing of image and image processing semantics, and we discuss the help that semantic web technologies (and especially ontologies) may bring to achieving this goal.
Assessment of the impact of modeling axial compression on PET image reconstruction.
Belzunce, Martin A; Reader, Andrew J
2017-10-01
To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher
A new reconstruction strategy for image improvement in pinhole SPECT
International Nuclear Information System (INIS)
Zeniya, Tsutomu; Watabe, Hiroshi; Kim, Kyeong Min; Teramoto, Noboru; Hayashi, Takuya; Iida, Hidehiro; Aoi, Toshiyuki; Sohlberg, Antti; Kudo, Hiroyuki
2004-01-01
Pinhole single-photon emission computed tomography (SPECT) is able to provide information on the biodistribution of several radioligands in small laboratory animals, but has limitations associated with non-uniform spatial resolution or axial blurring. We have hypothesised that this blurring is due to incompleteness of the projection data acquired by a single circular pinhole orbit, and have evaluated a new strategy for accurate image reconstruction with better spatial resolution uniformity. A pinhole SPECT system using two circular orbits and a dedicated three-dimensional ordered subsets expectation maximisation (3D-OSEM) reconstruction method were developed. In this system, not the camera but the object rotates, and the two orbits are at 90 and 45 relative to the object's axis. This system satisfies Tuy's condition, and is thus able to provide complete data for 3D pinhole SPECT reconstruction within the whole field of view (FOV). To evaluate this system, a series of experiments was carried out using a multiple-disk phantom filled with 99m Tc solution. The feasibility of the proposed method for small animal imaging was tested with a mouse bone study using 99m Tc-hydroxymethylene diphosphonate. Feldkamp's filtered back-projection (FBP) method and the 3D-OSEM method were applied to these data sets, and the visual and statistical properties were examined. Axial blurring, which was still visible at the edge of the FOV even after applying the conventional 3D-OSEM instead of FBP for single-orbit data, was not visible after application of 3D-OSEM using two-orbit data. 3D-OSEM using two-orbit data dramatically reduced the resolution non-uniformity and statistical noise, and also demonstrated considerably better image quality in the mouse scan. This system may be of use in quantitative assessment of bio-physiological functions in small animals. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Zheng Guoyan [Institute for Surgical Technology and Biomechanics, University of Bern, Stauffacherstrasse 78, CH-3014 Bern (Switzerland)
2010-04-15
Purpose: The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Methods: Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction. The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. Results: The technique could reconstruct the surface models of all 14 pelvises directly from the landmark
Level-set-based reconstruction algorithm for EIT lung images: first clinical results.
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)
Fast MR image reconstruction for partially parallel imaging with arbitrary k-space trajectories.
Ye, Xiaojing; Chen, Yunmei; Lin, Wei; Huang, Feng
2011-03-01
Both acquisition and reconstruction speed are crucial for magnetic resonance (MR) imaging in clinical applications. In this paper, we present a fast reconstruction algorithm for SENSE in partially parallel MR imaging with arbitrary k-space trajectories. The proposed method is a combination of variable splitting, the classical penalty technique and the optimal gradient method. Variable splitting and the penalty technique reformulate the SENSE model with sparsity regularization as an unconstrained minimization problem, which can be solved by alternating two simple minimizations: One is the total variation and wavelet based denoising that can be quickly solved by several recent numerical methods, whereas the other one involves a linear inversion which is solved by the optimal first order gradient method in our algorithm to significantly improve the performance. Comparisons with several recent parallel imaging algorithms indicate that the proposed method significantly improves the computation efficiency and achieves state-of-the-art reconstruction quality.
Application of the fractional Fourier transform to image reconstruction in MRI.
Parot, Vicente; Sing-Long, Carlos; Lizama, Carlos; Tejos, Cristian; Uribe, Sergio; Irarrazaval, Pablo
2012-07-01
The classic paradigm for MRI requires a homogeneous B(0) field in combination with linear encoding gradients. Distortions are produced when the B(0) is not homogeneous, and several postprocessing techniques have been developed to correct them. Field homogeneity is difficult to achieve, particularly for short-bore magnets and higher B(0) fields. Nonlinear magnetic components can also arise from concomitant fields, particularly in low-field imaging, or intentionally used for nonlinear encoding. In any of these situations, the second-order component is key, because it constitutes the first step to approximate higher-order fields. We propose to use the fractional Fourier transform for analyzing and reconstructing the object's magnetization under the presence of quadratic fields. The fractional fourier transform provides a precise theoretical framework for this. We show how it can be used for reconstruction and for gaining a better understanding of the quadratic field-induced distortions, including examples of reconstruction for simulated and in vivo data. The obtained images have improved quality compared with standard Fourier reconstructions. The fractional fourier transform opens a new paradigm for understanding the MR signal generated by an object under a quadratic main field or nonlinear encoding. Copyright © 2011 Wiley Periodicals, Inc.
Influence of image reconstruction methods on statistical parametric mapping of brain PET images
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Yin Dayi; Chen Yingmao; Yao Shulin; Shao Mingzhe; Yin Ling; Tian Jiahe; Cui Hongyan
2007-01-01
Objective: Statistic parametric mapping (SPM) was widely recognized as an useful tool in brain function study. The aim of this study was to investigate if imaging reconstruction algorithm of PET images could influence SPM of brain. Methods: PET imaging of whole brain was performed in six normal volunteers. Each volunteer had two scans with true and false acupuncturing. The PET scans were reconstructed using ordered subsets expectation maximization (OSEM) and filtered back projection (FBP) with 3 varied parameters respectively. The images were realigned, normalized and smoothed using SPM program. The difference between true and false acupuncture scans was tested using a matched pair t test at every voxel. Results: (1) SPM corrected multiple comparison (P corrected uncorrected <0.001): SPM derived from the images with different reconstruction method were different. The largest difference, in number and position of the activated voxels, was noticed between FBP and OSEM re- construction algorithm. Conclusions: The method of PET image reconstruction could influence the results of SPM uncorrected multiple comparison. Attention should be paid when the conclusion was drawn using SPM uncorrected multiple comparison. (authors)
Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging.
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Xingjian Yu
Full Text Available In dynamic Positron Emission Tomography (PET, an estimate of the radio activity concentration is obtained from a series of frames of sinogram data taken at ranging in duration from 10 seconds to minutes under some criteria. So far, all the well-known reconstruction algorithms require known data statistical properties. It limits the speed of data acquisition, besides, it is unable to afford the separated information about the structure and the variation of shape and rate of metabolism which play a major role in improving the visualization of contrast for some requirement of the diagnosing in application. This paper presents a novel low rank-based activity map reconstruction scheme from emission sinograms of dynamic PET, termed as SLCR representing Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging. In this method, the stationary background is formulated as a low rank component while variations between successive frames are abstracted to the sparse. The resulting nuclear norm and l1 norm related minimization problem can also be efficiently solved by many recently developed numerical methods. In this paper, the linearized alternating direction method is applied. The effectiveness of the proposed scheme is illustrated on three data sets.
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.
Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm
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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)
Reconstruction algorithm medical imaging DRR; Algoritmo de construccion de imagenes medicas DRR
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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)
PET image reconstruction using multi-parametric anato-functional priors
Mehranian, Abolfazl; Belzunce, Martin A.; Niccolini, Flavia; Politis, Marios; Prieto, Claudia; Turkheimer, Federico; Hammers, Alexander; Reader, Andrew J.
2017-08-01
In this study, we investigate the application of multi-parametric anato-functional (MR-PET) priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address the limitations of the conventional anatomical priors in the presence of PET-MR mismatches. In addition to partial volume correction benefits, the suitability of these priors for reconstruction of low-count PET data is also introduced and demonstrated, comparing to standard maximum-likelihood (ML) reconstruction of high-count data. The conventional local Tikhonov and total variation (TV) priors and current state-of-the-art anatomical priors including the Kaipio, non-local Tikhonov prior with Bowsher and Gaussian similarity kernels are investigated and presented in a unified framework. The Gaussian kernels are calculated using both voxel- and patch-based feature vectors. To cope with PET and MR mismatches, the Bowsher and Gaussian priors are extended to multi-parametric priors. In addition, we propose a modified joint Burg entropy prior that by definition exploits all parametric information in the MAP reconstruction of PET data. The performance of the priors was extensively evaluated using 3D simulations and two clinical brain datasets of [18F]florbetaben and [18F]FDG radiotracers. For simulations, several anato-functional mismatches were intentionally introduced between the PET and MR images, and furthermore, for the FDG clinical dataset, two PET-unique active tumours were embedded in the PET data. Our simulation results showed that the joint Burg entropy prior far outperformed the conventional anatomical priors in terms of preserving PET unique lesions, while still reconstructing functional boundaries with corresponding MR boundaries. In addition, the multi-parametric extension of the Gaussian and Bowsher priors led to enhanced preservation of edge and PET unique features and also an improved bias-variance performance. In agreement with the simulation results, the clinical results
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.
Johnson, R K; Wright, C K; Gandhi, A; Charny, M C; Barr, L
2013-03-01
We performed a cost analysis (using UK 2011/12 NHS tariffs as a proxy for cost) comparing immediate breast reconstruction using the new one-stage technique of acellular dermal matrix (Strattice™) with implant versus the standard alternative techniques of tissue expander (TE)/implant as a two-stage procedure and latissimus dorsi (LD) flap reconstruction. Clinical report data were collected for operative time, length of stay, outpatient procedures, and number of elective and emergency admissions in our first consecutive 24 patients undergoing one-stage Strattice reconstruction. Total cost to the NHS based on tariff, assuming top-up payments to cover Strattice acquisition costs, was assessed and compared to the two historical control groups matched on key variables. Eleven patients having unilateral Strattice reconstruction were compared to 10 having TE/implant reconstruction and 10 having LD flap and implant reconstruction. Thirteen patients having bilateral Strattice reconstruction were compared to 12 having bilateral TE/implant reconstruction. Total costs were: unilateral Strattice, £3685; unilateral TE, £4985; unilateral LD and implant, £6321; bilateral TE, £5478; and bilateral Strattice, £6771. The cost analysis shows a financial advantage of using acellular dermal matrix (Strattice) in unilateral breast reconstruction versus alternative procedures. The reimbursement system in England (Payment by Results) is based on disease-related groups similar to that of many countries across Europe and tariffs are based on reported hospital costs, making this analysis of relevance in other countries. Copyright © 2013 Elsevier Ltd. All rights reserved.
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.
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Papoular, R
1997-07-01
The Fourier Transform is of central importance to Crystallography since it allows the visualization in real space of tridimensional scattering densities pertaining to physical systems from diffraction data (powder or single-crystal diffraction, using x-rays, neutrons, electrons or else). In turn, this visualization makes it possible to model and parametrize these systems, the crystal structures of which are eventually refined by Least-Squares techniques (e.g., the Rietveld method in the case of Powder Diffraction). The Maximum Entropy Method (sometimes called MEM or MaxEnt) is a general imaging technique, related to solving ill-conditioned inverse problems. It is ideally suited for tackling undetermined systems of linear questions (for which the number of variables is much larger than the number of equations). It is already being applied successfully in Astronomy, Radioastronomy and Medical Imaging. The advantages of using MAXIMUM Entropy over conventional Fourier and `difference Fourier` syntheses stem from the following facts: MaxEnt takes the experimental error bars into account; MaxEnt incorporate Prior Knowledge (e.g., the positivity of the scattering density in some instances); MaxEnt allows density reconstructions from incompletely phased data, as well as from overlapping Bragg reflections; MaxEnt substantially reduces truncation errors to which conventional experimental Fourier reconstructions are usually prone. The principles of Maximum Entropy imaging as applied to Crystallography are first presented. The method is then illustrated by a detailed example specific to Neutron Diffraction: the search for proton in solids. (author). 17 refs.
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.
International Nuclear Information System (INIS)
Tong, S; Alessio, A M; Kinahan, P E
2010-01-01
The addition of accurate system modeling in PET image reconstruction results in images with distinct noise texture and characteristics. In particular, the incorporation of point spread functions (PSF) into the system model has been shown to visually reduce image noise, but the noise properties have not been thoroughly studied. This work offers a systematic evaluation of noise and signal properties in different combinations of reconstruction methods and parameters. We evaluate two fully 3D PET reconstruction algorithms: (1) OSEM with exact scanner line of response modeled (OSEM+LOR), (2) OSEM with line of response and a measured point spread function incorporated (OSEM+LOR+PSF), in combination with the effects of four post-reconstruction filtering parameters and 1-10 iterations, representing a range of clinically acceptable settings. We used a modified NEMA image quality (IQ) phantom, which was filled with 68 Ge and consisted of six hot spheres of different sizes with a target/background ratio of 4:1. The phantom was scanned 50 times in 3D mode on a clinical system to provide independent noise realizations. Data were reconstructed with OSEM+LOR and OSEM+LOR+PSF using different reconstruction parameters, and our implementations of the algorithms match the vendor's product algorithms. With access to multiple realizations, background noise characteristics were quantified with four metrics. Image roughness and the standard deviation image measured the pixel-to-pixel variation; background variability and ensemble noise quantified the region-to-region variation. Image roughness is the image noise perceived when viewing an individual image. At matched iterations, the addition of PSF leads to images with less noise defined as image roughness (reduced by 35% for unfiltered data) and as the standard deviation image, while it has no effect on background variability or ensemble noise. In terms of signal to noise performance, PSF-based reconstruction has a 7% improvement in
Reconstruction, Processing and Display of 3D-Images
International Nuclear Information System (INIS)
Lenz, R.
1986-01-01
In the last few years a number of methods have been developed which can produce true 3D images, volumes of density values. We review two of these techniques (confocal microscopy and X-ray tomography) which were used in the reconstruction of some of our images. The other images came from transmission electron microscopes, gammacameras and magnetic resonance scanners. A new algorithm is suggested which uses projection onto convex sets to improve the depth resolution in the microscopy case. Since we use a TV-monitor as display device we have to project 3D volumes to 2D images. We use the following type of projections: reprojections, range images, colorcoded depth and shaded surface displays. Shaded surface displays use the surface gradient to compute the gray value in the projection. We describe how this gradient can be computed from the range image and from the original density volume. Normally we compute a whole series of projections where the volume is rotated some degrees between two projections. In a separate display session we can display these images in stereo and motion. We describe how noise reduction filters, gray value transformations, geometric manipulations, gradient filters, texture filters and binary techniques can be used to remove uninteresting points from the volume. Finally, a filter design strategy is developed which is based on the optimal basis function approach by Hummel. We show that for a large class of patterns, in images of arbitrary dimensions, the optimal basis functions are rotation-invariant operators as introduced by Danielsson in the 2D case. We also describe how the orientation of a pattern can be computed from its feature vector. (With 107 refs.) (author)
Poisson image reconstruction with Hessian Schatten-norm regularization.
Lefkimmiatis, Stamatios; Unser, Michael
2013-11-01
Poisson inverse problems arise in many modern imaging applications, including biomedical and astronomical ones. The main challenge is to obtain an estimate of the underlying image from a set of measurements degraded by a linear operator and further corrupted by Poisson noise. In this paper, we propose an efficient framework for Poisson image reconstruction, under a regularization approach, which depends on matrix-valued regularization operators. In particular, the employed regularizers involve the Hessian as the regularization operator and Schatten matrix norms as the potential functions. For the solution of the problem, we propose two optimization algorithms that are specifically tailored to the Poisson nature of the noise. These algorithms are based on an augmented-Lagrangian formulation of the problem and correspond to two variants of the alternating direction method of multipliers. Further, we derive a link that relates the proximal map of an l(p) norm with the proximal map of a Schatten matrix norm of order p. This link plays a key role in the development of one of the proposed algorithms. Finally, we provide experimental results on natural and biological images for the task of Poisson image deblurring and demonstrate the practical relevance and effectiveness of the proposed framework.
Automatic cortical surface reconstruction of high-resolution T1 echo planar imaging data.
Renvall, Ville; Witzel, Thomas; Wald, Lawrence L; Polimeni, Jonathan R
2016-07-01
Echo planar imaging (EPI) is the method of choice for the majority of functional magnetic resonance imaging (fMRI), yet EPI is prone to geometric distortions and thus misaligns with conventional anatomical reference data. The poor geometric correspondence between functional and anatomical data can lead to severe misplacements and corruption of detected activation patterns. However, recent advances in imaging technology have provided EPI data with increasing quality and resolution. Here we present a framework for deriving cortical surface reconstructions directly from high-resolution EPI-based reference images that provide anatomical models exactly geometric distortion-matched to the functional data. Anatomical EPI data with 1mm isotropic voxel size were acquired using a fast multiple inversion recovery time EPI sequence (MI-EPI) at 7T, from which quantitative T1 maps were calculated. Using these T1 maps, volumetric data mimicking the tissue contrast of standard anatomical data were synthesized using the Bloch equations, and these T1-weighted data were automatically processed using FreeSurfer. The spatial alignment between T2(⁎)-weighted EPI data and the synthetic T1-weighted anatomical MI-EPI-based images was improved compared to the conventional anatomical reference. In particular, the alignment near the regions vulnerable to distortion due to magnetic susceptibility differences was improved, and sampling of the adjacent tissue classes outside of the cortex was reduced when using cortical surface reconstructions derived directly from the MI-EPI reference. The MI-EPI method therefore produces high-quality anatomical data that can be automatically segmented with standard software, providing cortical surface reconstructions that are geometrically matched to the BOLD fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.
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.
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Sebastian Schaetz
2017-01-01
Full Text Available Purpose. To develop generic optimization strategies for image reconstruction using graphical processing units (GPUs in magnetic resonance imaging (MRI and to exemplarily report on our experience with a highly accelerated implementation of the nonlinear inversion (NLINV algorithm for dynamic MRI with high frame rates. Methods. The NLINV algorithm is optimized and ported to run on a multi-GPU single-node server. The algorithm is mapped to multiple GPUs by decomposing the data domain along the channel dimension. Furthermore, the algorithm is decomposed along the temporal domain by relaxing a temporal regularization constraint, allowing the algorithm to work on multiple frames in parallel. Finally, an autotuning method is presented that is capable of combining different decomposition variants to achieve optimal algorithm performance in different imaging scenarios. Results. The algorithm is successfully ported to a multi-GPU system and allows online image reconstruction with high frame rates. Real-time reconstruction with low latency and frame rates up to 30 frames per second is demonstrated. Conclusion. Novel parallel decomposition methods are presented which are applicable to many iterative algorithms for dynamic MRI. Using these methods to parallelize the NLINV algorithm on multiple GPUs, it is possible to achieve online image reconstruction with high frame rates.
Model-based image reconstruction for four-dimensional PET
International Nuclear Information System (INIS)
Li Tianfang; Thorndyke, Brian; Schreibmann, Eduard; Yang Yong; Xing Lei
2006-01-01
Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case
Compositional-prior-guided image reconstruction algorithm for multi-modality imaging
Fang, Qianqian; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.
2010-01-01
The development of effective multi-modality imaging methods typically requires an efficient information fusion model, particularly when combining structural images with a complementary imaging modality that provides functional information. We propose a composition-based image segmentation method for X-ray digital breast tomosynthesis (DBT) and a structural-prior-guided image reconstruction for a combined DBT and diffuse optical tomography (DOT) breast imaging system. Using the 3D DBT images from 31 clinically measured healthy breasts, we create an empirical relationship between the X-ray intensities for adipose and fibroglandular tissue. We use this relationship to then segment another 58 healthy breast DBT images from 29 subjects into compositional maps of different tissue types. For each breast, we build a weighted-graph in the compositional space and construct a regularization matrix to incorporate the structural priors into a finite-element-based DOT image reconstruction. Use of the compositional priors enables us to fuse tissue anatomy into optical images with less restriction than when using a binary segmentation. This allows us to recover the image contrast captured by DOT but not by DBT. We show that it is possible to fine-tune the strength of the structural priors by changing a single regularization parameter. By estimating the optical properties for adipose and fibroglandular tissue using the proposed algorithm, we found the results are comparable or superior to those estimated with expert-segmentations, but does not involve the time-consuming manual selection of regions-of-interest. PMID:21258460
Image Reconstruction and Evaluation: Applications on Micro-Surfaces and Lenna Image Representation
Directory of Open Access Journals (Sweden)
Mohammad Mayyas
2016-09-01
Full Text Available This article develops algorithms for the characterization and the visualization of micro-scale features using a small number of sample points, with the goal of mitigating the measurement shortcomings, which are often destructive or time consuming. The popular measurement techniques that are used in imaging of micro-surfaces include the 3D stylus or interferometric profilometry and Scanning Electron Microscopy (SEM, where both could represent the micro-surface characteristics in terms of 3D dimensional topology and greyscale image, respectively. Such images could be highly dense; therefore, traditional image processing techniques might be computationally expensive. We implement the algorithms in several case studies to rapidly examine the microscopic features of micro-surface of Microelectromechanical System (MEMS, and then we validate the results using a popular greyscale image; i.e., “Lenna” image. The contributions of this research include: First, development of local and global algorithm based on modified Thin Plate Spline (TPS model to reconstruct high resolution images of the micro-surface’s topography, and its derivatives using low resolution images. Second, development of a bending energy algorithm from our modified TPS model for filtering out image defects. Finally, development of a computationally efficient technique, referred to as Windowing, which combines TPS and Linear Sequential Estimation (LSE methods, to enhance the visualization of images. The Windowing technique allows rapid image reconstruction based on the reduction of inverse problem.
An Optimized Method for Terrain Reconstruction Based on Descent Images
Directory of Open Access Journals (Sweden)
Xu Xinchao
2016-02-01
Full Text Available An optimization method is proposed to perform high-accuracy terrain reconstruction of the landing area of Chang’e III. First, feature matching is conducted using geometric model constraints. Then, the initial terrain is obtained and the initial normal vector of each point is solved on the basis of the initial terrain. By changing the vector around the initial normal vector in small steps a set of new vectors is obtained. By combining these vectors with the direction of light and camera, the functions are set up on the basis of a surface reflection model. Then, a series of gray values is derived by solving the equations. The new optimized vector is recorded when the obtained gray value is closest to the corresponding pixel. Finally, the optimized terrain is obtained after iteration of the vector field. Experiments were conducted using the laboratory images and descent images of Chang’e III. The results showed that the performance of the proposed method was better than that of the classical feature matching method. It can provide a reference for terrain reconstruction of the landing area in subsequent moon exploration missions.
Iterative feature refinement for accurate undersampled MR image reconstruction
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)
MR imaging of the augmented and reconstructed breast
International Nuclear Information System (INIS)
Ivanov, V.; Kirova, G.
2013-01-01
Full text: Introduction: Various diagnostic methods are used to assess the changes in both the integrity of the implant, and the fibrous capsule of breast parenchyma. MRI has advantages over other diagnostic methods providing high tissue contrast, multi-faceted imaging and lack of ionizing radiation. What you will learn: MRI evaluation of breast augmentation approaches and their complications, MRI assessment of disease with malignant and benign characteristics in patients with breast implants, MRI assessment of breast reconstruction with autologous tissue. Discussion: Mammography after augmentation and reconstructive mammoplasty is hampered by the deformation of the breast parenchyma of the implant and the reduced compression. Postoperative scarring is also difficult to assess. MRI evaluation of implant rupture is accurate using the findings specific to it - linguine sign, teardrop sign or siliconomas. According to Gorczyca et al. MRI has a sensitivity 94% and specificity 97% in the evaluation of rupture. MRI mammography is highly sensitive - between 90 and 95%, in the detection of malignant, but it has limited specificity, which is its disadvantage. Malignant lesions can be represented as fibroadenomas, postoperative and inflammatory changes. Conclusion: Difficulties in the diagnosis of rupture of the implant, the primary and recurrent carcinoma based on clinical examination and inconclusive data from mammography and ultrasound imaging make MRI the method of choice in the evaluation of patients with breast implants
A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.
Konkle, Justin J; Goodwill, Patrick W; Hensley, Daniel W; Orendorff, Ryan D; Lustig, Michael; Conolly, Steven M
2015-01-01
Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.
Fully three-dimensional image reconstruction in radiology and nuclear medicine. Proceedings
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NONE
2011-07-01
The proceedings of the meeting on ''fully three-dimensional image reconstruction in radiology and nuclear medicine'' covers contributions on the following topics: CT imaging, PET imaging, fidelity; iterative and few-view CT, CT-analytical; PET/SPECT Compton analytical; doses - spectral methods; phase contrast; compressed sensing- sparse reconstruction; special issues; motion - cardiac.
Towards establishing compact imaging spectrometer standards
Slonecker, E. Terrence; Allen, David W.; Resmini, Ronald G.
2016-01-01
Remote sensing science is currently undergoing a tremendous expansion in the area of hyperspectral imaging (HSI) technology. Spurred largely by the explosive growth of Unmanned Aerial Vehicles (UAV), sometimes called Unmanned Aircraft Systems (UAS), or drones, HSI capabilities that once required access to one of only a handful of very specialized and expensive sensor systems are now miniaturized and widely available commercially. Small compact imaging spectrometers (CIS) now on the market offer a number of hyperspectral imaging capabilities in terms of spectral range and sampling. The potential uses of HSI/CIS on UAVs/UASs seem limitless. However, the rapid expansion of unmanned aircraft and small hyperspectral sensor capabilities has created a number of questions related to technological, legal, and operational capabilities. Lightweight sensor systems suitable for UAV platforms are being advertised in the trade literature at an ever-expanding rate with no standardization of system performance specifications or terms of reference. To address this issue, both the U.S. Geological Survey and the National Institute of Standards and Technology are eveloping draft standards to meet these issues. This paper presents the outline of a combined USGS/NIST cooperative strategy to develop and test a characterization methodology to meet the needs of a new and expanding UAV/CIS/HSI user community.
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.
Directory of Open Access Journals (Sweden)
Luís F Seoane
2015-04-01
Full Text Available We provide a proof of concept for an EEG-based reconstruction of a visual image which is on a user's mind. Our approach is based on the Rapid Serial Visual Presentation (RSVP of polygon primitives and Brain-Computer Interface (BCI technology. In an experimental setup, subjects were presented bursts of polygons: some of them contributed to building a target image (because they matched the shape and/or color of the target while some of them did not. The presentation of the contributing polygons triggered attention-related EEG patterns. These Event Related Potentials (ERPs could be determined using BCI classification and could be matched to the stimuli that elicited them. These stimuli (i.e. the ERP-correlated polygons were accumulated in the display until a satisfactory reconstruction of the target image was reached. As more polygons were accumulated, finer visual details were attained resulting in more challenging classification tasks. In our experiments, we observe an average classification accuracy of around 75%. An in-depth investigation suggests that many of the misclassifications were not misinterpretations of the BCI concerning the users' intent, but rather caused by ambiguous polygons that could contribute to reconstruct several different images. When we put our BCI-image reconstruction in perspective with other RSVP BCI paradigms, there is large room for improvement both in speed and accuracy. These results invite us to be optimistic. They open a plethora of possibilities to explore non-invasive BCIs for image reconstruction both in healthy and impaired subjects and, accordingly, suggest interesting recreational and clinical applications.
Brief review of image reconstruction methods for imaging in nuclear medicine
International Nuclear Information System (INIS)
Murayama, Hideo
1999-01-01
Emission computed tomography (ECT) has as its major emphasis the quantitative determination of the moment to moment changes in the chemistry and flow physiology of injected or inhaled compounds labeled with radioactive atoms in a human body. The major difference lies in the fact that ECT seeks to describe the location and intensity of sources of emitted photons in an attenuating medium whereas transmission X-ray computed tomography (TCT) seeks to determine the distribution of the attenuating medium. A second important difference between ECT and TCT is that of available statistics. ECT statistics are low because each photon without control in emitting direction must be detected and analyzed, not as in TCT. The following sections review the historical development of image reconstruction methods for imaging in nuclear medicine, relevant intrinsic concepts for image reconstruction on ECT, and current status of volume imaging as well as a unique approach on iterative techniques for ECT. (author). 130 refs
First results of genetic algorithm application in ML image reconstruction in emission tomography
International Nuclear Information System (INIS)
Smolik, W.
1999-01-01
This paper concerns application of genetic algorithm in maximum likelihood image reconstruction in emission tomography. The example of genetic algorithm for image reconstruction is presented. The genetic algorithm was based on the typical genetic scheme modified due to the nature of solved problem. The convergence of algorithm was examined. The different adaption functions, selection and crossover methods were verified. The algorithm was tested on simulated SPECT data. The obtained results of image reconstruction are discussed. (author)
International Nuclear Information System (INIS)
Matsuo, Shinro; Nakajima, Kenichi; Okuda, Koichi; Yamashina, Shohei; Sakata, Kazuyuki; Momose, Mitsuru; Hashimoto, Jun; Kumita, Shinichiro; Kawano, Masaya
2009-01-01
The standard patterns of myocardial radiotracer distribution of 123 I-metaiodobenzylguanidine (MIBG) and 123 I-β-methyl-p-iodophenyl-pentadecanoic acid (BMIPP) should be defined in a Japanese population. The purpose of this study was to present and provide data on the characteristics of MIBG and BMIPP with respect to myocardial single photon emission computed tomography. The normal database included 123 I-MIBG and 123 I-BMIPP imaging and a 99 mTc-sestamibi/tetrofosmin myocardial perfusion study. The projection images were transferred by digital imaging and communications in medicine (DICOM) format and reconstructed and analyzed with polar maps. The projection data from multiple centers were successfully transferred to a common format for single photon emission computed tomography (SPECT) reconstruction. When the average values were analyzed using a 17-segment model, MIBG uptake in the inferior and apical wall appeared to be slightly lower than anterior uptake (P 99m Tc-tracer uptake (P<0.05). Myocardial sympathetic nerve and metabolic scintigraphy data that were specific for the Japanese population were generated and found to be different from that of perfusion tracers. The normal database can serve as a standard for nuclear cardiology work conducted in Japan. (author)
Isotope specific resolution recovery image reconstruction in high resolution PET imaging
Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib
Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to
Image improvement and three-dimensional reconstruction using holographic image processing
Stroke, G. W.; Halioua, M.; Thon, F.; Willasch, D. H.
1977-01-01
Holographic computing principles make possible image improvement and synthesis in many cases of current scientific and engineering interest. Examples are given for the improvement of resolution in electron microscopy and 3-D reconstruction in electron microscopy and X-ray crystallography, following an analysis of optical versus digital computing in such applications.
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Han, H; Xing, L [Stanford University, Palo Alto, CA (United States); Liang, Z [Stony Brook University, Stony Brook, NY (United States)
2016-06-15
Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.
International Nuclear Information System (INIS)
Han, H; Xing, L; Liang, Z
2016-01-01
Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern for each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.
Watanabe, Shota; Sakaguchi, Kenta; Hosono, Makoto; Ishii, Kazunari; Murakami, Takamichi; Ichikawa, Katsuhiro
The purpose of this study was to evaluate the effect of a hybrid-type iterative reconstruction method on Z-score mapping of hyperacute stroke in unenhanced computed tomography (CT) images. We used a hybrid-type iterative reconstruction [adaptive statistical iterative reconstruction (ASiR)] implemented in a CT system (Optima CT660 Pro advance, GE Healthcare). With 15 normal brain cases, we reconstructed CT images with a filtered back projection (FBP) and ASiR with a blending factor of 100% (ASiR100%). Two standardized normal brain data were created from normal databases of FBP images (FBP-NDB) and ASiR100% images (ASiR-NDB), and standard deviation (SD) values in basal ganglia were measured. The Z-score mapping was performed for 12 hyperacute stroke cases by using FBP-NDB and ASiR-NDB, and compared Z-score value on hyperacute stroke area and normal area between FBP-NDB and ASiR-NDB. By using ASiR-NDB, the SD value of standardized brain was decreased by 16%. The Z-score value of ASiR-NDB on hyperacute stroke area was significantly higher than FBP-NDB (pASiR100% for Z-score mapping had potential to improve the accuracy of Z-score mapping.
International Nuclear Information System (INIS)
Rampado, O.; Bossi, L.; Garabello, D.; Davini, O.; Ropolo, R.
2012-01-01
Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10–22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from −2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.
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Rampado, O., E-mail: orampado@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Bossi, L., E-mail: laura-bossi@hotmail.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Garabello, D., E-mail: dgarabello@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Davini, O., E-mail: odavini@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Ropolo, R., E-mail: rropolo@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy)
2012-11-15
Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10-22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from -2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.
X-ray volumetric imaging in image-guided radiotherapy: The new standard in on-treatment imaging
International Nuclear Information System (INIS)
McBain, Catherine A.; Henry, Ann M.; Sykes, Jonathan; Amer, Ali; Marchant, Tom; Moore, Christopher M.; Davies, Julie; Stratford, Julia; McCarthy, Claire; Porritt, Bridget; Williams, Peter; Khoo, Vincent S.; Price, Pat
2006-01-01
Purpose: X-ray volumetric imaging (XVI) for the first time allows for the on-treatment acquisition of three-dimensional (3D) kV cone beam computed tomography (CT) images. Clinical imaging using the Synergy System (Elekta, Crawley, UK) commenced in July 2003. This study evaluated image quality and dose delivered and assessed clinical utility for treatment verification at a range of anatomic sites. Methods and Materials: Single XVIs were acquired from 30 patients undergoing radiotherapy for tumors at 10 different anatomic sites. Patients were imaged in their setup position. Radiation doses received were measured using TLDs on the skin surface. The utility of XVI in verifying target volume coverage was qualitatively assessed by experienced clinicians. Results: X-ray volumetric imaging acquisition was completed in the treatment position at all anatomic sites. At sites where a full gantry rotation was not possible, XVIs were reconstructed from projection images acquired from partial rotations. Soft-tissue definition of organ boundaries allowed direct assessment of 3D target volume coverage at all sites. Individual image quality depended on both imaging parameters and patient characteristics. Radiation dose ranged from 0.003 Gy in the head to 0.03 Gy in the pelvis. Conclusions: On-treatment XVI provided 3D verification images with soft-tissue definition at all anatomic sites at acceptably low radiation doses. This technology sets a new standard in treatment verification and will facilitate novel adaptive radiotherapy techniques
Bindu, G; Semenov, S
2013-01-01
This paper describes an efficient two-dimensional fused image reconstruction approach for Microwave Tomography (MWT). Finite Difference Time Domain (FDTD) models were created for a viable MWT experimental system having the transceivers modelled using thin wire approximation with resistive voltage sources. Born Iterative and Distorted Born Iterative methods have been employed for image reconstruction with the extremity imaging being done using a differential imaging technique. The forward solver in the imaging algorithm employs the FDTD method of solving the time domain Maxwell's equations with the regularisation parameter computed using a stochastic approach. The algorithm is tested with 10% noise inclusion and successful image reconstruction has been shown implying its robustness.
Directory of Open Access Journals (Sweden)
Mingjian Sun
2015-01-01
Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.
MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction
International Nuclear Information System (INIS)
Chen, G; Pan, X; Stayman, J; Samei, E
2014-01-01
Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical
Bruce, Iain P.; Karaman, M. Muge; Rowe, Daniel B.
2012-01-01
The acquisition of sub-sampled data from an array of receiver coils has become a common means of reducing data acquisition time in MRI. Of the various techniques used in parallel MRI, SENSitivity Encoding (SENSE) is one of the most common, making use of a complex-valued weighted least squares estimation to unfold the aliased images. It was recently shown in Bruce et al. [Magn. Reson. Imag. 29(2011):1267–1287] that when the SENSE model is represented in terms of a real-valued isomorphism, it assumes a skew-symmetric covariance between receiver coils, as well as an identity covariance structure between voxels. In this manuscript, we show that not only is the skew-symmetric coil covariance unlike that of real data, but the estimated covariance structure between voxels over a time series of experimental data is not an identity matrix. As such, a new model, entitled SENSE-ITIVE, is described with both revised coil and voxel covariance structures. Both the SENSE and SENSE-ITIVE models are represented in terms of real-valued isomorphisms, allowing for a statistical analysis of reconstructed voxel means, variances, and correlations resulting from the use of different coil and voxel covariance structures used in the reconstruction processes to be conducted. It is shown through both theoretical and experimental illustrations that the miss-specification of the coil and voxel covariance structures in the SENSE model results in a lower standard deviation in each voxel of the reconstructed images, and thus an artificial increase in SNR, compared to the standard deviation and SNR of the SENSE-ITIVE model where both the coil and voxel covariances are appropriately accounted for. It is also shown that there are differences in the correlations induced by the reconstruction operations of both models, and consequently there are differences in the correlations estimated throughout the course of reconstructed time series. These differences in correlations could result in meaningful
International Nuclear Information System (INIS)
Son, J.H.
1979-01-01
Because of much attractiveness, digital reconstruction of image from ultrasonic hologram by computer has been widely studied in recent years. But the method of digital reconstruction of image is displayed in the plain only, so study is done mainly of the hologram obtained from bidimensional objects. Many applications of the ultrasonic holography such as the non-distructive testing and the ultrasonic diagnosis are mostly of the tridimensional object. In the ordinary digital reconstruction of the image from the hologram obtained from tridimensional object, a question of hidden-image problem arises, and the separated reconstruction of the image for the considered part of the object is required. In this paper, multi-diffraction by tridimensional object is assumed to have linearity, ie. superposition property by each diffraction of bidimensional objects. And a new algorithm is proposed here, namely reconstructed image for considered one of bidimensional objects in tridimensional object obtained by means of operation from the two holograms tilted in unequal angles. Such tilted holograms are obtained from the tilted linear array receivers by scanning method. That images can be reconstructed by the operation from two holograms means that the new algorithm is verified. And another new method of the transformation of hologram, that is, transformation of a hologram to arbitrarily tilted hologram, has been proved valid. The reconstructed images obtained with the method of transformation and the method of operation, are the images reconstructed from one hologram by the tridimensional object and more distinctly separated that any images mentioned above. (author)
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Katsura, Masaki, E-mail: mkatsura-tky@umin.ac.jp [Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 (Japan); Sato, Jiro; Akahane, Masaaki; Matsuda, Izuru; Ishida, Masanori; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni [Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 (Japan)
2013-02-15
Objectives: To evaluate the impact on image quality of three different image reconstruction techniques in the cervicothoracic region: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). Methods: Forty-four patients underwent unenhanced standard-of-care clinical computed tomography (CT) examinations which included the cervicothoracic region with a 64-row multidetector CT scanner. Images were reconstructed with FBP, 50% ASIR-FBP blending (ASIR50), and MBIR. Two radiologists assessed the cervicothoracic region in a blinded manner for streak artifacts, pixilated blotchy appearances, critical reproduction of visually sharp anatomical structures (thyroid gland, common carotid artery, and esophagus), and overall diagnostic acceptability. Objective image noise was measured in the internal jugular vein. Data were analyzed using the sign test and pair-wise Student's t-test. Results: MBIR images had significant lower quantitative image noise (8.88 ± 1.32) compared to ASIR images (18.63 ± 4.19, P < 0.01) and FBP images (26.52 ± 5.8, P < 0.01). Significant improvements in streak artifacts of the cervicothoracic region were observed with the use of MBIR (P < 0.001 each for MBIR vs. the other two image data sets for both readers), while no significant difference was observed between ASIR and FBP (P > 0.9 for ASIR vs. FBP for both readers). MBIR images were all diagnostically acceptable. Unique features of MBIR images included pixilated blotchy appearances, which did not adversely affect diagnostic acceptability. Conclusions: MBIR significantly improves image noise and streak artifacts of the cervicothoracic region over ASIR and FBP. MBIR is expected to enhance the value of CT examinations for areas where image noise and streak artifacts are problematic.
Current profile reconstruction using electron temperature imaging diagnostics
International Nuclear Information System (INIS)
Tritz, K.; Stutman, D.; Delgado-Aparicio, L.F.; Finkenthal, M.; Pacella, D.; Kaita, R.; Stratton, B.; Sabbagh, S.
2004-01-01
Flux surface shape information can be used to constrain the current profile for reconstruction of the plasma equilibrium. One method of inferring flux surface shape relies on plasma x-ray emission; however, deviations from the flux surfaces due to impurity and density asymmetries complicate the interpretation. Electron isotherm surfaces should correspond well to the plasma flux surfaces, and equilibrium constraint modeling using this isotherm information constrains the current profile. The KFIT code is used to assess the profile uncertainty and to optimize the number, location and SNR required for the Te detectors. As Te imaging detectors we consider tangentially viewing, vertically spaced, linear gas electron multiplier arrays operated in pulse height analysis (PHA) mode and multifoil soft x-ray arrays. Isoflux coordinate sets provided by T e measurements offer a strong constraint on the equilibrium reconstruction in both a stacked horizontal array configuration and a crossed horizontal and vertical beam system, with q 0 determined to within ±4%. The required SNR can be provided with either PHA or multicolor diagnostic techniques, though the multicolor system requires ∼x4 better statistics for comparable final errors
An implementation of the NiftyRec medical imaging library for PIXE-tomography reconstruction
Michelet, C.; Barberet, P.; Desbarats, P.; Giovannelli, J.-F.; Schou, C.; Chebil, I.; Delville, M.-H.; Gordillo, N.; Beasley, D. G.; Devès, G.; Moretto, P.; Seznec, H.
2017-08-01
A new development of the TomoRebuild software package is presented, including ;thick sample; correction for non linear X-ray production (NLXP) and X-ray absorption (XA). As in the previous versions, C++ programming with standard libraries was used for easier portability. Data reduction requires different steps which may be run either from a command line instruction or via a user friendly interface, developed as a portable Java plugin in ImageJ. All experimental and reconstruction parameters can be easily modified, either directly in the ASCII parameter files or via the ImageJ interface. A detailed user guide in English is provided. Sinograms and final reconstructed images are generated in usual binary formats that can be read by most public domain graphic softwares. New MLEM and OSEM methods are proposed, using optimized methods from the NiftyRec medical imaging library. An overview of the different medical imaging methods that have been used for ion beam microtomography applications is presented. In TomoRebuild, PIXET data reduction is performed for each chemical element independently and separately from STIMT, except for two steps where the fusion of STIMT and PIXET data is required: the calculation of the correction matrix and the normalization of PIXET data to obtain mass fraction distributions. Correction matrices for NLXP and XA are calculated using procedures extracted from the DISRA code, taking into account a large X-ray detection solid angle. For this, the 3D STIMT mass density distribution is used, considering a homogeneous global composition. A first example of PIXET experiment using two detectors is presented. Reconstruction results are compared and found in good agreement between different codes: FBP, NiftyRec MLEM and OSEM of the TomoRebuild software package, the original DISRA, its accelerated version provided in JPIXET and the accelerated MLEM version of JPIXET, with or without correction.
Focal dynamics of multiple filaments: Microscopic imaging and reconstruction
International Nuclear Information System (INIS)
Kiran, P. Prem; Bagchi, Suman; Kumar, G. Ravindra; Krishnan, Siva Rama; Arnold, C. L.; Couairon, A.
2010-01-01
We observe the complete dynamics of the propagation of very intense, femtosecond laser pulses in air under tight focusing conditions via direct imaging of the entire interaction zone. The whole life history of the focused pulses is then reconstructed by means of numerical simulations. We show that beam breakup leads to a dual-rate increase in filament numbers with laser power. Linearly and circularly polarized pulses give rise to beam breakup and fusion governed by external focusing conditions. For tight focusing conditions, intensity saturation due to plasma generation and nonlinear losses does not limit the intensity growth, thereby giving access to a new propagation regime featured by an efficient laser energy deposition in fully ionized air and intense 10 15 W/cm 2 pulses at the focus.
Magnetic resonance imaging evaluation of cruciate ligaments after arthroscopic reconstruction
Directory of Open Access Journals (Sweden)
Amit Kharat
2017-01-01
Full Text Available Background: Due to increase in road traffic and sports injuries, tears of anterior cruciate ligament (ACL and the posterior cruciate ligament (PCL of the knee are common. Magnetic resonance imaging (MRI is emerging as an important tool of diagnosis and evaluation of these injuries. Methods: We carried out a prospective study on role of MRI on ten patients who had undergone ACL or PCL repair over a period of six months. In this report we present three illustrative cases to capture the spectrum of findings in our series to underline the role of MRI in management of such injuries and discuss the modalities of the procedure. Results: In our series, as demonstrated by the cases, MRI had an important role in diagnosis and evaluation of injuries to the cruciate ligaments. Conclusion: MRI can play an important role, particularly in tertiary centres, in diagnosis and evaluation of reconstructed ACL and PCL ligaments of the knee joint.
International Nuclear Information System (INIS)
Ogino, Takashi; Egawa, Sunao
1991-01-01
New algorithms of CT value correction for reconstructing a radiotherapy simulation image through axial CT images were developed. One, designated plane weighting method, is to correct CT value in proportion to the position of the beam element passing through the voxel. The other, designated solid weighting method, is to correct CT value in proportion to the length of the beam element passing through the voxel and the volume of voxel. Phantom experiments showed fair spatial resolution in the transverse direction. In the longitudinal direction, however, spatial resolution of under slice thickness could not be obtained. Contrast resolution was equivalent for both methods. In patient studies, the reconstructed radiotherapy simulation image was almost similar in visual perception of the density resolution to a simulation film taken by X-ray simulator. (author)
Consistent reconstruction of 4D fetal heart ultrasound images to cope with fetal motion.
Tanner, Christine; Flach, Barbara; Eggenberger, Céline; Mattausch, Oliver; Bajka, Michael; Goksel, Orcun
2017-08-01
4D ultrasound imaging of the fetal heart relies on reconstructions from B-mode images. In the presence of fetal motion, current approaches suffer from artifacts, which are unrecoverable for single sweeps. We propose to use many sweeps and exploit the resulting redundancy to automatically recover from motion by reconstructing a 4D image which is consistent in phase, space, and time. An interactive visualization framework to view animated ultrasound slices from 4D reconstructions on arbitrary planes was developed using a magnetically tracked mock probe. We first quantified the performance of 10 4D reconstruction formulations on simulated data. Reconstructions of 14 in vivo sequences by a baseline, the current state-of-the-art, and the proposed approach were then visually ranked with respect to temporal quality on orthogonal views. Rankings from 5 observers showed that the proposed 4D reconstruction approach significantly improves temporal image quality in comparison with the baseline. The 4D reconstructions of the baseline and the proposed methods were then inspected interactively for accessibility to clinically important views and rated for their clinical usefulness by an ultrasound specialist in obstetrics and gynecology. The reconstructions by the proposed method were rated as 'very useful' in 71% and were statistically significantly more useful than the baseline reconstructions. Multi-sweep fetal heart ultrasound acquisitions in combination with consistent 4D image reconstruction improves quality as well as clinical usefulness of the resulting 4D images in the presence of fetal motion.
Cone-beam and fan-beam image reconstruction algorithms based on spherical and circular harmonics
International Nuclear Information System (INIS)
Zeng, Gengsheng L; Gullberg, Grant T
2004-01-01
A cone-beam image reconstruction algorithm using spherical harmonic expansions is proposed. The reconstruction algorithm is in the form of a summation of inner products of two discrete arrays of spherical harmonic expansion coefficients at each cone-beam point of acquisition. This form is different from the common filtered backprojection algorithm and the direct Fourier reconstruction algorithm. There is no re-sampling of the data, and spherical harmonic expansions are used instead of Fourier expansions. As a special case, a new fan-beam image reconstruction algorithm is also derived in terms of a circular harmonic expansion. Computer simulation results for both cone-beam and fan-beam algorithms are presented for circular planar orbit acquisitions. The algorithms give accurate reconstructions; however, the implementation of the cone-beam reconstruction algorithm is computationally intensive. A relatively efficient algorithm is proposed for reconstructing the central slice of the image when a circular scanning orbit is used
Priori mask guided image reconstruction (p-MGIR) for ultra-low dose cone-beam computed tomography
Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Kahler, Darren L.; Liu, Chihray; Lu, Bo
2015-11-01
Recently, the compressed sensing (CS) based iterative reconstruction method has received attention because of its ability to reconstruct cone beam computed tomography (CBCT) images with good quality using sparsely sampled or noisy projections, thus enabling dose reduction. However, some challenges remain. In particular, there is always a tradeoff between image resolution and noise/streak artifact reduction based on the amount of regularization weighting that is applied uniformly across the CBCT volume. The purpose of this study is to develop a novel low-dose CBCT reconstruction algorithm framework called priori mask guided image reconstruction (p-MGIR) that allows reconstruction of high-quality low-dose CBCT images while preserving the image resolution. In p-MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions: (1) where anatomical structures are complex, and (2) where intensities are relatively uniform. The priori mask, which is the key concept of the p-MGIR algorithm, was defined as the matrix that distinguishes between the two separate CBCT regions where the resolution needs to be preserved and where streak or noise needs to be suppressed. We then alternately updated each part of image by solving two sub-minimization problems iteratively, where one minimization was focused on preserving the edge information of the first part while the other concentrated on the removal of noise/artifacts from the latter part. To evaluate the performance of the p-MGIR algorithm, a numerical head-and-neck phantom, a Catphan 600 physical phantom, and a clinical head-and-neck cancer case were used for analysis. The results were compared with the standard Feldkamp-Davis-Kress as well as conventional CS-based algorithms. Examination of the p-MGIR algorithm showed that high-quality low-dose CBCT images can be reconstructed without compromising the image resolution. For both phantom and the patient cases, the p-MGIR is able to achieve a clinically
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.
International Nuclear Information System (INIS)
Liu, Patrick T.; Pavlicek, William P.; Peter, Mary B.; Roberts, Catherine C.; Paden, Robert G.; Spangehl, Mark J.
2009-01-01
Despite recent advances in CT technology, metal orthopedic implants continue to cause significant artifacts on many CT exams, often obscuring diagnostic information. We performed this prospective study to evaluate the effectiveness of an experimental metal artifact reduction (MAR) image reconstruction program for CT. We examined image quality on CT exams performed in patients with hip arthroplasties as well as other types of implanted metal orthopedic devices. The exam raw data were reconstructed using two different methods, the standard filtered backprojection (FBP) program and the MAR program. Images were evaluated for quality of the metal-cement-bone interfaces, trabeculae ≤1 cm from the metal, trabeculae 5 cm apart from the metal, streak artifact, and overall soft tissue detail. The Wilcoxon Rank Sum test was used to compare the image scores from the large and small prostheses. Interobserver agreement was calculated. When all patients were grouped together, the MAR images showed mild to moderate improvement over the FBP images. However, when the cases were divided by implant size, the MAR images consistently received higher image quality scores than the FBP images for large metal implants (total hip prostheses). For small metal implants (screws, plates, staples), conversely, the MAR images received lower image quality scores than the FBP images due to blurring artifact. The difference of image scores for the large and small implants was significant (p=0.002). Interobserver agreement was found to be high for all measures of image quality (k>0.9). The experimental MAR reconstruction algorithm significantly improved CT image quality for patients with large metal implants. However, the MAR algorithm introduced blurring artifact that reduced image quality with small metal implants. (orig.)
Reconstructed coronal views of CT and isotopic images of the pancreas
International Nuclear Information System (INIS)
Kasuga, Toshio; Kobayashi, Toshio; Nakanishi, Fumiko
1980-01-01
To compare functional images of the pancreas by scintigraphy with morphological views of the pancreas by CT, CT coronal views of the pancreas were reconstructed. As CT coronal views were reconstructed from the routine scanning, there was a problem in longitudinal spatial resolution. However, almost satisfactory total images of the pancreas were obtained by improving images adequately. In 27 patients whose diseases had been confirmed, it was easy to compare pancreatic scintigrams with pancreatic CT images by using reconstructed CT coronal views, and information which had not been obtained by original CT images could be obtained by using reconstructed CT coronal views. Especially, defects on pancreatic images and the shape of pancreas which had not been visualized clearly by scintigraphy alone could be visualized by using reconstructed CT coronal views of the pancreas. (Tsunoda, M.)
Lemoigne, Yves
2008-01-01
This volume collects the lectures presented at the ninth ESI School held at Archamps (FR) in November 2006 and is dedicated to nuclear physics applications in molecular imaging. The lectures focus on the multiple facets of image reconstruction processing and management and illustrate the role of digital imaging in clinical practice. Medical computing and image reconstruction are introduced by analysing the underlying physics principles and their implementation, relevant quality aspects, clinical performance and recent advancements in the field. Several stages of the imaging process are specifically addressed, e.g. optimisation of data acquisition and storage, distributed computing, physiology and detector modelling, computer algorithms for image reconstruction and measurement in tomography applications, for both clinical and biomedical research applications. All topics are presented with didactical language and style, making this book an appropriate reference for students and professionals seeking a comprehen...
Guidelines for imaging retinoblastoma: imaging principles and MRI standardization
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Graaf, Pim de; Rodjan, Firazia; Castelijns, Jonas A. [VU University Medical Center, Department of Radiology, Amsterdam (Netherlands); Goericke, Sophia [University Hospital, Department of Diagnostic and Interventional Radiology and Neuroradiology, Essen (Germany); Galluzzi, Paolo [Azienda Ospedaliera e Universitaria Senese, Policlinico ' ' Le Scotte' ' , Unit of Diagnostic and Therapeutic Neuroradiology, Siena (Italy); Maeder, Philippe [CHUV, Service de Radiodiagnostic et Radiologie Interventionelle, Lausanne (Switzerland); Brisse, Herve J. [Institut Curie, Departement d' Imagerie, Paris (France)
2012-01-15
Retinoblastoma is the most common intraocular tumor in children. The diagnosis is usually established by the ophthalmologist on the basis of fundoscopy and US. Together with US, high-resolution MRI has emerged as an important imaging modality for pretreatment assessment, i.e. for diagnostic confirmation, detection of local tumor extent, detection of associated developmental malformation of the brain and detection of associated intracranial primitive neuroectodermal tumor (trilateral retinoblastoma). Minimum requirements for pretreatment diagnostic evaluation of retinoblastoma or mimicking lesions are presented, based on consensus among members of the European Retinoblastoma Imaging Collaboration (ERIC). The most appropriate techniques for imaging in a child with leukocoria are reviewed. CT is no longer recommended. Implementation of a standardized MRI protocol for retinoblastoma in clinical practice may benefit children worldwide, especially those with hereditary retinoblastoma, since a decreased use of CT reduces the exposure to ionizing radiation. (orig.)
Tricarico, Francesco; Hlavacek, Anthony M.; Schoepf, U. Joseph; Ebersberger, Ullrich; Nance, John W.; Vliegenthart, Rozemarijn; Cho, Young Jun; Spears, J. Reid; Secchi, Francesco; Savino, Giancarlo; Marano, Riccardo; Schoenberg, Stefan O.; Bonomo, Lorenzo; Apfaltrer, Paul
To evaluate image quality (IQ) of low-radiation-dose paediatric cardiovascular CT angiography (CTA), comparing iterative reconstruction in image space (IRIS) and sinogram-affirmed iterative reconstruction (SAFIRE) with filtered back-projection (FBP) and estimate the potential for further dose
Reconstruction-of-difference (RoD) imaging for cone-beam CT neuro-angiography
Wu, P.; Stayman, J. W.; Mow, M.; Zbijewski, W.; Sisniega, A.; Aygun, N.; Stevens, R.; Foos, D.; Wang, X.; Siewerdsen, J. H.
2018-06-01
Timely evaluation of neurovasculature via CT angiography (CTA) is critical to the detection of pathology such as ischemic stroke. Cone-beam CTA (CBCT-A) systems provide potential advantages in the timely use at the point-of-care, although challenges of a relatively slow gantry rotation speed introduce tradeoffs among image quality, data consistency and data sparsity. This work describes and evaluates a new reconstruction-of-difference (RoD) approach that is robust to such challenges. A fast digital simulation framework was developed to test the performance of the RoD over standard reference reconstruction methods such as filtered back-projection (FBP) and penalized likelihood (PL) over a broad range of imaging conditions, grouped into three scenarios to test the trade-off between data consistency, data sparsity and peak contrast. Two experiments were also conducted using a CBCT prototype and an anthropomorphic neurovascular phantom to test the simulation findings in real data. Performance was evaluated primarily in terms of normalized root mean square error (NRMSE) in comparison to truth, with reconstruction parameters chosen to optimize performance in each case to ensure fair comparison. The RoD approach reduced NRMSE in reconstructed images by up to 50%–53% compared to FBP and up to 29%–31% compared to PL for each scenario. Scan protocols well suited to the RoD approach were identified that balance tradeoffs among data consistency, sparsity and peak contrast—for example, a CBCT-A scan with 128 projections acquired in 8.5 s over a 180° + fan angle half-scan for a time attenuation curve with ~8.5 s time-to-peak and 600 HU peak contrast. With imaging conditions such as the simulation scenarios of fixed data sparsity (i.e. varying levels of data consistency and peak contrast), the experiments confirmed the reduction of NRMSE by 34% and 17% compared to FBP and PL, respectively. The RoD approach demonstrated superior performance in 3D angiography
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Kim, Min Cheol; Choi, Yun Sun; KIm, Hyoung Seop; Choi, Nam Hong [Nowon Eulji Medical Center, Eulji University, Seoul (Korea, Republic of)
2016-11-15
Reconstruction of a ruptured anterior cruciate ligament (ACL) is a well-established procedure for repair of ACL injury. Despite improvement of surgical and rehabilitation techniques over the past decades, up to 25% of patients still fail to regain satisfactory function after an ACL reconstruction. With development of CT imaging techniques for reducing metal artifacts, multi-planar reconstruction, and three-dimensional reconstruction, early post-operative imaging is increasingly being used to provide immediate feedback to surgeons regarding tunnel positioning, fixation, and device placement. Early post-operative radiography and CT imaging are easy to perform and serve as the baseline examinations for future reference.
International Nuclear Information System (INIS)
Reinartz, S.D.; Diefenbach, B.S.; Kuhl, C.K.; Mahnken, A.H.; Allmendinger, T.
2012-01-01
To compare image quality in coronary artery computed tomography angiography (cCTA) using reconstructions with automated phase detection and Reconstructions computed with Identical Filling of the heart (RIF). Seventy-four patients underwent ECG-gated dual source CT (DSCT) between November 2009 and July 2010 for suspected coronary heart disease (n = 35), planning of transcatheter aortic valve replacement (n = 34) or evaluation of ventricular function (n = 5). Image data sets by the RIF formula and automated phase detection were computed and evaluated with the AHA 15-segment model and a 5-grade Likert scale (1: poor, 5: excellent quality). Subgroups regarding rhythm (sinus rhythm = SR; arrhythmia = ARR) and potential premedication were evaluated by a per-segment, per-vessel and per-patient analysis. RIF significantly improved image quality in 10 of 15 coronary segments (P < 0.05). More diagnostic segments were provided by RIF regarding the entire cohort (n = 693 vs. 590, P < 0.001) and all of the subgroups (e.g. ARR: n = 143 vs. 72, P < 0.001). In arrhythmic patients (n = 19), more diagnostic vessels (e.g. LAD: n = 10 vs. 3; P < 0.014) and complete data sets (n = 7 vs. 1; P < 0.001) were produced. RIF reconstruction is superior to automatic diastolic non-edited reconstructions, especially in arrhythmic patients. RIF theory provides a physiological approach for determining the optimal image reconstruction point in ECG-gated CT angiography. (orig.)
Hussain, Fahad Ahmed; Mail, Noor; Shamy, Abdulrahman M; Suliman, Alghamdi; Saoudi, Abdelhamid
2016-05-08
Image quality is a key issue in radiology, particularly in a clinical setting where it is important to achieve accurate diagnoses while minimizing radiation dose. Some computed tomography (CT) manufacturers have introduced algorithms that claim significant dose reduction. In this study, we assessed CT image quality produced by two reconstruction algorithms provided with GE Healthcare's Discovery 690 Elite positron emission tomography (PET) CT scanner. Image quality was measured for images obtained at various doses with both conventional filtered back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR) algorithms. A stan-dard CT dose index (CTDI) phantom and a pencil ionization chamber were used to measure the CT dose at 120 kVp and an exposure of 260 mAs. Image quality was assessed using two phantoms. CT images of both phantoms were acquired at tube voltage (kV) of 120 with exposures ranging from 25 mAs to 400 mAs. Images were reconstructed using FBP and ASIR ranging from 10% to 100%, then analyzed for noise, low-contrast detectability, contrast-to-noise ratio (CNR), and modulation transfer function (MTF). Noise was 4.6 HU in water phantom images acquired at 260 mAs/FBP 120 kV and 130 mAs/50% ASIR 120 kV. The large objects (fre-quency ASIR, compared to 260 mAs/FBP. The application of ASIR for small objects (frequency >7 lp/cm) showed poor visibility compared to FBP at 260 mAs and even worse for images acquired at less than 130 mAs. ASIR blending more than 50% at low dose tends to reduce contrast of small objects (frequency >7 lp/cm). We concluded that dose reduction and ASIR should be applied with close attention if the objects to be detected or diagnosed are small (frequency > 7 lp/cm). Further investigations are required to correlate the small objects (frequency > 7 lp/cm) to patient anatomy and clinical diagnosis.
Resolution-recovery-embedded image reconstruction for a high-resolution animal SPECT system.
Zeraatkar, Navid; Sajedi, Salar; Farahani, Mohammad Hossein; Arabi, Hossein; Sarkar, Saeed; Ghafarian, Pardis; Rahmim, Arman; Ay, Mohammad Reza
2014-11-01
The small-animal High-Resolution SPECT (HiReSPECT) is a dedicated dual-head gamma camera recently designed and developed in our laboratory for imaging of murine models. Each detector is composed of an array of 1.2 × 1.2 mm(2) (pitch) pixelated CsI(Na) crystals. Two position-sensitive photomultiplier tubes (H8500) are coupled to each head's crystal. In this paper, we report on a resolution-recovery-embedded image reconstruction code applicable to the system and present the experimental results achieved using different phantoms and mouse scans. Collimator-detector response functions (CDRFs) were measured via a pixel-driven method using capillary sources at finite distances from the head within the field of view (FOV). CDRFs were then fitted by independent Gaussian functions. Thereafter, linear interpolations were applied to the standard deviation (σ) values of the fitted Gaussians, yielding a continuous map of CDRF at varying distances from the head. A rotation-based maximum-likelihood expectation maximization (MLEM) method was used for reconstruction. A fast rotation algorithm was developed to rotate the image matrix according to the desired angle by means of pre-generated rotation maps. The experiments demonstrated improved resolution utilizing our resolution-recovery-embedded image reconstruction. While the full-width at half-maximum (FWHM) radial and tangential resolution measurements of the system were over 2 mm in nearly all positions within the FOV without resolution recovery, reaching around 2.5 mm in some locations, they fell below 1.8 mm everywhere within the FOV using the resolution-recovery algorithm. The noise performance of the system was also acceptable; the standard deviation of the average counts per voxel in the reconstructed images was 6.6% and 8.3% without and with resolution recovery, respectively. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Yu Yunhan; Xia Yan; Liu Yaqiang; Wang Shi; Ma Tianyu; Chen Jing; Hong Baoyu
2013-01-01
To achieve a maximum compression of system matrix in positron emission tomography (PET) image reconstruction, we proposed a polygonal image pixel division strategy in accordance with rotationally symmetric PET geometry. Geometrical definition and indexing rule for polygonal pixels were established. Image conversion from polygonal pixel structure to conventional rectangular pixel structure was implemented using a conversion matrix. A set of test images were analytically defined in polygonal pixel structure, converted to conventional rectangular pixel based images, and correctly displayed which verified the correctness of the image definition, conversion description and conversion of polygonal pixel structure. A compressed system matrix for PET image recon was generated by tap model and tested by forward-projecting three different distributions of radioactive sources to the sinogram domain and comparing them with theoretical predictions. On a practical small animal PET scanner, a compress ratio of 12.6:1 of the system matrix size was achieved with the polygonal pixel structure, comparing with the conventional rectangular pixel based tap-mode one. OS-EM iterative image reconstruction algorithms with the polygonal and conventional Cartesian pixel grid were developed. A hot rod phantom was detected and reconstructed based on these two grids with reasonable time cost. Image resolution of reconstructed images was both 1.35 mm. We conclude that it is feasible to reconstruct and display images in a polygonal image pixel structure based on a compressed system matrix in PET image reconstruction. (authors)
Energy Technology Data Exchange (ETDEWEB)
Eck, Brendan L.; Fahmi, Rachid; Miao, Jun [Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 (United States); Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun [Philips Healthcare, Cleveland, Ohio 44143 (United States); Wilson, David L., E-mail: dlw@case.edu [Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 and Department of Radiology, Case Western Reserve University, Cleveland, Ohio 44106 (United States)
2015-10-15
Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit
4D reconstruction of the past: the image retrieval and 3D model construction pipeline
Hadjiprocopis, Andreas; Ioannides, Marinos; Wenzel, Konrad; Rothermel, Mathias; Johnsons, Paul S.; Fritsch, Dieter; Doulamis, Anastasios; Protopapadakis, Eftychios; Kyriakaki, Georgia; Makantasis, Kostas; Weinlinger, Guenther; Klein, Michael; Fellner, Dieter; Stork, Andre; Santos, Pedro
2014-08-01
One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.
Does thorax EIT image analysis depend on the image reconstruction method?
Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut
2013-04-01
Different methods were proposed to analyze the resulting images of electrical impedance tomography (EIT) measurements during ventilation. The aim of our study was to examine if the analysis methods based on back-projection deliver the same results when applied on images based on other reconstruction algorithms. Seven mechanically ventilated patients with ARDS were examined by EIT. The thorax contours were determined from the routine CT images. EIT raw data was reconstructed offline with (1) filtered back-projection with circular forward model (BPC); (2) GREIT reconstruction method with circular forward model (GREITC) and (3) GREIT with individual thorax geometry (GREITT). Three parameters were calculated on the resulting images: linearity, global ventilation distribution and regional ventilation distribution. The results of linearity test are 5.03±2.45, 4.66±2.25 and 5.32±2.30 for BPC, GREITC and GREITT, respectively (median ±interquartile range). The differences among the three methods are not significant (p = 0.93, Kruskal-Wallis test). The proportions of ventilation in the right lung are 0.58±0.17, 0.59±0.20 and 0.59±0.25 for BPC, GREITC and GREITT, respectively (p = 0.98). The differences of the GI index based on different reconstruction methods (0.53±0.16, 0.51±0.25 and 0.54±0.16 for BPC, GREITC and GREITT, respectively) are also not significant (p = 0.93). We conclude that the parameters developed for images generated with GREITT are comparable with filtered back-projection and GREITC.
A Method for Interactive 3D Reconstruction of Piecewise Planar Objects from Single Images
Sturm , Peter; Maybank , Steve
1999-01-01
International audience; We present an approach for 3D reconstruction of objects from a single image. Obviously, constraints on the 3D structure are needed to perform this task. Our approach is based on user-provided coplanarity, perpendicularity and parallelism constraints. These are used to calibrate the image and perform 3D reconstruction. The method is described in detail and results are provided.
International Nuclear Information System (INIS)
Tereshchenko, Sergei A; Potapov, D A; Podgaetskii, Vitalii M; Smirnov, A V
2002-01-01
A distorting influence of light refraction at the boundaries of scattering media on the results of tomographic reconstruction of images of radially symmetric objects is investigated. The methods for the correction of such refraction-caused distortions are described. The results of the image reconstruction for two model cylindrical objects are presented.
Influence of iterative image reconstruction on CT-based calcium score measurements
van Osch, Jochen A. C.; Mouden, Mohamed; van Dalen, Jorn A.; Timmer, Jorik R.; Reiffers, Stoffer; Knollema, Siert; Greuter, Marcel J. W.; Ottervanger, Jan Paul; Jager, Piet L.
Iterative reconstruction techniques for coronary CT angiography have been introduced as an alternative for traditional filter back projection (FBP) to reduce image noise, allowing improved image quality and a potential for dose reduction. However, the impact of iterative reconstruction on the
Energy Technology Data Exchange (ETDEWEB)
Grosser, Oliver S.; Kupitz, Dennis; Powerski, Maciej; Mohnike, Konrad; Ricke, Jens [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Wybranski, Christian [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne (Germany); Pech, Maciej [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Medical University of Gdansk, Second Department of Radiology, Gdansk (Poland); Amthauer, Holger [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Charite, Department of Nuclear Medicine, Berlin (Germany)
2017-09-15
The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP). Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers. Noise was significantly influenced by reconstruction, I, body region and circumference (all p ≤ 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p ≤ 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ≤ 0.02). The inter-rater reliability for noise and readers' confidence was good (W ≥ 0.75, p < 0.0001). Noise and readers' confidence were significantly better in AIDR-3D compared to FBP (p ≤ 0.03). Generally, IA yielded a significant reduction of the median effective dose. The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased. (orig.)
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
Experimental validation of incomplete data CT image reconstruction techniques
International Nuclear Information System (INIS)
Eberhard, J.W.; Hsiao, M.L.; Tam, K.C.
1989-01-01
X-ray CT inspection of large metal parts is often limited by x-ray penetration problems along many of the ray paths required for a complete CT data set. In addition, because of the complex geometry of many industrial parts, manipulation difficulties often prevent scanning over some range of angles. CT images reconstructed from these incomplete data sets contain a variety of artifacts which limit their usefulness in part quality determination. Over the past several years, the authors' company has developed 2 new methods of incorporating a priori information about the parts under inspection to significantly improve incomplete data CT image quality. This work reviews the methods which were developed and presents experimental results which confirm the effectiveness of the techniques. The new methods for dealing with incomplete CT data sets rely on a priori information from part blueprints (in electronic form), outer boundary information from touch sensors, estimates of part outer boundaries from available x-ray data, and linear x-ray attenuation coefficients of the part. The two methods make use of this information in different fashions. The relative performance of the two methods in detecting various flaw types is compared. Methods for accurately registering a priori information with x-ray data are also described. These results are critical to a new industrial x-ray inspection cell built for inspection of large aircraft engine parts
DEFF Research Database (Denmark)
Christensen, Nana Louise; Tolbod, Lars Poulsen
PET scans. 3) Static and dynamic images from a set of 7 patients (BSA: 1.6-2.2 m2) referred for 82Rb cardiac PET was analyzed using a range of beta factors. Results were compared to the institution’s standard clinical practice reconstruction protocol. All scans were performed on GE DMI Digital......Aim: Q.Clear reconstruction is expected to improve detection of perfusion defects in cardiac PET due to the high degree of image convergence and effective noise suppression. However, 82Rb (T½=76s) possess a special problem, since count statistics vary significantly not only between patients...... statistics using a cardiac PET phantom as well as a selection of clinical patients referred for 82Rb cardiac PET. Methods: The study consistent of 3 parts: 1) A thorax-cardiac phantom was scanned for 10 minutes after injection of 1110 MBq 82Rb. Frames at 3 different times after infusion were reconstructed...
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.)
Optimization of the Reconstruction Interval in Neurovascular 4D-CTA Imaging
Hoogenboom, T.C.H.; van Beurden, R.M.J.; van Teylingen, B.; Schenk, B.; Willems, P.W.A.
2012-01-01
Summary Time resolved whole brain CT angiography (4D-CTA) is a novel imaging technology providing information regarding blood flow. One of the factors that influence the diagnostic value of this examination is the temporal resolution, which is affected by the gantry rotation speed during acquisition and the reconstruction interval during post-processing. Post-processing determines the time spacing between two reconstructed volumes and, unlike rotation speed, does not affect radiation burden. The data sets of six patients who underwent a cranial 4D-CTA were used for this study. Raw data was acquired using a 320-slice scanner with a rotation speed of 2 Hz. The arterial to venous passage of an intravenous contrast bolus was captured during a 15 s continuous scan. The raw data was reconstructed using four different reconstruction-intervals: 0.2, 0.3, 0.5 and 1.0 s. The results were rated by two observers using a standardized score sheet. The appearance of each lesion was rated correctly in all readings. Scoring for quality of temporal resolution revealed a stepwise improvement from the 1.0 s interval to the 0.3 s interval, while no discernable improvement was noted between the 0.3 s and 0.2 s interval. An increase in temporal resolution may improve the diagnostic quality of cranial 4D-CTA. Using a rotation speed of 0.5 s, the optimal reconstruction interval appears to be 0.3 s, beyond which, changes can no longer be discerned. PMID:23217631
MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images
International Nuclear Information System (INIS)
Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J
2015-01-01
Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features
MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images
Energy Technology Data Exchange (ETDEWEB)
Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J [UT MD Anderson Cancer Center, Houston, TX (United States)
2015-06-15
Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.
Super resolution reconstruction of infrared images based on classified dictionary learning
Liu, Fei; Han, Pingli; Wang, Yi; Li, Xuan; Bai, Lu; Shao, Xiaopeng
2018-05-01
Infrared images always suffer from low-resolution problems resulting from limitations of imaging devices. An economical approach to combat this problem involves reconstructing high-resolution images by reasonable methods without updating devices. Inspired by compressed sensing theory, this study presents and demonstrates a Classified Dictionary Learning method to reconstruct high-resolution infrared images. It classifies features of the samples into several reasonable clusters and trained a dictionary pair for each cluster. The optimal pair of dictionaries is chosen for each image reconstruction and therefore, more satisfactory results is achieved without the increase in computational complexity and time cost. Experiments and results demonstrated that it is a viable method for infrared images reconstruction since it improves image resolution and recovers detailed information of targets.
Guan, Huifeng; Anastasio, Mark A.
2017-03-01
It is well-known that properly designed image reconstruction methods can facilitate reductions in imaging doses and data-acquisition times in tomographic imaging. The ability to do so is particularly important for emerging modalities such as differential X-ray phase-contrast tomography (D-XPCT), which are currently limited by these factors. An important application of D-XPCT is high-resolution imaging of biomedical samples. However, reconstructing high-resolution images from few-view tomographic measurements remains a challenging task. In this work, a two-step sub-space reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. It is demonstrated that the resulting iterative algorithm can mitigate the high-frequency information loss caused by data incompleteness and produce images that have better preserved high spatial frequency content than those produced by use of a conventional penalized least squares (PLS) estimator.
International Nuclear Information System (INIS)
Yamada, Yoshifumi; Liu, Na; Ito, Satoshi
2006-01-01
The signal in the Fresnel transform technique corresponds to a blurred one of the spin density image. Because the amplitudes of adjacent sampled signals have a high interrelation, the signal amplitude at a point between sampled points can be estimated with a high degree of accuracy even if the sampling is so coarse as to generate aliasing in the reconstructed images. In this report, we describe a new aliasless image reconstruction technique in the phase scrambling Fourier transform (PSFT) imaging technique in which the PSFT signals are converted to Fresnel transform signals by multiplying them by a quadratic phase term and are then interpolated using polynomial expressions to generate fully encoded signals. Numerical simulation using MR images showed that almost completely aliasless images are reconstructed by this technique. Experiments using ultra-low-field PSFT MRI were conducted, and aliasless images were reconstructed from coarsely sampled PSFT signals. (author)
International Nuclear Information System (INIS)
Kawamura, Hirotsune; Iseki, Hiroshi; Umezawa, Yoshihiro
1991-01-01
A new simulation and navigation system utilizing three-dimensional CT images has been developed for image-guided stereotactic surgery. Preoperative CT images are not always useful in predicting the intraoperative location of lesions, for cerebral lesions are easily displaced or distorted by gravity, brain retraction, and/or CSF aspiration during operative procedure. This new system, however, has the advantage that the intraoperative locations of intracranial lesions or the anatomical structures of the brain can be precisely confirmed during stereotactic surgery. Serial CT images were obtained from a patient whose head had been fixed to the ISEKI CT-guided stereotactic frame. The data of serial CT images were saved on a floppy disc and then transferred to the work station (IRIS) using the off line. In order to find the best approach angle for ultrasound-guided stereotactic surgery, three-dimenstional CT images were reconstructed using the work station. The site of the craniotomy or the angle of the trajectory of the ultrasound probe was measured preoperatively based on the three-dimensional CT images. Then, in the operating room, the patient's head was fixed to the ISEKI frame with the subframe at the same position as before according to the measurement of the CT images. In a case of cystic glioma, the predicable ultrasonograms from three-dimensional reconstructive CT images were ascertained to correspond well to the actual ultrasound images during ultrasound-guided stereotactic surgery. Therefore, the new simulation and navigation system can be judged to be a powerful operative supporting modality for correcting the locations of cerebral lesions; it allows one to perform stereotactic surgery more accurately and less invasively. (author)
The research of Digital Holographic Object Wave Field Reconstruction in Image and Object Space
Institute of Scientific and Technical Information of China (English)
LI Jun-Chang; PENG Zu-Jie; FU Yun-Chang
2011-01-01
@@ For conveniently detecting objects of different sizes using digital holography, usual measurements employ the object wave transformed by an optical system with different magnifications to fit charge coupled devices (CCDs), then the object field reconstruction involves the diffraction calculation of the optic wave passing through the optical system.We propose two methods to reconstruct the object field.The one is that, when the object is imaging in an image space in which we reconstruct the image of the object field, the object field can be expressed according to the object-image relationship.The other is that, when the object field reaching CCD is imaged in an object space in which we reconstruct the object field, the optical system is described by introducing matrix optics in this paper.The reconstruction formulae which easily use classic diffraction integral are derived.Finally, experimental verifications are also accomplished.%For conveniently detecting objects of different sizes using digital holography, usual measurements employ the object wave transformed by an optical system with different magnifications to fit charge coupled devices (CCDs), then the object Reid reconstruction involves the diffraction calculation of the optic wave passing through the optical system. We propose two methods to reconstruct the object field. The one is that, when the object is imaging in an image space in which we reconstruct the image of the object field, the object field can be expressed according to the object-image relationship. The other is that, when the object field reaching CCD is imaged in an object space in which we reconstruct the object field, the optical system is described by introducing matrix optics in this paper. The reconstruction formulae which easily use classic diffraction integral are derived. Finally, experimental verifications are also accomplished.
Choice of reconstructed tissue properties affects interpretation of lung EIT images.
Grychtol, Bartłomiej; Adler, Andy
2014-06-01
Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization.
Choice of reconstructed tissue properties affects interpretation of lung EIT images
International Nuclear Information System (INIS)
Grychtol, Bartłomiej; Adler, Andy
2014-01-01
Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization. (paper)
Suzuki, Shigeru; Machida, Haruhiko; Tanaka, Isao; Ueno, Eiko
2013-03-01
The purpose of this study was to evaluate the performance of model-based iterative reconstruction (MBIR) in measurement of the inner diameter of models of blood vessels and compare performance between MBIR and a standard filtered back projection (FBP) algorithm. Vascular models with wall thicknesses of 0.5, 1.0, and 1.5 mm were scanned with a 64-MDCT unit and densities of contrast material yielding 275, 396, and 542 HU. Images were reconstructed images by MBIR and FBP, and the mean diameter of each model vessel was measured by software automation. Twenty separate measurements were repeated for each vessel, and variance among the repeated measures was analyzed for determination of measurement error. For all nine model vessels, CT attenuation profiles were compared along a line passing through the luminal center on axial images reconstructed with FBP and MBIR, and the 10-90% edge rise distances at the boundary between the vascular wall and the lumen were evaluated. For images reconstructed with FBP, measurement errors were smallest for models with 1.5-mm wall thickness, except those filled with 275-HU contrast material, and errors grew as the density of the contrast material decreased. Measurement errors with MBIR were comparable to or less than those with FBP. In CT attenuation profiles of images reconstructed with MBIR, the 10-90% edge rise distances at the boundary between the lumen and vascular wall were relatively short for each vascular model compared with those of the profile curves of FBP images. MBIR is better than standard FBP for reducing reconstruction blur and improving the accuracy of diameter measurement at CT angiography.
Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification
Zhu, Xiaofeng
2015-05-28
This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple visual features, the MMKR first maps them into a high-dimensional space, e.g., a reproducing kernel Hilbert space (RKHS), where test images are then linearly reconstructed by some representative training images, rather than all of them. Furthermore a classification rule is proposed to classify test images. Experimental results on real datasets show the effectiveness of the proposed MMKR while comparing to state-of-the-art algorithms.
Electro-optical system for the high speed reconstruction of computed tomography images
International Nuclear Information System (INIS)
Tresp, V.
1989-01-01
An electro-optical system for the high-speed reconstruction of computed tomography (CT) images has been built and studied. The system is capable of reconstructing high-contrast and high-resolution images at video rate (30 images per second), which is more than two orders of magnitude faster than the reconstruction rate achieved by special purpose digital computers used in commercial CT systems. The filtered back-projection algorithm which was implemented in the reconstruction system requires the filtering of all projections with a prescribed filter function. A space-integrating acousto-optical convolver, a surface acoustic wave filter and a digital finite-impulse response filter were used for this purpose and their performances were compared. The second part of the reconstruction, the back projection of the filtered projections, is computationally very expensive. An optical back projector has been built which maps the filtered projections onto the two-dimensional image space using an anamorphic lens system and a prism image rotator. The reconstructed image is viewed by a video camera, routed through a real-time image-enhancement system, and displayed on a TV monitor. The system reconstructs parallel-beam projection data, and in a modified version, is also capable of reconstructing fan-beam projection data. This extension is important since the latter are the kind of projection data actually acquired in high-speed X-ray CT scanners. The reconstruction system was tested by reconstructing precomputed projection data of phantom images. These were stored in a special purpose projection memory and transmitted to the reconstruction system as an electronic signal. In this way, a projection measurement system that acquires projections sequentially was simulated
SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography
International Nuclear Information System (INIS)
Zhang, J; Ge, G; Winkler, M; Cong, W; Wang, G
2014-01-01
Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose
Model-Based Photoacoustic Image Reconstruction using Compressed Sensing and Smoothed L0 Norm
Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi
2018-01-01
Photoacoustic imaging (PAI) is a novel medical imaging modality that uses the advantages of the spatial resolution of ultrasound imaging and the high contrast of pure optical imaging. Analytical algorithms are usually employed to reconstruct the photoacoustic (PA) images as a result of their simple implementation. However, they provide a low accurate image. Model-based (MB) algorithms are used to improve the image quality and accuracy while a large number of transducers and data acquisition a...
Liu, Yang; Li, Feng; Xin, Lei; Fu, Jie; Huang, Puming
2017-10-01
Large amount of data is one of the most obvious features in satellite based remote sensing systems, which is also a burden for data processing and transmission. The theory of compressive sensing(CS) has been proposed for almost a decade, and massive experiments show that CS has favorable performance in data compression and recovery, so we apply CS theory to remote sensing images acquisition. In CS, the construction of classical sensing matrix for all sparse signals has to satisfy the Restricted Isometry Property (RIP) strictly, which limits applying CS in practical in image compression. While for remote sensing images, we know some inherent characteristics such as non-negative, smoothness and etc.. Therefore, the goal of this paper is to present a novel measurement matrix that breaks RIP. The new sensing matrix consists of two parts: the standard Nyquist sampling matrix for thumbnails and the conventional CS sampling matrix. Since most of sun-synchronous based satellites fly around the earth 90 minutes and the revisit cycle is also short, lots of previously captured remote sensing images of the same place are available in advance. This drives us to reconstruct remote sensing images through a deep learning approach with those measurements from the new framework. Therefore, we propose a novel deep convolutional neural network (CNN) architecture which takes in undersampsing measurements as input and outputs an intermediate reconstruction image. It is well known that the training procedure to the network costs long time, luckily, the training step can be done only once, which makes the approach attractive for a host of sparse recovery problems.
Directory of Open Access Journals (Sweden)
Christian Schou Oxvig
2014-10-01
Full Text Available Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also provides researchers in compressed sensing with a selection of algorithms for reconstructing undersampled general images, and offers a consistent and rigorous way to efficiently evaluate the researchers own developed reconstruction algorithms in terms of phase transitions. The package also serves as a convenient platform for researchers in compressed sensing aiming at obtaining a high degree of reproducibility of their research.
International Nuclear Information System (INIS)
Choi, Joonsung; Kim, Dongchan; Oh, Changhyun; Han, Yeji; Park, HyunWook
2013-01-01
In MRI (magnetic resonance imaging), signal sampling along a radial k-space trajectory is preferred in certain applications due to its distinct advantages such as robustness to motion, and the radial sampling can be beneficial for reconstruction algorithms such as parallel MRI (pMRI) due to the incoherency. For radial MRI, the image is usually reconstructed from projection data using analytic methods such as filtered back-projection or Fourier reconstruction after gridding. However, the quality of the reconstructed image from these analytic methods can be degraded when the number of acquired projection views is insufficient. In this paper, we propose a novel reconstruction method based on the expectation maximization (EM) method, where the EM algorithm is remodeled for MRI so that complex images can be reconstructed. Then, to optimize the proposed method for radial pMRI, a reconstruction method that uses coil sensitivity information of multichannel RF coils is formulated. Experiment results from synthetic and in vivo data show that the proposed method introduces better reconstructed images than the analytic methods, even from highly subsampled data, and provides monotonic convergence properties compared to the conjugate gradient based reconstruction method. (paper)
A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT
International Nuclear Information System (INIS)
Cho, Seungryong; Xia, Dan; Pellizzari, Charles A.; Pan Xiaochuan
2010-01-01
Purpose: Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation. Methods: The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack-Noo-formula-based filteredbackprojection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step. Results: The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts. Conclusions: They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories.
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.
Recent improvements in Hurricane Imaging Radiometer’s brightness temperature image reconstruction
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Sayak K. Biswas
Full Text Available NASA MSFCs airborne Hurricane Imaging Radiometer (HIRAD uses interferometric aperture synthesis to produce high resolution wide swath images of scene brightness temperature (Tb distribution at four discrete C-band microwave frequencies (4.0, 5.0, 6.0 and 6.6 GHz. Images of ocean surface wind speed under heavy precipitation such as in tropical cyclones, is inferred from these measurements. The baseline HIRAD Tb reconstruction algorithm had produced prominent along-track streaks in the Tb images. Particularly the 4.0 GHz channel had been so dominated by the streaks as to be unusable.The loss of a frequency channel had compromised the final wind speed retrievals. During 2016, the HIRAD team made substantial progress in developing a quality controlled signal processing technique for the HIRAD data collected in 2015’s Tropical Cyclone Intensity (TCI experiment and reduced the effect of streaks in all channels including 4.0 GHz. 2000 MSC: 41A05, 41A10, 65D05, 65D17, Keywords: Microwave radiometry, Aperture synthesis, Image reconstruction, Hurricane winds
PIRPLE: a penalized-likelihood framework for incorporation of prior images in CT reconstruction
International Nuclear Information System (INIS)
Stayman, J Webster; Dang, Hao; Ding, Yifu; Siewerdsen, Jeffrey H
2013-01-01
Over the course of diagnosis and treatment, it is common for a number of imaging studies to be acquired. Such imaging sequences can provide substantial patient-specific prior knowledge about the anatomy that can be incorporated into a prior-image-based tomographic reconstruction for improved image quality and better dose utilization. We present a general methodology using a model-based reconstruction approach including formulations of the measurement noise that also integrates prior images. This penalized-likelihood technique adopts a sparsity enforcing penalty that incorporates prior information yet allows for change between the current reconstruction and the prior image. Moreover, since prior images are generally not registered with the current image volume, we present a modified model-based approach that seeks a joint registration of the prior image in addition to the reconstruction of projection data. We demonstrate that the combined prior-image- and model-based technique outperforms methods that ignore the prior data or lack a noise model. Moreover, we demonstrate the importance of registration for prior-image-based reconstruction methods and show that the prior-image-registered penalized-likelihood estimation (PIRPLE) approach can maintain a high level of image quality in the presence of noisy and undersampled projection data. (paper)
International Nuclear Information System (INIS)
Song, Xizi; Xu, Yanbin; Dong, Feng
2017-01-01
Electrical resistance tomography (ERT) is a promising measurement technique with important industrial and clinical applications. However, with limited effective measurements, it suffers from poor spatial resolution due to the ill-posedness of the inverse problem. Recently, there has been an increasing research interest in hybrid imaging techniques, utilizing couplings of physical modalities, because these techniques obtain much more effective measurement information and promise high resolution. Ultrasound modulated electrical impedance tomography (UMEIT) is one of the newly developed hybrid imaging techniques, which combines electric and acoustic modalities. A linearized image reconstruction method based on power density is proposed for UMEIT. The interior data, power density distribution, is adopted to reconstruct the conductivity distribution with the proposed image reconstruction method. At the same time, relating the power density change to the change in conductivity, the Jacobian matrix is employed to make the nonlinear problem into a linear one. The analytic formulation of this Jacobian matrix is derived and its effectiveness is also verified. In addition, different excitation patterns are tested and analyzed, and opposite excitation provides the best performance with the proposed method. Also, multiple power density distributions are combined to implement image reconstruction. Finally, image reconstruction is implemented with the linear back-projection (LBP) algorithm. Compared with ERT, with the proposed image reconstruction method, UMEIT can produce reconstructed images with higher quality and better quantitative evaluation results. (paper)
International Nuclear Information System (INIS)
Doyley, Marvin M; Srinivasan, Seshadri; Dimidenko, Eugene; Soni, Nirmal; Ophir, Jonathan
2006-01-01
Model-based elastography is fraught with problems owing to the ill-posed nature of the inverse elasticity problem. To overcome this limitation, we have recently developed a novel inversion scheme that incorporates a priori information concerning the mechanical properties of the underlying tissue structures, and the variance incurred during displacement estimation in the modulus image reconstruction process. The information was procured by employing standard strain imaging methodology, and introduced in the reconstruction process through the generalized Tikhonov approach. In this paper, we report the results of experiments conducted on gelatin phantoms to evaluate the performance of modulus elastograms computed with the generalized Tikhonov (GTK) estimation criterion relative to those computed by employing the un-weighted least-squares estimation criterion, the weighted least-squares estimation criterion and the standard Tikhonov method (i.e., the generalized Tikhonov method with no modulus prior). The results indicate that modulus elastograms computed with the generalized Tikhonov approach had superior elastographic contrast discrimination and contrast recovery. In addition, image reconstruction was more resilient to structural decorrelation noise when additional constraints were imposed on the reconstruction process through the GTK method
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Chen Deyun
2013-01-01
Full Text Available According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm.
Rybicki, F J; Hrovat, M I; Patz, S
2000-09-01
We have proposed a two-dimensional PERiodic-Linear (PERL) magnetic encoding field geometry B(x,y) = g(y)y cos(q(x)x) and a magnetic resonance imaging pulse sequence which incorporates two fields to image a two-dimensional spin density: a standard linear gradient in the x dimension, and the PERL field. Because of its periodicity, the PERL field produces a signal where the phase of the two dimensions is functionally different. The x dimension is encoded linearly, but the y dimension appears as the argument of a sinusoidal phase term. Thus, the time-domain signal and image spin density are not related by a two-dimensional Fourier transform. They are related by a one-dimensional Fourier transform in the x dimension and a new Bessel function integral transform (the PERL transform) in the y dimension. The inverse of the PERL transform provides a reconstruction algorithm for the y dimension of the spin density from the signal space. To date, the inverse transform has been computed numerically by a Bessel function expansion over its basis functions. This numerical solution used a finite sum to approximate an infinite summation and thus introduced a truncation error. This work analytically determines the basis functions for the PERL transform and incorporates them into the reconstruction algorithm. The improved algorithm is demonstrated by (1) direct comparison between the numerically and analytically computed basis functions, and (2) reconstruction of a known spin density. The new solution for the basis functions also lends proof of the system function for the PERL transform under specific conditions.
Robust framework for PET image reconstruction incorporating system and measurement uncertainties.
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Huafeng Liu
Full Text Available In Positron Emission Tomography (PET, an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts.
Accurate reconstruction of hyperspectral images from compressive sensing measurements
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.
Imaging features of anterior cruciate ligament reconstruction graft insufficiency
International Nuclear Information System (INIS)
Shang Yao; Zhang Yue; Tian Chunyan; Zheng Zhuozhao
2011-01-01
Objective: To investigate the imaging features of anterior cruciate ligament (ACL) graft insufficiency. Methods: X-Ray and MR imaging examinations in 24 consecutive patients who had ACL reconstructive graft insufficiency were retrospectively evaluated for tunnel position, osteoarthrosis and its related complications. Follow-up arthroscopy showed 16 graft tears and 8 graft laxities. Fisher exact test was used to compare tunnel malpositions, the proportion of graft tear on MRI and osteoarthrosis between graft tear group and graft laxity group. Results: Two malpositions of tibial tunnel and 3 malpositions of femoral tunnel were seen in graft tear group. Three-malpositions of tibial tunnel and 4 malpositions of femoral tunnel were seen in graft laxity group. The proportion of tibial or femoral malposition showed no significant difference between the two groups (P=0.289, P=0.167). In graft tear group, 15 complete graft tears were diagnosed correctly, 1 partial tear was misdiagnosed as normal on MRI. In graft laxity group, 4 grafts were diagnosed as normal and 4 were considered as graft tear on MRI. A significant difference was seen between the two groups (P=0.028) in the proportion of graft tear diagnosed on MRI. Fourteen osteoarthrosis were seen in graft tear group and 5 in graft laxity group. No significant difference was seen between the two groups (P= 0.289) in the proportion of osteoarthrosis. Conclusion: The proportions of tunnel malposition and osteoarthrosis showed no significant difference between the graft tear group and graft Laxity group. Most graft tears can be diagnosed accurately on MRI, but some cases of graft laxity may be misdiagnosed for graft tear. (authors)
Positron transaxial emission tomograph with computerized image reconstruction
International Nuclear Information System (INIS)
Jatteau, Michel.
1981-01-01
This invention concerns a positron transaxial emission tomography apparatus with computerized image reconstruction, like those used in nuclear medicine for studying the metabolism of organs, in physiological examinations and as a diagnosis aid. The operation is based on the principle of the detection of photons emitted when the positrons are annihilated by impact with an electron. The appliance is mainly composed of: (a) - a set of gamma ray detectors distributed on a polygonal arrangement around the body area to be examined, (b) - circuits for amplifying the signals delivered by the gamma ray detectors, (c) - computers essentially comprising energy integration and discrimination circuits and provided at the output of the detectors for calculating and delivering, as from the amplified signals, information on the position and energy relative to each occurrence constituted by the detections of photons, (d) - time coincidence circuits for selecting by emission of detector validation signals, only those occurrences, among the ensemble of those detected, which effectively result from the annihilation of positrons inside the area examined, (e) - a data processing system [fr
International Nuclear Information System (INIS)
Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu
2015-01-01
Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy. (paper)