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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2010-04-15

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

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

International Nuclear Information System (INIS)

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

1996-01-01

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

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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

Science.gov (United States)

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

2018-05-01

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

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

Science.gov (United States)

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

2014-07-01

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

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

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

International Nuclear Information System (INIS)

Quan, E; Lalush, D S

2009-01-01

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

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

Science.gov (United States)

Lohvithee, Manasavee; Biguri, Ander; Soleimani, Manuchehr

2017-12-01

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

A trial to reduce cardiac motion artifact on HR-CT images of the lung with the use of subsecond scan and special cine reconstruction algorithm

Energy Technology Data Exchange (ETDEWEB)

Sakai, Fumikazu; Tsuuchi, Yasuhiko; Suzuki, Keiko; Ueno, Keiko; Yamada, Takayuki; Okawa, Tomohiko [Tokyo Women`s Medical Coll. (Japan); Yun, Shen; Horiuchi, Tetsuya; Kimura, Fumiko

1998-05-01

We describe our trial to reduce cardiac motion artifacts on HR-CT images caused by cardiac pulsation by combining use of subsecond CT (scan time 0.8 s) and a special cine reconstruction algorithm (cine reconstruction algorithm with 180-degree helical interpolation). Eleven to 51 HR-CT images were reconstructed with the special cine reconstruction algorithm at the pitch of 0.1 (0.08 s) from the data obtained by two to six contigious rotation scans at the same level. Images with the fewest cardiac motion artifacts were selected for evaluation. These images were compared with those reconstructed with a conventional cine reconstruction algorithm and step-by-step scan. In spite of its increased radiation exposure, technical complexity and slight degradation of spatial resolution, our method was useful in reducing cardiac motion artifacts on HR-CT images in regions adjacent to the heart. (author)

Enhanced temporal resolution at cardiac CT with a novel CT image reconstruction algorithm: Initial patient experience

Energy Technology Data Exchange (ETDEWEB)

Apfaltrer, Paul, E-mail: paul.apfaltrer@medma.uni-heidelberg.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Schoendube, Harald, E-mail: harald.schoendube@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Schoepf, U. Joseph, E-mail: schoepf@musc.edu [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Allmendinger, Thomas, E-mail: thomas.allmendinger@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Tricarico, Francesco, E-mail: francescotricarico82@gmail.com [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Department of Bioimaging and Radiological Sciences, Catholic University of the Sacred Heart, “A. Gemelli” Hospital, Largo A. Gemelli 8, Rome (Italy); Schindler, Andreas, E-mail: andreas.schindler@campus.lmu.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Vogt, Sebastian, E-mail: sebastian.vogt@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Sunnegårdh, Johan, E-mail: johan.sunnegardh@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); and others

2013-02-15

Objective: To evaluate the effect of a temporal resolution improvement method (TRIM) for cardiac CT on diagnostic image quality for coronary artery assessment. Materials and methods: The TRIM-algorithm employs an iterative approach to reconstruct images from less than 180° of projections and uses a histogram constraint to prevent the occurrence of limited-angle artifacts. This algorithm was applied in 11 obese patients (7 men, 67.2 ± 9.8 years) who had undergone second generation dual-source cardiac CT with 120 kV, 175–426 mAs, and 500 ms gantry rotation. All data were reconstructed with a temporal resolution of 250 ms using traditional filtered-back projection (FBP) and of 200 ms using the TRIM-algorithm. Contrast attenuation and contrast-to-noise-ratio (CNR) were measured in the ascending aorta. The presence and severity of coronary motion artifacts was rated on a 4-point Likert scale. Results: All scans were considered of diagnostic quality. Mean BMI was 36 ± 3.6 kg/m{sup 2}. Average heart rate was 60 ± 9 bpm. Mean effective dose was 13.5 ± 4.6 mSv. When comparing FBP- and TRIM reconstructed series, the attenuation within the ascending aorta (392 ± 70.7 vs. 396.8 ± 70.1 HU, p > 0.05) and CNR (13.2 ± 3.2 vs. 11.7 ± 3.1, p > 0.05) were not significantly different. A total of 110 coronary segments were evaluated. All studies were deemed diagnostic; however, there was a significant (p < 0.05) difference in the severity score distribution of coronary motion artifacts between FBP (median = 2.5) and TRIM (median = 2.0) reconstructions. Conclusion: The algorithm evaluated here delivers diagnostic imaging quality of the coronary arteries despite 500 ms gantry rotation. Possible applications include improvement of cardiac imaging on slower gantry rotation systems or mitigation of the trade-off between temporal resolution and CNR in obese patients.

Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

Science.gov (United States)

Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

2015-01-01

For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. Methods We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 seconds. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.04375 mAs, were investigated. Both the analytical FDK algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. Results With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels

Low dose reconstruction algorithm for differential phase contrast imaging.

Science.gov (United States)

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

2011-01-01

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

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)

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-09-15

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

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

International Nuclear Information System (INIS)

Solomon, Justin; Samei, Ehsan

2014-01-01

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

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

Science.gov (United States)

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

2016-12-01

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

Versatility of the CFR algorithm for limited angle reconstruction

International Nuclear Information System (INIS)

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

1990-01-01

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

Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

Science.gov (United States)

Li, Liang; Wang, Bigong; Wang, Ge

2016-01-01

In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.

Median prior constrained TV algorithm for sparse view low-dose CT reconstruction.

Science.gov (United States)

Liu, Yi; Shangguan, Hong; Zhang, Quan; Zhu, Hongqing; Shu, Huazhong; Gui, Zhiguo

2015-05-01

It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current, has been demonstrated to be able to result in significant radiation dose reduction while maintain image quality, noticeable patchy artifacts still exist in reconstructed images. In this study, to address the problem of patchy artifacts, we proposed a median prior constrained TV regularization to retain the image quality by introducing an auxiliary vector m in register with the object. Specifically, the approximate action of m is to draw, in each iteration, an object voxel toward its own local median, aiming to improve low-dose image quality with sparse-view projection measurements. Subsequently, an alternating optimization algorithm is adopted to optimize the associative objective function. We refer to the median prior constrained TV regularization as "TV_MP" for simplicity. Experimental results on digital phantoms and clinical phantom demonstrated that the proposed TV_MP with appropriate control parameters can not only ensure a higher signal to noise ratio (SNR) of the reconstructed image, but also its resolution compared with the original TV method. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-04-15

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

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

International Nuclear Information System (INIS)

Shen Le; Xing Yuxiang

2010-01-01

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

Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm

Science.gov (United States)

Wang, Yuzhu; Rahman, Sheik S.; Arns, Christoph H.

2018-03-01

X-ray computed tomography (μ-CT) is considered to be the most effective way to obtain the inner structure of rock sample without destructions. However, its limited resolution hampers its ability to probe sub-micro structures which is critical for flow transportation of rock sample. In this study, we propose an innovative methodology to improve the resolution of μ-CT image using neighbour embedding algorithm where low frequency information is provided by μ-CT image itself while high frequency information is supplemented by high resolution scanning electron microscopy (SEM) image. In order to obtain prior for reconstruction, a large number of image patch pairs contain high- and low- image patches are extracted from the Gaussian image pyramid generated by SEM image. These image patch pairs contain abundant information about tomographic evolution of local porous structures under different resolution spaces. Relying on the assumption of self-similarity of porous structure, this prior information can be used to supervise the reconstruction of high resolution μ-CT image effectively. The experimental results show that the proposed method is able to achieve the state-of-the-art performance.

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

Filtered backprojection proton CT reconstruction along most likely paths

Energy Technology Data Exchange (ETDEWEB)

Rit, Simon; Dedes, George; Freud, Nicolas; Sarrut, David; Letang, Jean Michel [Universite de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Universite Lyon 1, Centre Leon Berard, 69008 Lyon (France)

2013-03-15

Purpose: Proton CT (pCT) has the potential to accurately measure the electron density map of tissues at low doses but the spatial resolution is prohibitive if the curved paths of protons in matter is not accounted for. The authors propose to account for an estimate of the most likely path of protons in a filtered backprojection (FBP) reconstruction algorithm. Methods: The energy loss of protons is first binned in several proton radiographs at different distances to the proton source to exploit the depth-dependency of the estimate of the most likely path. This process is named the distance-driven binning. A voxel-specific backprojection is then used to select the adequate radiograph in the distance-driven binning in order to propagate in the pCT image the best achievable spatial resolution in proton radiographs. The improvement in spatial resolution is demonstrated using Monte Carlo simulations of resolution phantoms. Results: The spatial resolution in the distance-driven binning depended on the distance of the objects from the source and was optimal in the binned radiograph corresponding to that distance. The spatial resolution in the reconstructed pCT images decreased with the depth in the scanned object but it was always better than previous FBP algorithms assuming straight line paths. In a water cylinder with 20 cm diameter, the observed range of spatial resolutions was 0.7 - 1.6 mm compared to 1.0 - 2.4 mm at best with a straight line path assumption. The improvement was strongly enhanced in shorter 200 Degree-Sign scans. Conclusions: Improved spatial resolution was obtained in pCT images with filtered backprojection reconstruction using most likely path estimates of protons. The improvement in spatial resolution combined with the practicality of FBP algorithms compared to iterative reconstruction algorithms makes this new algorithm a candidate of choice for clinical pCT.

The reconstruction algorithm used for ["6"8Ga]PSMA-HBED-CC PET/CT reconstruction significantly influences the number of detected lymph node metastases and coeliac ganglia

International Nuclear Information System (INIS)

Krohn, Thomas; Birmes, Anita; Winz, Oliver H.; Drude, Natascha I.; Mottaghy, Felix M.; Behrendt, Florian F.; Verburg, Frederik A.

2017-01-01

To investigate whether the numbers of lymph node metastases and coeliac ganglia delineated on ["6"8Ga]PSMA-HBED-CC PET/CT scans differ among datasets generated using different reconstruction algorithms. Data were constructed using the BLOB-OS-TF, BLOB-OS and 3D-RAMLA algorithms. All reconstructions were assessed by two nuclear medicine physicians for the number of pelvic/paraaortal lymph node metastases as well the number of coeliac ganglia. Standardized uptake values (SUV) were also calculated in different regions. At least one ["6"8Ga]PSMA-HBED-CC PET/CT-positive pelvic or paraaortal lymph node metastasis was found in 49 and 35 patients using the BLOB-OS-TF algorithm, in 42 and 33 patients using the BLOB-OS algorithm, and in 41 and 31 patients using the 3D-RAMLA algorithm, respectively, and a positive ganglion was found in 92, 59 and 24 of 100 patients using the three algorithms, respectively. Quantitatively, the SUVmean and SUVmax were significantly higher with the BLOB-OS algorithm than with either the BLOB-OS-TF or the 3D-RAMLA algorithm in all measured regions (p < 0.001 for all comparisons). The differences between the SUVs with the BLOB-OS-TF- and 3D-RAMLA algorithms were not significant in the aorta (SUVmean, p = 0.93; SUVmax, p = 0.97) but were significant in all other regions (p < 0.001 in all cases). The SUVmean ganglion/gluteus ratio was significantly higher with the BLOB-OS-TF algorithm than with either the BLOB-OS or the 3D-RAMLA algorithm and was significantly higher with the BLOB-OS than with the 3D-RAMLA algorithm (p < 0.001 in all cases). The results of ["6"8Ga]PSMA-HBED-CC PET/CT are affected by the reconstruction algorithm used. The highest number of lesions and physiological structures will be visualized using a modern algorithm employing time-of-flight information. (orig.)

The reconstruction algorithm used for [{sup 68}Ga]PSMA-HBED-CC PET/CT reconstruction significantly influences the number of detected lymph node metastases and coeliac ganglia

Energy Technology Data Exchange (ETDEWEB)

Krohn, Thomas [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Ulm University, Department of Nuclear Medicine, Ulm (Germany); Birmes, Anita; Winz, Oliver H.; Drude, Natascha I. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Mottaghy, Felix M. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Maastricht UMC+, Department of Nuclear Medicine, Maastricht (Netherlands); Behrendt, Florian F. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); Radiology Institute ' ' Aachen Land' ' , Wuerselen (Germany); Verburg, Frederik A. [RWTH University Hospital Aachen, Department of Nuclear Medicine, Aachen (Germany); University Hospital Giessen and Marburg, Department of Nuclear Medicine, Marburg (Germany)

2017-04-15

To investigate whether the numbers of lymph node metastases and coeliac ganglia delineated on [{sup 68}Ga]PSMA-HBED-CC PET/CT scans differ among datasets generated using different reconstruction algorithms. Data were constructed using the BLOB-OS-TF, BLOB-OS and 3D-RAMLA algorithms. All reconstructions were assessed by two nuclear medicine physicians for the number of pelvic/paraaortal lymph node metastases as well the number of coeliac ganglia. Standardized uptake values (SUV) were also calculated in different regions. At least one [{sup 68}Ga]PSMA-HBED-CC PET/CT-positive pelvic or paraaortal lymph node metastasis was found in 49 and 35 patients using the BLOB-OS-TF algorithm, in 42 and 33 patients using the BLOB-OS algorithm, and in 41 and 31 patients using the 3D-RAMLA algorithm, respectively, and a positive ganglion was found in 92, 59 and 24 of 100 patients using the three algorithms, respectively. Quantitatively, the SUVmean and SUVmax were significantly higher with the BLOB-OS algorithm than with either the BLOB-OS-TF or the 3D-RAMLA algorithm in all measured regions (p < 0.001 for all comparisons). The differences between the SUVs with the BLOB-OS-TF- and 3D-RAMLA algorithms were not significant in the aorta (SUVmean, p = 0.93; SUVmax, p = 0.97) but were significant in all other regions (p < 0.001 in all cases). The SUVmean ganglion/gluteus ratio was significantly higher with the BLOB-OS-TF algorithm than with either the BLOB-OS or the 3D-RAMLA algorithm and was significantly higher with the BLOB-OS than with the 3D-RAMLA algorithm (p < 0.001 in all cases). The results of [{sup 68}Ga]PSMA-HBED-CC PET/CT are affected by the reconstruction algorithm used. The highest number of lesions and physiological structures will be visualized using a modern algorithm employing time-of-flight information. (orig.)

Effect of reconstruction algorithm on image quality and identification of ground-glass opacities and partly solid nodules on low-dose thin-section CT: Experimental study using chest phantom

International Nuclear Information System (INIS)

Koyama, Hisanobu; Ohno, Yoshiharu; Kono, Atsushi A.; Kusaka, Akiko; Konishi, Minoru; Yoshii, Masaru; Sugimura, Kazuro

2010-01-01

Purpose: The purpose of this study was to assess the influence of reconstruction algorithm on identification and image quality of ground-glass opacities (GGOs) and partly solid nodules on low-dose thin-section CT. Materials and methods: A chest CT phantom including simulated GGOs and partly solid nodules was scanned with five different tube currents and reconstructed by using standard (A) and newly developed (B) high-resolution reconstruction algorithms, followed by visually assessment of identification and image quality of GGOs and partly solid nodules by two chest radiologists. Inter-observer agreement, ROC analysis and ANOVA were performed to compare identification and image quality of each data set with those of the standard reference. The standard reference used 120 mA s in conjunction with reconstruction algorithm A. Results: Kappa values (κ) of overall identification and image qualities were substantial or almost perfect (0.60 < κ). Assessment of identification showed that area under the curve of 25 mA reconstructed with reconstruction algorithm A was significantly lower than that of standard reference (p < 0.05), while assessment of image quality indicated that 50 mA s reconstructed with reconstruction algorithm A and 25 mA s reconstructed with both reconstruction algorithms were significantly lower than standard reference (p < 0.05). Conclusion: Reconstruction algorithm may be an important factor for identification and image quality of ground-glass opacities and partly solid nodules on low-dose CT examination.

First-order convex feasibility algorithms for x-ray CT

DEFF Research Database (Denmark)

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

2013-01-01

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times...... problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited...

Metal artifact reduction image reconstruction algorithm for CT of implanted metal orthopedic devices: a work in progress

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.)

Iterative CT reconstruction via minimizing adaptively reweighted total variation.

Science.gov (United States)

Zhu, Lei; Niu, Tianye; Petrongolo, Michael

2014-01-01

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

DART: a practical reconstruction algorithm for discrete tomography.

Science.gov (United States)

Batenburg, Kees Joost; Sijbers, Jan

2011-09-01

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

Convergence of SART + OS + TV iterative reconstruction algorithm for optical CT imaging of gel dosimeters

International Nuclear Information System (INIS)

Du, Yi; Yu, Gongyi; Xiang, Xincheng; Wang, Xiangang; De Deene, Yves

2017-01-01

Computational simulations are used to investigate the convergence of a hybrid iterative algorithm for optical CT reconstruction, i.e. the simultaneous algebraic reconstruction technique (SART) integrated with ordered subsets (OS) iteration and total variation (TV) minimization regularization, or SART+OS+TV for short. The influence of parameter selection to reach convergence, spatial dose gradient integrity, MTF and convergent speed are discussed. It’s shown that the results of SART+OS+TV algorithm converge to the true values without significant bias, and MTF and convergent speed are affected by different parameter sets used for iterative calculation. In conclusion, the performance of the SART+OS+TV depends on parameter selection, which also implies that careful parameter tuning work is required and necessary for proper spatial performance and fast convergence. (paper)

Region-of-interest reconstruction for a cone-beam dental CT with a circular trajectory

International Nuclear Information System (INIS)

Hu, Zhanli; Zou, Jing; Gui, Jianbao; Zheng, Hairong; Xia, Dan

2013-01-01

Dental CT is the most appropriate and accurate device for preoperative evaluation of dental implantation. It can demonstrate the quantity of bone in three dimensions (3D), the location of important adjacent anatomic structures and the quality of available bone with minimal geometric distortion. Nevertheless, with the rapid increase of dental CT examinations, we are facing the problem of dose reduction without loss of image quality. In this work, backprojection-filtration (BPF) and Feldkamp–Davis–Kress (FDK) algorithm was applied to reconstruct the 3D full image and region-of-interest (ROI) image from complete and truncated circular cone-beam data respectively by computer-simulation. In addition, the BPF algorithm was evaluated based on the 3D ROI-image reconstruction from real data, which was acquired from our developed circular cone-beam prototype dental CT system. The results demonstrated that the ROI-image quality reconstructed from truncated data using the BPF algorithm was comparable to that reconstructed from complete data. The FDK algorithm, however, created artifacts while reconstructing ROI-image. Thus it can be seen, for circular cone-beam dental CT, reducing scanning angular range of the BPF algorithm used for ROI-image reconstruction are helpful for reducing the radiation dose and scanning time. Finally, an analytical method was developed for estimation of the ROI projection area on the detector before CT scanning, which would help doctors to roughly estimate the total radiation dose before the CT examination. -- Highlights: ► BPF algorithm was applied by using dental CT for the first time. ► A method was developed for estimation of projection region before CT scanning. ► Roughly predict the total radiation dose before CT scans. ► Potential reduce imaging radiation dose, scatter, and scanning time

Dose reduction in pediatric abdominal CT: use of iterative reconstruction techniques across different CT platforms

International Nuclear Information System (INIS)

Khawaja, Ranish Deedar Ali; Singh, Sarabjeet; Otrakji, Alexi; Padole, Atul; Lim, Ruth; Nimkin, Katherine; Westra, Sjirk; Kalra, Mannudeep K.; Gee, Michael S.

2015-01-01

Dose reduction in children undergoing CT scanning is an important priority for the radiology community and public at large. Drawbacks of radiation reduction are increased image noise and artifacts, which can affect image interpretation. Iterative reconstruction techniques have been developed to reduce noise and artifacts from reduced-dose CT examinations, although reconstruction algorithm, magnitude of dose reduction and effects on image quality vary. We review the reconstruction principles, radiation dose potential and effects on image quality of several iterative reconstruction techniques commonly used in clinical settings, including 3-D adaptive iterative dose reduction (AIDR-3D), adaptive statistical iterative reconstruction (ASIR), iDose, sinogram-affirmed iterative reconstruction (SAFIRE) and model-based iterative reconstruction (MBIR). We also discuss clinical applications of iterative reconstruction techniques in pediatric abdominal CT. (orig.)

Dose reduction in pediatric abdominal CT: use of iterative reconstruction techniques across different CT platforms

Energy Technology Data Exchange (ETDEWEB)

Khawaja, Ranish Deedar Ali; Singh, Sarabjeet; Otrakji, Alexi; Padole, Atul; Lim, Ruth; Nimkin, Katherine; Westra, Sjirk; Kalra, Mannudeep K.; Gee, Michael S. [MGH Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA (United States)

2015-07-15

Dose reduction in children undergoing CT scanning is an important priority for the radiology community and public at large. Drawbacks of radiation reduction are increased image noise and artifacts, which can affect image interpretation. Iterative reconstruction techniques have been developed to reduce noise and artifacts from reduced-dose CT examinations, although reconstruction algorithm, magnitude of dose reduction and effects on image quality vary. We review the reconstruction principles, radiation dose potential and effects on image quality of several iterative reconstruction techniques commonly used in clinical settings, including 3-D adaptive iterative dose reduction (AIDR-3D), adaptive statistical iterative reconstruction (ASIR), iDose, sinogram-affirmed iterative reconstruction (SAFIRE) and model-based iterative reconstruction (MBIR). We also discuss clinical applications of iterative reconstruction techniques in pediatric abdominal CT. (orig.)

Fast parallel algorithm for CT image reconstruction.

Science.gov (United States)

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).

Accuracy improvement of CT reconstruction using tree-structured filter bank

International Nuclear Information System (INIS)

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

2009-01-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

A temporal interpolation approach for dynamic reconstruction in perfusion CT

International Nuclear Information System (INIS)

Montes, Pau; Lauritsch, Guenter

2007-01-01

This article presents a dynamic CT reconstruction algorithm for objects with time dependent attenuation coefficient. Projection data acquired over several rotations are interpreted as samples of a continuous signal. Based on this idea, a temporal interpolation approach is proposed which provides the maximum temporal resolution for a given rotational speed of the CT scanner. Interpolation is performed using polynomial splines. The algorithm can be adapted to slow signals, reducing the amount of data acquired and the computational cost. A theoretical analysis of the approximations made by the algorithm is provided. In simulation studies, the temporal interpolation approach is compared with three other dynamic reconstruction algorithms based on linear regression, linear interpolation, and generalized Parker weighting. The presented algorithm exhibits the highest temporal resolution for a given sampling interval. Hence, our approach needs less input data to achieve a certain quality in the reconstruction than the other algorithms discussed or, equivalently, less x-ray exposure and computational complexity. The proposed algorithm additionally allows the possibility of using slow rotating scanners for perfusion imaging purposes

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

Directory of Open Access Journals (Sweden)

Bin Yan

2015-01-01

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

Variability and accuracy of coronary CT angiography including use of iterative reconstruction algorithms for plaque burden assessment as compared with intravascular ultrasound - an ex vivo study

Energy Technology Data Exchange (ETDEWEB)

Stolzmann, Paul [Massachusetts General Hospital and Harvard Medical School, Cardiac MR PET CT Program, Boston, MA (United States); University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland); Schlett, Christopher L.; Maurovich-Horvat, Pal; Scheffel, Hans; Engel, Leif-Christopher; Karolyi, Mihaly; Hoffmann, Udo [Massachusetts General Hospital and Harvard Medical School, Cardiac MR PET CT Program, Boston, MA (United States); Maehara, Akiko; Ma, Shixin; Mintz, Gary S. [Columbia University Medical Center, Cardiovascular Research Foundation, New York, NY (United States)

2012-10-15

To systematically assess inter-technique and inter-/intra-reader variability of coronary CT angiography (CTA) to measure plaque burden compared with intravascular ultrasound (IVUS) and to determine whether iterative reconstruction algorithms affect variability. IVUS and CTA data were acquired from nine human coronary arteries ex vivo. CT images were reconstructed using filtered back projection (FBPR) and iterative reconstruction algorithms: adaptive-statistical (ASIR) and model-based (MBIR). After co-registration of 284 cross-sections between IVUS and CTA, two readers manually delineated the cross-sectional plaque area in all images presented in random order. Average plaque burden by IVUS was 63.7 {+-} 10.7% and correlated significantly with all CTA measurements (r = 0.45-0.52; P < 0.001), while CTA overestimated the burden by 10 {+-} 10%. There were no significant differences among FBPR, ASIR and MBIR (P > 0.05). Increased overestimation was associated with smaller plaques, eccentricity and calcification (P < 0.001). Reproducibility of plaque burden by CTA and IVUS datasets was excellent with a low mean intra-/inter-reader variability of <1/<4% for CTA and <0.5/<1% for IVUS respectively (P < 0.05) with no significant difference between CT reconstruction algorithms (P > 0.05). In ex vivo coronary arteries, plaque burden by coronary CTA had extremely low inter-/intra-reader variability and correlated significantly with IVUS measurements. Accuracy as well as reader reliability were independent of CT image reconstruction algorithm. (orig.)

Improvement of the temporal resolution of cardiac CT reconstruction algorithms using an optimized filtering step

International Nuclear Information System (INIS)

Roux, S.; Desbat, L.; Koenig, A.; Grangeat, P.

2005-01-01

In this paper we study a property of the filtering step of multi-cycle reconstruction algorithm used in the field of cardiac CT. We show that the common filtering step procedure is not optimal in the case of divergent geometry and decrease slightly the temporal resolution. We propose to use the filtering procedure related to the work of Noo at al ( F.Noo, M. Defrise, R. Clakdoyle, and H. Kudo. Image reconstruction from fan-beam projections on less than a short-scan. Phys. Med.Biol., 47:2525-2546, July 2002)and show that this alternative allows to reach the optimal temporal resolution with the same computational effort. (N.C.)

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

International Nuclear Information System (INIS)

Li Jing; Sun Yi; Zhu Peiping

2013-01-01

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

SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

International Nuclear Information System (INIS)

Ali, I; Ahmad, S; Alsbou, N

2015-01-01

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases

SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

Energy Technology Data Exchange (ETDEWEB)

Ali, I; Ahmad, S [University of Oklahoma Health Sciences, Oklahoma City, OK (United States); Alsbou, N [Ohio Northern University, Ada, OH (United States)

2015-06-15

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases

Quantitative tomography simulations and reconstruction algorithms

International Nuclear Information System (INIS)

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

2000-01-01

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

Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure

Energy Technology Data Exchange (ETDEWEB)

Maier, Joscha, E-mail: joscha.maier@dkfz.de [Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg (Germany); Sawall, Stefan; Kachelrieß, Marc [Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany and Institute of Medical Physics, University of Erlangen–Nürnberg, 91052 Erlangen (Germany)

2014-05-15

Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the

Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure

International Nuclear Information System (INIS)

Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc

2014-01-01

Purpose: Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Methods: Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Results: Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the

Assessment of dedicated low-dose cardiac micro-CT reconstruction algorithms using the left ventricular volume of small rodents as a performance measure.

Science.gov (United States)

Maier, Joscha; Sawall, Stefan; Kachelrieß, Marc

2014-05-01

Phase-correlated microcomputed tomography (micro-CT) imaging plays an important role in the assessment of mouse models of cardiovascular diseases and the determination of functional parameters as the left ventricular volume. As the current gold standard, the phase-correlated Feldkamp reconstruction (PCF), shows poor performance in case of low dose scans, more sophisticated reconstruction algorithms have been proposed to enable low-dose imaging. In this study, the authors focus on the McKinnon-Bates (MKB) algorithm, the low dose phase-correlated (LDPC) reconstruction, and the high-dimensional total variation minimization reconstruction (HDTV) and investigate their potential to accurately determine the left ventricular volume at different dose levels from 50 to 500 mGy. The results were verified in phantom studies of a five-dimensional (5D) mathematical mouse phantom. Micro-CT data of eight mice, each administered with an x-ray dose of 500 mGy, were acquired, retrospectively gated for cardiac and respiratory motion and reconstructed using PCF, MKB, LDPC, and HDTV. Dose levels down to 50 mGy were simulated by using only a fraction of the projections. Contrast-to-noise ratio (CNR) was evaluated as a measure of image quality. Left ventricular volume was determined using different segmentation algorithms (Otsu, level sets, region growing). Forward projections of the 5D mouse phantom were performed to simulate a micro-CT scan. The simulated data were processed the same way as the real mouse data sets. Compared to the conventional PCF reconstruction, the MKB, LDPC, and HDTV algorithm yield images of increased quality in terms of CNR. While the MKB reconstruction only provides small improvements, a significant increase of the CNR is observed in LDPC and HDTV reconstructions. The phantom studies demonstrate that left ventricular volumes can be determined accurately at 500 mGy. For lower dose levels which were simulated for real mouse data sets, the HDTV algorithm shows the

Iterative CT reconstruction with correction for known rigid motion

Energy Technology Data Exchange (ETDEWEB)

Nuyts, Johan [Katholieke Univ. Leuven (Belgium). Dept. of Nuclear Medicine; Kim, Jung-Ha; Fulton, Roger [Sydney Univ., NSW (Australia). School of Physics; Westmead Hospital, Sydney (Australia). Medical Physics

2011-07-01

In PET/CT brain imaging, correction for motion may be needed, in particular for children and psychiatric patients. Motion is more likely to occur in the lengthy PET measurement, but also during the short CT acquisition patient motion is possible. Rigid motion of the head can be measured independently from the PET/CT system with optical devices. In this paper, we propose a method and some preliminary simulation results for iterative CT reconstruction with correction for known rigid motion. We implemented an iterative algorithm for fully 3D reconstruction from helical CT scans. The motion of the head is incorporated in the system matrix as a view-dependent motion of the CT-system. The first simulation results indicate that some motion patterns may produce loss of essential data. This loss precludes exact reconstruction and results in artifacts in the reconstruction, even when motion is taken into account. However, by reducing the pitch during acquisition, the same motion pattern no longer caused artifacts in the motion corrected image. (orig.)

CT reconstruction techniques for improved accuracy of lung CT airway measurement

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, A. [Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53705 (United States); Ranallo, F. N. [Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53705 and Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53792 (United States); Judy, P. F. [Brigham and Women’s Hospital, Boston, Massachusetts 02115 (United States); Gierada, D. S. [Department of Radiology, Washington University, St. Louis, Missouri 63110 (United States); Fain, S. B., E-mail: sfain@wisc.edu [Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53705 (United States); Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53792 (United States); Department of Biomedical Engineering,University of Wisconsin School of Engineering, Madison, Wisconsin 53706 (United States)

2014-11-01

Purpose: To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose. Methods: Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12–100 mA s current–time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error. Results: WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD

CT reconstruction techniques for improved accuracy of lung CT airway measurement

International Nuclear Information System (INIS)

Rodriguez, A.; Ranallo, F. N.; Judy, P. F.; Gierada, D. S.; Fain, S. B.

2014-01-01

Purpose: To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose. Methods: Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12–100 mA s current–time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error. Results: WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD

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

DEFF Research Database (Denmark)

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

2012-01-01

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

Multichannel algorithm for fast 3D reconstruction

International Nuclear Information System (INIS)

Rodet, Thomas; Grangeat, Pierre; Desbat, Laurent

2002-01-01

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

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

Iterative Reconstruction Techniques in Abdominopelvic CT: Technical Concepts and Clinical Implementation.

Science.gov (United States)

Patino, Manuel; Fuentes, Jorge M; Singh, Sarabjeet; Hahn, Peter F; Sahani, Dushyant V

2015-07-01

This article discusses the clinical challenge of low-radiation-dose examinations, the commonly used approaches for dose optimization, and their effect on image quality. We emphasize practical aspects of the different iterative reconstruction techniques, along with their benefits, pitfalls, and clinical implementation. The widespread use of CT has raised concerns about potential radiation risks, motivating diverse strategies to reduce the radiation dose associated with CT. CT manufacturers have developed alternative reconstruction algorithms intended to improve image quality on dose-optimized CT studies, mainly through noise and artifact reduction. Iterative reconstruction techniques take unique approaches to noise reduction and provide distinct strength levels or settings.

SU-F-T-441: Dose Calculation Accuracy in CT Images Reconstructed with Artifact Reduction Algorithm

Energy Technology Data Exchange (ETDEWEB)

Ng, C; Chan, S; Lee, F; Ngan, R [Queen Elizabeth Hospital (Hong Kong); Lee, V [University of Hong Kong, Hong Kong, HK (Hong Kong)

2016-06-15

Purpose: Accuracy of radiotherapy dose calculation in patients with surgical implants is complicated by two factors. First is the accuracy of CT number, second is the dose calculation accuracy. We compared measured dose with dose calculated on CT images reconstructed with FBP and an artifact reduction algorithm (OMAR, Philips) for a phantom with high density inserts. Dose calculation were done with Varian AAA and AcurosXB. Methods: A phantom was constructed with solid water in which 2 titanium or stainless steel rods could be inserted. The phantom was scanned with the Philips Brillance Big Bore CT. Image reconstruction was done with FBP and OMAR. Two 6 MV single field photon plans were constructed for each phantom. Radiochromic films were placed at different locations to measure the dose deposited. One plan has normal incidence on the titanium/steel rods. In the second plan, the beam is at almost glancing incidence on the metal rods. Measurements were then compared with dose calculated with AAA and AcurosXB. Results: The use of OMAR images slightly improved the dose calculation accuracy. The agreement between measured and calculated dose was best with AXB and image reconstructed with OMAR. Dose calculated on titanium phantom has better agreement with measurement. Large discrepancies were seen at points directly above and below the high density inserts. Both AAA and AXB underestimated the dose directly above the metal surface, while overestimated the dose below the metal surface. Doses measured downstream of metal were all within 3% of calculated values. Conclusion: When doing treatment planning for patients with metal implants, care must be taken to acquire correct CT images to improve dose calculation accuracy. Moreover, great discrepancies in measured and calculated dose were observed at metal/tissue interface. Care must be taken in estimating the dose in critical structures that come into contact with metals.

Effects of Different Reconstruction Parameters on CT Volumetric Measurement 
of Pulmonary Nodules

Directory of Open Access Journals (Sweden)

Rongrong YANG

2012-02-01

Full Text Available Background and objective It has been proven that volumetric measurements could detect subtle changes in small pulmonary nodules in serial CT scans, and thus may play an important role in the follow-up of indeterminate pulmonary nodules and in differentiating malignant nodules from benign nodules. The current study aims to evaluate the effects of different reconstruction parameters on the volumetric measurements of pulmonary nodules in chest CT scans. Methods Thirty subjects who underwent chest CT scan because of indeterminate pulmonary nodules in General Hospital of Tianjin Medical University from December 2009 to August 2011 were retrospectively analyzed. A total of 52 pulmonary nodules were included, and all CT data were reconstructed using three reconstruction algorithms and three slice thicknesses. The volumetric measurements of the nodules were performed using the advanced lung analysis (ALA software. The effects of the reconstruction algorithms, slice thicknesses, and nodule diameters on the volumetric measurements were assessed using the multivariate analysis of variance for repeated measures, the correlation analysis, and the Bland-Altman method. Results The reconstruction algorithms (F=13.6, P<0.001 and slice thicknesses (F=4.4, P=0.02 had significant effects on the measured volume of pulmonary nodules. In addition, the coefficients of variation of nine measurements were inversely related with nodule diameter (r=-0.814, P<0.001. The volume measured at the 2.5 mm slice thickness had poor agreement with the volumes measured at 1.25 mm and 0.625 mm, respectively. Moreover, the best agreement was achieved between the slice thicknesses of 1.25 mm and 0.625 mm using the bone algorithm. Conclusion Reconstruction algorithms and slice thicknesses have significant impacts on the volumetric measurements of lung nodules, especially for the small nodules. Therefore, the reconstruction setting in serial CT scans should be consistent in the follow

Evaluation of accelerated iterative x-ray CT image reconstruction using floating point graphics hardware

International Nuclear Information System (INIS)

Kole, J S; Beekman, F J

2006-01-01

Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases

Fourier rebinning algorithm for inverse geometry CT.

Science.gov (United States)

Mazin, Samuel R; Pele, Norbert J

2008-11-01

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

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

International Nuclear Information System (INIS)

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

2005-01-01

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

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

Science.gov (United States)

Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

2011-03-01

Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

3D dictionary learning based iterative cone beam CT reconstruction

Directory of Open Access Journals (Sweden)

Ti Bai

2014-03-01

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

Methods of X-ray CT image reconstruction from few projections

International Nuclear Information System (INIS)

Wang, H.

2011-01-01

To improve the safety (low dose) and the productivity (fast acquisition) of a X-ray CT system, we want to reconstruct a high quality image from a small number of projections. The classical reconstruction algorithms generally fail since the reconstruction procedure is unstable and suffers from artifacts. A new approach based on the recently developed 'Compressed Sensing' (CS) theory assumes that the unknown image is in some sense 'sparse' or 'compressible', and the reconstruction is formulated through a non linear optimization problem (TV/l1 minimization) by enhancing the sparsity. Using the pixel (or voxel in 3D) as basis, to apply the CS framework in CT one usually needs a 'sparsifying' transform, and combines it with the 'X-ray projector' which applies on the pixel image. In this thesis, we have adapted a 'CT-friendly' radial basis of Gaussian family called 'blob' to the CS-CT framework. The blob has better space-frequency localization properties than the pixel, and many operations, such as the X-ray transform, can be evaluated analytically and are highly parallelizable (on GPU platform). Compared to the classical Kaisser-Bessel blob, the new basis has a multi-scale structure: an image is the sum of dilated and translated radial Mexican hat functions. The typical medical objects are compressible under this basis, so the sparse representation system used in the ordinary CS algorithms is no more needed. 2D simulations show that the existing TV and l1 algorithms are more efficient and the reconstructions have better visual quality than the equivalent approach based on the pixel or wavelet basis. The new approach has also been validated on 2D experimental data, where we have observed that in general the number of projections can be reduced to about 50%, without compromising the image quality. (author) [fr

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)

Diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction algorithm for the detection of hypervascular liver lesions: a phantom study

Energy Technology Data Exchange (ETDEWEB)

Nakamoto, Atsushi; Tanaka, Yoshikazu; Juri, Hiroshi; Nakai, Go; Narumi, Yoshifumi [Osaka Medical College, Department of Radiology, Takatsuki, Osaka (Japan); Yoshikawa, Shushi [Osaka Medical College Hospital, Central Radiology Department, Takatsuki, Osaka (Japan)

2017-07-15

To investigate the diagnostic performance of reduced-dose CT with a hybrid iterative reconstruction (IR) algorithm for the detection of hypervascular liver lesions. Thirty liver phantoms with or without simulated hypervascular lesions were scanned with a 320-slice CT scanner with control-dose (40 mAs) and reduced-dose (30 and 20 mAs) settings. Control-dose images were reconstructed with filtered back projection (FBP), and reduced-dose images were reconstructed with FBP and a hybrid IR algorithm. Objective image noise and the lesion to liver contrast-to-noise ratio (CNR) were evaluated quantitatively. Images were interpreted independently by 2 blinded radiologists, and jackknife alternative free-response receiver-operating characteristic (JAFROC) analysis was performed. Hybrid IR images with reduced-dose settings (both 30 and 20 mAs) yielded significantly lower objective image noise and higher CNR than control-dose FBP images (P <.05). However, hybrid IR images with reduced-dose settings had lower JAFROC1 figure of merit than control-dose FBP images, although only the difference between 20 mAs images and control-dose FBP images was significant for both readers (P <.01). An aggressive reduction of the radiation dose would impair the detectability of hypervascular liver lesions, although objective image noise and CNR would be preserved by a hybrid IR algorithm. (orig.)

Brachytherapy reconstruction using orthogonal scout views from the CT

International Nuclear Information System (INIS)

Perez, J.; Lliso, F.; Carmona, V.; Bea, J.; Tormo, A.; Petschen, I.

1996-01-01

Introduction: CT assisted brachytherapy planning is demonstrating to have great advantages as external RT planning does. One of the problems we have found in this approach with the conventional gynecological Fletcher applicators is the high amount of artefacts (ovoids with rectal and vessical protections) in the CT slice. We have introduced a reconstruction method based on scout views in order to avoid this problem, allowing us to perform brachytherapy reconstruction completely CT assisted. We use a virtual simulation chain by General Electric Medical Systems. Method and discussion: Two orthogonal scout views (0 and 90 tube positions) are performed. The reconstruction method takes into account the virtual position of the focus and the fact that there is only divergence in the transverse plane. Algorithms developed for sources as well as for reference points localisation (A, B, lymphatic Fletcher trapezoid, pelvic wall, etc.) are presented. This method has the following practical advantages: the porte-cassette is not necessary, the image quality can be improved (it is very helpful in pelvic lateral views that are critical in conventional radiographs), the total time to get the data is smaller than for conventional radiographs (reduction of patient motion effects) and problems that appear in CT-slice based reconstruction in the case of strongly curved intrauterine applicators are avoided. Even though the resolution is smaller than in conventional radiographs it is good enough for brachytherapy. Regarding the CT planning this method presents the interesting feature that the co-ordinate system is the same for the reconstruction process that for the CT-slices set. As the application can be reconstructed from scout views and the doses can be evaluated on CT slices it is easier to correlate the dose values obtained for the traditional points with those provided by the CT information

A parallel implementation of 3-d CT image reconstruction on a hypercube multiprocessor

International Nuclear Information System (INIS)

Chen, C.M.; Lee, S.Y.; Cho, Z.H.

1990-01-01

In this paper, the authors describe how image reconstruction in computerized tomography (CT) can be parallelized on a message-passing multiprocessor. In particular, the results obtained from parallel implementation of 3-D CT image reconstruction for parallel beam geometries on the Intel hypercube, iPSC/2, are presented. A two stage pipelining approach is employed for filtering (convolution) and backprojection. The conventional sequential convolution algorithm is modified such that the symmetry of the filter kernel is fully utilized for parallelization. In the backprojection stage, the 3-D incremental algorithm, the authors' recently developed backprojection scheme which is shown to be faster than conventional algorithm, is parallelized

Computer-assisted lung nodule volumetry from multi-detector row CT: Influence of image reconstruction parameters

International Nuclear Information System (INIS)

Honda, Osamu; Sumikawa, Hiromitsu; Johkoh, Takeshi; Tomiyama, Noriyuki; Mihara, Naoki; Inoue, Atsuo; Tsubamoto, Mitsuko; Natsag, Javzandulam; Hamada, Seiki; Nakamura, Hironobu

2007-01-01

Purpose: To investigate differences in volumetric measurement of pulmonary nodules caused by changing the reconstruction parameters for multi-detector row CT. Materials and methods: Thirty-nine pulmonary nodules less than 2 cm in diameter were examined by multi-slice CT. All nodules were solid, and located in the peripheral part of the lungs. The resultant 48 parameters images were reconstructed by changing slice thickness (1.25, 2.5, 3.75, or 5 mm), field of view (FOV: 10, 20, or 30 cm), algorithm (high-spatial frequency algorithm or low-spatial frequency algorithm) and reconstruction interval (reconstruction with 50% overlapping of the reconstructed slices or non-overlapping reconstruction). Volumetric measurements were calculated using commercially available software. The differences between nodule volumes were analyzed by the Kruskal-Wallis test and the Wilcoxon Signed-Ranks test. Results: The diameter of the nodules was 8.7 ± 2.7 mm on average, ranging from 4.3 to 16.4 mm. Pulmonary nodule volume did not change significantly with changes in slice thickness or FOV (p > 0.05), but was significantly larger with the high-spatial frequency algorithm than the low-spatial frequency algorithm (p < 0.05), except for one reconstruction parameter. The volumes determined by non-overlapping reconstruction were significantly larger than those of overlapping reconstruction (p < 0.05), except for a 1.25 mm thickness with 10 cm FOV with the high-spatial frequency algorithm, and 5 mm thickness. The maximum difference in measured volume was 16% on average between the 1.25 mm slice thickness/10 cm FOV/high-spatial frequency algorithm parameters and overlapping reconstruction. Conclusion: Volumetric measurements of pulmonary nodules differ with changes in the reconstruction parameters, with a tendency toward larger volumes in high-spatial frequency algorithm and non-overlapping reconstruction compared to the low-spatial frequency algorithm and overlapping reconstruction

Alpha image reconstruction (AIR): A new iterative CT image reconstruction approach using voxel-wise alpha blending

International Nuclear Information System (INIS)

Hofmann, Christian; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

2014-01-01

factor for contrast-resolution plots. Furthermore, the authors calculate the contrast-to-noise ratio with the low contrast disks and the authors compare the agreement of the reconstructions with the ground truth by calculating the normalized cross-correlation and the root-mean-square deviation. To evaluate the clinical performance of the proposed method, the authors reconstruct patient data acquired with a Somatom Definition Flash dual source CT scanner (Siemens Healthcare, Forchheim, Germany). Results: The results of the simulation study show that among the compared algorithms AIR achieves the highest resolution and the highest agreement with the ground truth. Compared to the reference FBP reconstruction AIR is able to reduce the relative pixel noise by up to 50% and at the same time achieve a higher resolution by maintaining the edge information from the basis images. These results can be confirmed with the patient data. Conclusions: To evaluate the AIR algorithm simulated and measured patient data of a state-of-the-art clinical CT system were processed. It is shown, that generating CT images through the reconstruction of weighting coefficients has the potential to improve the resolution noise trade-off and thus to improve the dose usage in clinical CT

Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction

Science.gov (United States)

Fang, Shiting; Wang, Huafeng; Liu, Yueliang; Zhang, Minghui; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

2017-10-01

Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al’s algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al’s method, thus indicating the effectivity and competitiveness of the proposed algorithm.

GPU-accelerated few-view CT reconstruction using the OSC and TV techniques

Energy Technology Data Exchange (ETDEWEB)

Matenine, Dmitri [Montreal Univ., QC (Canada). Dept. de Physique; Hissoiny, Sami [Ecole Polytechnique de Montreal, QC (Canada). Dept. de Genie Informatique et Genie Logiciel; Despres, Philippe [Centre Hospitalier Univ. de Quebec, QC (Canada). Dept. de Radio-Oncologie

2011-07-01

The present work proposes a promising iterative reconstruction technique designed specifically for X-ray transmission computed tomography (CT). The main objective is to reduce diagnostic radiation dose through the reduction of the number of CT projections, while preserving image quality. The second objective is to provide a fast implementation compatible with clinical activities. The proposed tomographic reconstruction technique is a combination of the Ordered Subsets Convex (OSC) algorithm and the Total Variation minimization (TV) regularization technique. The results in terms of image quality and computational speed are discussed. Using this technique, it was possible to obtain reconstructed slices of relatively good quality with as few as 100 projections, leading to potential dose reduction factors of up to an order of magnitude depending on the application. The algorithm was implemented on a Graphical Processing Unit (GPU) and yielded reconstruction times of approximately 185 ms per slice. (orig.)

Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study.

Science.gov (United States)

Kim, Hyungjin; Park, Chang Min; Song, Yong Sub; Lee, Sang Min; Goo, Jin Mo

2014-05-01

To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. CT scans were performed on a chest phantom containing various nodules (10 and 12mm; +100, -630 and -800HU) at 120kVp with tube current-time settings of 10, 20, 50, and 100mAs. Each CT was reconstructed using filtered back projection (FBP), iDose(4) and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p>0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose(4) at all radiation dose settings (pvolumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Interior tomography in microscopic CT with image reconstruction constrained by full field of view scan at low spatial resolution

Science.gov (United States)

Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang

2018-04-01

In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.

CT reconstruction from few-views with anisotropic edge-guided total variance

International Nuclear Information System (INIS)

Rong, Junyan; Liu, Wenlei; Gao, Peng; Liao, Qimei; Jiao, Chun; Ma, Jianhua; Lu, Hongbing

2016-01-01

To overcome the oversmoothing drawback in the edge areas when reconstructing few-view CT with total variation (TV) minimization, in this paper, we propose an anisotropic edge-guided TV minimization framework for few-view CT reconstruction. In the framework, anisotropic TV is summed with pre-weighted image gradient and then used as the object function for minimizing. It includes edge-guided TV minimization (EGTV) and edge-guided adaptive-weighted TV minimization (EGAwTV) algorithms. For EGTV algorithm, the weights of the TV discretization term are updated by anisotropic edge information detected from the image, whereas the weights for EGAwTV are determined based on edge information and local image-intensity gradients. To solve the minimization problem of the proposed algorithm, a similar TV-based minimization implementation is developed to address the raw data fidelity and other constraints. The evaluation results using both computer simulations with the Shepp-Logan phantom and experimental data from a physical phantom demonstrate that the proposed algorithms exhibit noticeable gains in the merits of spatial resolution compared with the conventional TV and other modified TV algorithms.

In-line phase contrast micro-CT reconstruction for biomedical specimens.

Science.gov (United States)

Fu, Jian; Tan, Renbo

2014-01-01

X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.

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

Directory of Open Access Journals (Sweden)

Peigang Ning

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

Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

International Nuclear Information System (INIS)

Brady, S. L.; Yee, B. S.; Kaufman, R. A.

2012-01-01

Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR™) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR™. Empirically derived dose reduction limits were established for ASiR™ for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%–100% ASiR™ blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR™ implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR™ reconstruction to maintain noise equivalence of the 0% ASiR™ image. Results: The ASiR™ algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR™ reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR™ presented a more smoothed appearance than the pre-ASiR™ 100% FBP image. Finally, relative to non-ASiR™ images with 100% of standard dose across the

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

OpenAIRE

Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Kuncic, Zdenka; Keall, Paul J.

2014-01-01

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An inv...

Accelerated Compressed Sensing Based CT Image Reconstruction.

Science.gov (United States)

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

2015-01-01

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

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.

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

Science.gov (United States)

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

2013-03-01

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

Reduction of metal artifacts from hip prostheses on CT images of the pelvis: value of iterative reconstructions.

Science.gov (United States)

Morsbach, Fabian; Bickelhaupt, Sebastian; Wanner, Guido A; Krauss, Andreas; Schmidt, Bernhard; Alkadhi, Hatem

2013-07-01

To assess the value of iterative frequency split-normalized (IFS) metal artifact reduction (MAR) for computed tomography (CT) of hip prostheses. This study had institutional review board and local ethics committee approval. First, a hip phantom with steel and titanium prostheses that had inlays of water, fat, and contrast media in the pelvis was used to optimize the IFS algorithm. Second, 41 consecutive patients with hip prostheses who were undergoing CT were included. Data sets were reconstructed with filtered back projection, the IFS algorithm, and a linear interpolation MAR algorithm. Two blinded, independent readers evaluated axial, coronal, and sagittal CT reformations for overall image quality, image quality of pelvic organs, and assessment of pelvic abnormalities. CT attenuation and image noise were measured. Statistical analysis included the Friedman test, Wilcoxon signed-rank test, and Levene test. Ex vivo experiments demonstrated an optimized IFS algorithm by using a threshold of 2200 HU with four iterations for both steel and titanium prostheses. Measurements of CT attenuation of the inlays were significantly (P algorithm for CT image reconstruction significantly reduces metal artifacts from hip prostheses, improves the reliability of CT number measurements, and improves the confidence for depicting pelvic abnormalities.

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)

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

International Nuclear Information System (INIS)

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

2003-01-01

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

Motion estimation and compensation in dynamic spiral CT reconstruction

International Nuclear Information System (INIS)

Kimdon, J.; Grangeat, P.; Koenig, A.; Bonnet, St.

2004-01-01

Respiratory and cardiac motion causes blurring in dynamic X-ray Computed Tomography (CT). Fast scans reduce this problem, but they require a higher radiation dose per time period to maintain the signal to noise ratio of the resulting images, thereby magnifying the health risk to the patient. As an alternative to increased radiation, our team has already developed a cone-beam reconstruction algorithm based on a dynamic particle model that estimates, predicts, and compensates for respiratory motion in circular X-ray CT. The current paper presents an extension of this method to spiral CT, applicable to modern multi-slice scanners that take advantage of the speed and dose benefits of helical trajectories. We adapted all three main areas of the algorithm: backprojection, prediction, and compensation/accumulation. In backprojection, we changed the longitudinal re-binning technique, filter direction, and the method of enforcing the data sufficiency requirements. For prediction, we had to be careful of objects appearing and disappearing as the scanner bed advanced. For compensation/accumulation, we controlled the reconstruction time and combined images to cover a greater longitudinal extent for each phase in the respiratory or cardiac cycle. Tests with moving numerical phantoms demonstrate that the algorithm successfully improves the temporal resolution of the images without increasing the dose or reducing the signal-to-noise ratio. (authors)

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

International Nuclear Information System (INIS)

Vaegler, Sven

2016-01-01

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

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

Science.gov (United States)

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

2016-12-01

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

Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study

International Nuclear Information System (INIS)

Kim, Hyungjin; Park, Chang Min; Song, Yong Sub; Lee, Sang Min; Goo, Jin Mo

2014-01-01

Purpose: To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. Materials and methods: CT scans were performed on a chest phantom containing various nodules (10 and 12 mm; +100, −630 and −800 HU) at 120 kVp with tube current–time settings of 10, 20, 50, and 100 mAs. Each CT was reconstructed using filtered back projection (FBP), iDose 4 and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Results: Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p > 0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose 4 at all radiation dose settings (p < 0.05). Conclusion: Semi-automated nodule volumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility

Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyungjin, E-mail: khj.snuh@gmail.com [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Park, Chang Min, E-mail: cmpark@radiol.snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Cancer Research Institute, Seoul National University, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Song, Yong Sub, E-mail: terasong@gmail.com [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Lee, Sang Min, E-mail: sangmin.lee.md@gmail.com [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Goo, Jin Mo, E-mail: jmgoo@plaza.snu.ac.kr [Department of Radiology, Seoul National University College of Medicine, Institute of Radiation Medicine, Seoul National University Medical Research Center, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of); Cancer Research Institute, Seoul National University, 101, Daehangno, Jongno-gu, Seoul 110-744 (Korea, Republic of)

2014-05-15

Purpose: To evaluate the influence of radiation dose settings and reconstruction algorithms on the measurement accuracy and reproducibility of semi-automated pulmonary nodule volumetry. Materials and methods: CT scans were performed on a chest phantom containing various nodules (10 and 12 mm; +100, −630 and −800 HU) at 120 kVp with tube current–time settings of 10, 20, 50, and 100 mAs. Each CT was reconstructed using filtered back projection (FBP), iDose{sup 4} and iterative model reconstruction (IMR). Semi-automated volumetry was performed by two radiologists using commercial volumetry software for nodules at each CT dataset. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. The absolute percentage measurement errors and differences were then calculated for volume and mass. The influence of radiation dose and reconstruction algorithm on measurement accuracy, reproducibility and objective image quality metrics was analyzed using generalized estimating equations. Results: Measurement accuracy and reproducibility of nodule volume and mass were not significantly associated with CT radiation dose settings or reconstruction algorithms (p > 0.05). Objective image quality metrics of CT images were superior in IMR than in FBP or iDose{sup 4} at all radiation dose settings (p < 0.05). Conclusion: Semi-automated nodule volumetry can be applied to low- or ultralow-dose chest CT with usage of a novel iterative reconstruction algorithm without losing measurement accuracy and reproducibility.

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

Science.gov (United States)

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

2018-01-01

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

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-05-15

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

Radiation dose reduction in medical x-ray CT via Fourier-based iterative reconstruction.

Science.gov (United States)

Fahimian, Benjamin P; Zhao, Yunzhe; Huang, Zhifeng; Fung, Russell; Mao, Yu; Zhu, Chun; Khatonabadi, Maryam; DeMarco, John J; Osher, Stanley J; McNitt-Gray, Michael F; Miao, Jianwei

2013-03-01

A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry. EST is a Fourier based iterative algorithm, which iterates back and forth between real and Fourier space utilizing the algebraically exact pseudopolar fast Fourier transform (PPFFT). In each iteration, physical constraints and mathematical regularization are applied in real space, while the measured data are enforced in Fourier space. The algorithm is automatically terminated when a proposed termination criterion is met. Experimentally, fan-beam projections were acquired by the Siemens z-flying focal spot technology, and subsequently interleaved and rebinned to a pseudopolar grid. Image quality phantoms were scanned at systematically varied mAs settings, reconstructed by EST and conventional reconstruction methods such as filtered back projection (FBP), and quantified using metrics including resolution, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs). Pediatric data sets were reconstructed at their original acquisition settings and additionally simulated to lower dose settings for comparison and evaluation of the potential for radiation dose reduction. Numerical experiments were conducted to quantify EST and other iterative methods in terms of image quality and computation time. The extension of EST to helical cone-beam CT was implemented by using the advanced single-slice rebinning (ASSR) method. Based on the phantom and pediatric patient fan-beam CT data, it is demonstrated that EST reconstructions with the lowest scanner flux setting of 39 m

Radiation dose reduction in medical x-ray CT via Fourier-based iterative reconstruction

International Nuclear Information System (INIS)

Fahimian, Benjamin P.; Zhao Yunzhe; Huang Zhifeng; Fung, Russell; Zhu Chun; Miao Jianwei; Mao Yu; Khatonabadi, Maryam; DeMarco, John J.; McNitt-Gray, Michael F.; Osher, Stanley J.

2013-01-01

Purpose: A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry. Methods: EST is a Fourier based iterative algorithm, which iterates back and forth between real and Fourier space utilizing the algebraically exact pseudopolar fast Fourier transform (PPFFT). In each iteration, physical constraints and mathematical regularization are applied in real space, while the measured data are enforced in Fourier space. The algorithm is automatically terminated when a proposed termination criterion is met. Experimentally, fan-beam projections were acquired by the Siemens z-flying focal spot technology, and subsequently interleaved and rebinned to a pseudopolar grid. Image quality phantoms were scanned at systematically varied mAs settings, reconstructed by EST and conventional reconstruction methods such as filtered back projection (FBP), and quantified using metrics including resolution, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs). Pediatric data sets were reconstructed at their original acquisition settings and additionally simulated to lower dose settings for comparison and evaluation of the potential for radiation dose reduction. Numerical experiments were conducted to quantify EST and other iterative methods in terms of image quality and computation time. The extension of EST to helical cone-beam CT was implemented by using the advanced single-slice rebinning (ASSR) method. Results: Based on the phantom and pediatric patient fan-beam CT data, it is demonstrated that EST reconstructions with the lowest

A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction.

Science.gov (United States)

Kang, Eunhee; Min, Junhong; Ye, Jong Chul

2017-10-01

Due to the potential risk of inducing cancer, radiation exposure by X-ray CT devices should be reduced for routine patient scanning. However, in low-dose X-ray CT, severe artifacts typically occur due to photon starvation, beam hardening, and other causes, all of which decrease the reliability of the diagnosis. Thus, a high-quality reconstruction method from low-dose X-ray CT data has become a major research topic in the CT community. Conventional model-based de-noising approaches are, however, computationally very expensive, and image-domain de-noising approaches cannot readily remove CT-specific noise patterns. To tackle these problems, we want to develop a new low-dose X-ray CT algorithm based on a deep-learning approach. We propose an algorithm which uses a deep convolutional neural network (CNN) which is applied to the wavelet transform coefficients of low-dose CT images. More specifically, using a directional wavelet transform to extract the directional component of artifacts and exploit the intra- and inter- band correlations, our deep network can effectively suppress CT-specific noise. In addition, our CNN is designed with a residual learning architecture for faster network training and better performance. Experimental results confirm that the proposed algorithm effectively removes complex noise patterns from CT images derived from a reduced X-ray dose. In addition, we show that the wavelet-domain CNN is efficient when used to remove noise from low-dose CT compared to existing approaches. Our results were rigorously evaluated by several radiologists at the Mayo Clinic and won second place at the 2016 "Low-Dose CT Grand Challenge." To the best of our knowledge, this work is the first deep-learning architecture for low-dose CT reconstruction which has been rigorously evaluated and proven to be effective. In addition, the proposed algorithm, in contrast to existing model-based iterative reconstruction (MBIR) methods, has considerable potential to benefit from

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

Science.gov (United States)

Cui, Xiaoming; Li, Tao; Li, Xin; Zhou, Weihua

2015-05-01

The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0±8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

SART-Type Half-Threshold Filtering Approach for CT Reconstruction.

Science.gov (United States)

Yu, Hengyong; Wang, Ge

2014-01-01

The [Formula: see text] regularization problem has been widely used to solve the sparsity constrained problems. To enhance the sparsity constraint for better imaging performance, a promising direction is to use the [Formula: see text] norm (0 < p < 1) and solve the [Formula: see text] minimization problem. Very recently, Xu et al. developed an analytic solution for the [Formula: see text] regularization via an iterative thresholding operation, which is also referred to as half-threshold filtering. In this paper, we design a simultaneous algebraic reconstruction technique (SART)-type half-threshold filtering framework to solve the computed tomography (CT) reconstruction problem. In the medical imaging filed, the discrete gradient transform (DGT) is widely used to define the sparsity. However, the DGT is noninvertible and it cannot be applied to half-threshold filtering for CT reconstruction. To demonstrate the utility of the proposed SART-type half-threshold filtering framework, an emphasis of this paper is to construct a pseudoinverse transforms for DGT. The proposed algorithms are evaluated with numerical and physical phantom data sets. Our results show that the SART-type half-threshold filtering algorithms have great potential to improve the reconstructed image quality from few and noisy projections. They are complementary to the counterparts of the state-of-the-art soft-threshold filtering and hard-threshold filtering.

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.

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Angular integration and inter-projection correlation effects in CT reconstruction

International Nuclear Information System (INIS)

Crawford, C.R.; Pele, N.J.

1987-01-01

CT reconstruction algorithms require snap-shot projections of an object. In order to minimize scan times, CT scanners rotate continuously which, in turn, prevents the acquisition of snap-shot projections. Acquired projections are integrals over angular position and may be correlated inter-projection. This paper shows that angular integration and inter-projection correlation introduce a radially dependent degradation of the spatial resolution and cause the image noise to vary non-linearly with radial position

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

International Nuclear Information System (INIS)

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

2009-01-01

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

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

GPU accelerated CT reconstruction for clinical use: quality driven performance

Science.gov (United States)

Vaz, Michael S.; Sneyders, Yuri; McLin, Matthew; Ricker, Alan; Kimpe, Tom

2007-03-01

We present performance and quality analysis of GPU accelerated FDK filtered backprojection for cone beam computed tomography (CBCT) reconstruction. Our implementation of the FDK CT reconstruction algorithm does not compromise fidelity at any stage and yields a result that is within 1 HU of a reference C++ implementation. Our streaming implementation is able to perform reconstruction as the images are acquired; it addresses low latency as well as fast throughput, which are key considerations for a "real-time" design. Further, it is scaleable to multiple GPUs for increased performance. The implementation does not place any constraints on image acquisition; it works effectively for arbitrary angular coverage with arbitrary angular spacing. As such, this GPU accelerated CT reconstruction solution may easily be used with scanners that are already deployed. We are able to reconstruct a 512 x 512 x 340 volume from 625 projections, each sized 1024 x 768, in less than 50 seconds. The quoted 50 second timing encompasses the entire reconstruction using bilinear interpolation and includes filtering on the CPU, uploading the filtered projections to the GPU, and also downloading the reconstructed volume from GPU memory to system RAM.

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

Science.gov (United States)

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

2015-01-01

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

Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

Energy Technology Data Exchange (ETDEWEB)

Brady, S. L.; Yee, B. S.; Kaufman, R. A. [Department of Radiological Sciences, St. Jude Children' s Research Hospital, Memphis, Tennessee 38105 (United States)

2012-09-15

Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR Trade-Mark-Sign ) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR Trade-Mark-Sign . Empirically derived dose reduction limits were established for ASiR Trade-Mark-Sign for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%-100% ASiR Trade-Mark-Sign blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR Trade-Mark-Sign implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR Trade-Mark-Sign reconstruction to maintain noise equivalence of the 0% ASiR Trade-Mark-Sign image. Results: The ASiR Trade-Mark-Sign algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR Trade-Mark-Sign reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR Trade-Mark-Sign presented a more

Fourier-based reconstruction via alternating direction total variation minimization in linear scan CT

International Nuclear Information System (INIS)

Cai, Ailong; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Li, Lei; Xi, Xiaoqi; Li, Jianxin

2015-01-01

In this study, we consider a novel form of computed tomography (CT), that is, linear scan CT (LCT), which applies a straight line trajectory. Furthermore, an iterative algorithm is proposed for pseudo-polar Fourier reconstruction through total variation minimization (PPF-TVM). Considering that the sampled Fourier data are distributed in pseudo-polar coordinates, the reconstruction model minimizes the TV of the image subject to the constraint that the estimated 2D Fourier data for the image are consistent with the 1D Fourier transform of the projection data. PPF-TVM employs the alternating direction method (ADM) to develop a robust and efficient iteration scheme, which ensures stable convergence provided that appropriate parameter values are given. In the ADM scheme, PPF-TVM applies the pseudo-polar fast Fourier transform and its adjoint to iterate back and forth between the image and frequency domains. Thus, there is no interpolation in the Fourier domain, which makes the algorithm both fast and accurate. PPF-TVM is particularly useful for limited angle reconstruction in LCT and it appears to be robust against artifacts. The PPF-TVM algorithm was tested with the FORBILD head phantom and real data in comparisons with state-of-the-art algorithms. Simulation studies and real data verification suggest that PPF-TVM can reconstruct higher accuracy images with lower time consumption

Statistical iterative reconstruction for streak artefact reduction when using multidetector CT to image the dento-alveolar structures.

Science.gov (United States)

Dong, J; Hayakawa, Y; Kober, C

2014-01-01

When metallic prosthetic appliances and dental fillings exist in the oral cavity, the appearance of metal-induced streak artefacts is not avoidable in CT images. The aim of this study was to develop a method for artefact reduction using the statistical reconstruction on multidetector row CT images. Adjacent CT images often depict similar anatomical structures. Therefore, reconstructed images with weak artefacts were attempted using projection data of an artefact-free image in a neighbouring thin slice. Images with moderate and strong artefacts were continuously processed in sequence by successive iterative restoration where the projection data was generated from the adjacent reconstructed slice. First, the basic maximum likelihood-expectation maximization algorithm was applied. Next, the ordered subset-expectation maximization algorithm was examined. Alternatively, a small region of interest setting was designated. Finally, the general purpose graphic processing unit machine was applied in both situations. The algorithms reduced the metal-induced streak artefacts on multidetector row CT images when the sequential processing method was applied. The ordered subset-expectation maximization and small region of interest reduced the processing duration without apparent detriments. A general-purpose graphic processing unit realized the high performance. A statistical reconstruction method was applied for the streak artefact reduction. The alternative algorithms applied were effective. Both software and hardware tools, such as ordered subset-expectation maximization, small region of interest and general-purpose graphic processing unit achieved fast artefact correction.

Recent advances in iterative reconstruction for clinical SPECT/PET and CT.

Science.gov (United States)

Hutton, Brian F

2011-08-01

Statistical iterative reconstruction is now widely used in clinical practice and has contributed to significant improvement in image quality in recent years. Although primarily used for reconstruction in emission tomography (both single photon emission computed tomography (SPECT) and positron emission tomography (PET)) there is increasing interest in also applying similar algorithms to x-ray computed tomography (CT). There is increasing complexity in the factors that are included in the reconstruction, a demonstration of the versatility of the approach. Research continues with exploration of methods for further improving reconstruction quality with effective correction for various sources of artefact.

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

Energy Technology Data Exchange (ETDEWEB)

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

2013-09-01

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

Comparative study between ultrahigh spatial frequency algorithm and high spatial frequency algorithm in high-resolution CT of the lungs

International Nuclear Information System (INIS)

Oh, Yu Whan; Kim, Jung Kyuk; Suh, Won Hyuck

1994-01-01

To date, the high spatial frequency algorithm (HSFA) which reduces image smoothing and increases spatial resolution has been used for the evaluation of parenchymal lung diseases in thin-section high-resolution CT. In this study, we compared the ultrahigh spatial frequency algorithm (UHSFA) with the high spatial frequency algorithm in the assessment of thin section images of the lung parenchyma. Three radiologists compared the UHSFA and HSFA on identical CT images in a line-pair resolution phantom, one lung specimen, 2 patients with normal lung and 18 patients with abnormal lung parenchyma. Scanning of a line-pair resolution phantom demonstrated no difference in resolution between two techniques but it showed that outer lines of the line pairs with maximal resolution looked thicker on UHSFA than those on HSFA. Lung parenchymal detail with UHSFA was judged equal or superior to HSFA in 95% of images. Lung parenchymal sharpness was improved with UHSFA in all images. Although UHSFA resulted in an increase in visible noise, observers did not found that image noise interfered with image interpretation. The visual CT attenuation of normal lung parenchyma is minimally increased in images with HSFA. The overall visual preference of the images reconstructed on UHSFA was considered equal to or greater than that of those reconstructed on HSFA in 78% of images. The ultrahigh spatial frequency algorithm improved the overall visual quality of the images in pulmonary parenchymal high-resolution CT

Towards an inline reconstruction architecture for micro-CT systems

International Nuclear Information System (INIS)

Brasse, David; Humbert, Bernard; Mathelin, Carole; Rio, Marie-Christine; Guyonnet, Jean-Louis

2005-01-01

Recent developments in micro-CT have revolutionized the ability to examine in vivo living experimental animal models such as mouse with a spatial resolution less than 50 μm. The main requirements of in vivo imaging for biological researchers are a good spatial resolution, a low dose induced to the animal during the full examination and a reduced acquisition and reconstruction time for screening purposes. We introduce inline acquisition and reconstruction architecture to obtain in real time the 3D attenuation map of the animal fulfilling the three previous requirements. The micro-CT system is based on commercially available x-ray detector and micro-focus x-ray source. The reconstruction architecture is based on a cluster of PCs where a dedicated communication scheme combining serial and parallel treatments is implemented. In order to obtain high performance transmission rate between the detector and the reconstruction architecture, a dedicated data acquisition system is also developed. With the proposed solution, the time required to filter and backproject a projection of 2048 x 2048 pixels inside a volume of 140 mega voxels using the Feldkamp algorithm is similar to 500 ms, the time needed to acquire the same projection

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

Science.gov (United States)

Armstrong, Ian S; Hoffmann, Sandra A

2016-11-01

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

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

Science.gov (United States)

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

2013-02-01

The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.

Gamma regularization based reconstruction for low dose CT

International Nuclear Information System (INIS)

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

2015-01-01

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

Automatic selection of optimal systolic and diastolic reconstruction windows for dual-source CT coronary angiography

International Nuclear Information System (INIS)

Seifarth, H.; Puesken, M.; Wienbeck, S.; Maintz, D.; Heindel, W.; Juergens, K.U.; Fischbach, R.

2009-01-01

The aim of this study was to assess the performance of a motion-map algorithm that automatically determines optimal reconstruction windows for dual-source coronary CT angiography. In datasets from 50 consecutive patients, optimal systolic and diastolic reconstruction windows were determined using the motion-map algorithm. For manual determination of the optimal reconstruction window, datasets were reconstructed in 5% steps throughout the RR interval. Motion artifacts were rated for each major coronary vessel using a five-point scale. Mean motion scores using the motion-map algorithm were 2.4 ± 0.8 for systolic reconstructions and 1.9 ± 0.8 for diastolic reconstructions. Using the manual approach, overall motion scores were significantly better (1.9 ± 0.5 and 1.7 ± 0.6, p 90% of cases using either approach. Using the automated approach, there was a negative correlation between heart rate and motion scores for systolic reconstructions (ρ = -0.26, p 80 bpm (systolic reconstruction). (orig.)

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

Energy Technology Data Exchange (ETDEWEB)

Puchner, Stefan B. [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Medical University of Vienna, Department of Biomedical Imaging and Image-Guided Therapy, Vienna (Austria); Ferencik, Maros [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Harvard Medical School, Division of Cardiology, Massachusetts General Hospital, Boston, MA (United States); Maurovich-Horvat, Pal [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Semmelweis University, MTA-SE Lenduelet Cardiovascular Imaging Research Group, Heart and Vascular Center, Budapest (Hungary); Nakano, Masataka; Otsuka, Fumiyuki; Virmani, Renu [CV Path Institute Inc., Gaithersburg, MD (United States); Kauczor, Hans-Ulrich [University Hospital Heidelberg, Ruprecht-Karls-University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany); Hoffmann, Udo [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); Schlett, Christopher L. [Massachusetts General Hospital, Harvard Medical School, Cardiac MR PET CT Program, Department of Radiology, Boston, MA (United States); University Hospital Heidelberg, Ruprecht-Karls-University of Heidelberg, Department of Diagnostic and Interventional Radiology, Heidelberg (Germany)

2015-01-15

To evaluate whether iterative reconstruction algorithms improve the diagnostic accuracy of coronary CT angiography (CCTA) for detection of lipid-core plaque (LCP) compared to histology. CCTA and histological data were acquired from three ex vivo hearts. CCTA images were reconstructed using filtered back projection (FBP), adaptive-statistical (ASIR) and model-based (MBIR) iterative algorithms. Vessel cross-sections were co-registered between FBP/ASIR/MBIR and histology. Plaque area <60 HU was semiautomatically quantified in CCTA. LCP was defined by histology as fibroatheroma with a large lipid/necrotic core. Area under the curve (AUC) was derived from logistic regression analysis as a measure of diagnostic accuracy. Overall, 173 CCTA triplets (FBP/ASIR/MBIR) were co-registered with histology. LCP was present in 26 cross-sections. Average measured plaque area <60 HU was significantly larger in LCP compared to non-LCP cross-sections (mm{sup 2}: 5.78 ± 2.29 vs. 3.39 ± 1.68 FBP; 5.92 ± 1.87 vs. 3.43 ± 1.62 ASIR; 6.40 ± 1.55 vs. 3.49 ± 1.50 MBIR; all p < 0.0001). AUC for detecting LCP was 0.803/0.850/0.903 for FBP/ASIR/MBIR and was significantly higher for MBIR compared to FBP (p = 0.01). MBIR increased sensitivity for detection of LCP by CCTA. Plaque area <60 HU in CCTA was associated with LCP in histology regardless of the reconstruction algorithm. However, MBIR demonstrated higher accuracy for detecting LCP, which may improve vulnerable plaque detection by CCTA. (orig.)

Spectrotemporal CT data acquisition and reconstruction at low dose

International Nuclear Information System (INIS)

Clark, Darin P.; Badea, Cristian T.; Lee, Chang-Lung; Kirsch, David G.

2015-01-01

problem using the split Bregman method and GPU-based implementations of backprojection, reprojection, and kernel regression. Using a preclinical mouse model, the authors apply the proposed algorithm to study myocardial injury following radiation treatment of breast cancer. Results: Quantitative 5D simulations are performed using the MOBY mouse phantom. Twenty data sets (ten cardiac phases, two energies) are reconstructed with 88 μm, isotropic voxels from 450 total projections acquired over a single 360° rotation. In vivo 5D myocardial injury data sets acquired in two mice injected with gold and iodine nanoparticles are also reconstructed with 20 data sets per mouse using the same acquisition parameters (dose: ∼60 mGy). For both the simulations and the in vivo data, the reconstruction quality is sufficient to perform material decomposition into gold and iodine maps to localize the extent of myocardial injury (gold accumulation) and to measure cardiac functional metrics (vascular iodine). Their 5D CT imaging protocol represents a 95% reduction in radiation dose per cardiac phase and energy and a 40-fold decrease in projection sampling time relative to their standard imaging protocol. Conclusions: Their 5D CT data acquisition and reconstruction protocol efficiently exploits the rank-sparse nature of spectral and temporal CT data to provide high-fidelity reconstruction results without increased radiation dose or sampling time

Iterative metal artefact reduction (MAR) in postsurgical chest CT: comparison of three iMAR-algorithms.

Science.gov (United States)

Aissa, Joel; Boos, Johannes; Sawicki, Lino Morris; Heinzler, Niklas; Krzymyk, Karl; Sedlmair, Martin; Kröpil, Patric; Antoch, Gerald; Thomas, Christoph

2017-11-01

The purpose of this study was to evaluate the impact of three novel iterative metal artefact (iMAR) algorithms on image quality and artefact degree in chest CT of patients with a variety of thoracic metallic implants. 27 postsurgical patients with thoracic implants who underwent clinical chest CT between March and May 2015 in clinical routine were retrospectively included. Images were retrospectively reconstructed with standard weighted filtered back projection (WFBP) and with three iMAR algorithms (iMAR-Algo1 = Cardiac algorithm, iMAR-Algo2 = Pacemaker algorithm and iMAR-Algo3 = ThoracicCoils algorithm). The subjective and objective image quality was assessed. Averaged over all artefacts, artefact degree was significantly lower for the iMAR-Algo1 (58.9 ± 48.5 HU), iMAR-Algo2 (52.7 ± 46.8 HU) and the iMAR-Algo3 (51.9 ± 46.1 HU) compared with WFBP (91.6 ± 81.6 HU, p algorithms, respectively. iMAR-Algo2 and iMAR-Algo3 reconstructions decreased mild and moderate artefacts compared with WFBP and iMAR-Algo1 (p algorithms led to a significant reduction of metal artefacts and increase in overall image quality compared with WFBP in chest CT of patients with metallic implants in subjective and objective analysis. The iMARAlgo2 and iMARAlgo3 were best for mild artefacts. IMARAlgo1 was superior for severe artefacts. Advances in knowledge: Iterative MAR led to significant artefact reduction and increase image-quality compared with WFBP in CT after implementation of thoracic devices. Adjusting iMAR-algorithms to patients' metallic implants can help to improve image quality in CT.

SU-G-TeP2-09: Evaluation of the MaxFOV Extended Field of View (EFOV) Reconstruction Algorithm On a GE RT590 CT Scanner

International Nuclear Information System (INIS)

Grzetic, S; Weldon, M; Noa, K; Gupta, N

2016-01-01

Purpose: This study compares the newly released MaxFOV Revision 1 EFOV reconstruction algorithm for GE RT590 to the older WideView EFOV algorithm. Two radiotherapy overlays from Q-fix and Diacor, are included in our analysis. Hounsfield Units (HU) generated with the WideView algorithm varied in the extended field (beyond 50cm) and the scanned object’s border varied from slice to slice. A validation of HU consistency between the two reconstruction algorithms is performed. Methods: A CatPhan 504 and CIRS062 Electron Density Phantom were scanned on a GE RT590 CT-Simulator. The phantoms were positioned in multiple locations within the scan field of view so some of the density plugs were outside the 50cm reconstruction circle. Images were reconstructed using both the WideView and MaxFOV algorithms. The HU for each scan were characterized both in average over a volume and in profile. Results: HU values are consistent between the two algorithms. Low-density material will have a slight increase in HU value and high-density material will have a slight decrease in HU value as the distance from the sweet spot increases. Border inconsistencies and shading artifacts are still present with the MaxFOV reconstruction on the Q-fix overlay but not the Diacor overlay (It should be noted that the Q-fix overlay is not currently GE-certified). HU values for water outside the 50cm FOV are within 40HU of reconstructions at the sweet spot of the scanner. CatPhan HU profiles show improvement with the MaxFOV algorithm as it approaches the scanner edge. Conclusion: The new MaxFOV algorithm improves the contour border for objects outside of the standard FOV when using a GE-approved tabletop. Air cavities outside of the standard FOV create inconsistent object borders. HU consistency is within GE specifications and the accuracy of the phantom edge improves. Further adjustments to the algorithm are being investigated by GE.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-04-15

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

Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

Science.gov (United States)

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.

A backprojection-filtration algorithm for nonstandard spiral cone-beam CT with an n-PI-window

International Nuclear Information System (INIS)

Yu Hengyong; Ye Yangbo; Zhao Shiying; Wang Ge

2005-01-01

For applications in bolus-chasing computed tomography (CT) angiography and electron-beam micro-CT, the backprojection-filtration (BPF) formula developed by Zou and Pan was recently generalized by Ye et al to reconstruct images from cone-beam data collected along a rather flexible scanning locus, including a nonstandard spiral. A major implication of the generalized BPF formula is that it can be applied for n-PI-window-based reconstruction in the nonstandard spiral scanning case. In this paper, we design an n-PI-window-based BPF algorithm, and report the numerical simulation results with the 3D Shepp-Logan phantom and Defrise disk phantom. The proposed BPF algorithm consists of three steps: cone-beam data differentiation, weighted backprojection and inverse Hilbert filtration. Our simulated results demonstrate the feasibility and merits of the proposed algorithm

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

Science.gov (United States)

Zeng, Gengsheng L

2017-10-01

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

Low-dose dual-energy cone-beam CT using a total-variation minimization algorithm

International Nuclear Information System (INIS)

Min, Jong Hwan

2011-02-01

Dual-energy cone-beam CT is an important imaging modality in diagnostic applications, and may also find its use in other application such as therapeutic image guidance. Despite of its clinical values, relatively high radiation dose of dual-energy scan may pose a challenge to its wide use. In this work, we investigated a low-dose, pre-reconstruction type of dual-energy cone-beam CT (CBCT) using a total-variation minimization algorithm for image reconstruction. An empirical dual-energy calibration method was used to prepare material-specific projection data. Raw data at high and low tube voltages are converted into a set of basis functions which can be linearly combined to produce material-specific data using the coefficients obtained through the calibration process. From much fewer views than are conventionally used, material specific images are reconstructed by use of the total-variation minimization algorithm. An experimental study was performed to demonstrate the feasibility of the proposed method using a micro-CT system. We have reconstructed images of the phantoms from only 90 projections acquired at tube voltages of 40 kVp and 90 kVp each. Aluminum-only and acryl-only images were successfully decomposed. We evaluated the quality of the reconstructed images by use of contrast-to-noise ratio and detectability. A low-dose dual-energy CBCT can be realized via the proposed method by greatly reducing the number of projections

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.

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR).

Science.gov (United States)

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

2013-11-01

Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables. Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision. Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A. The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of accuracy on reconstruction algorithms

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

Science.gov (United States)

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

2011-03-01

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

Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction.

Science.gov (United States)

Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide

2018-06-01

Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.

SU-E-I-93: Improved Imaging Quality for Multislice Helical CT Via Sparsity Regularized Iterative Image Reconstruction Method Based On Tensor Framelet

International Nuclear Information System (INIS)

Nam, H; Guo, M; Lee, K; Li, R; Xing, L; Gao, H

2014-01-01

Purpose: Inspired by compressive sensing, sparsity regularized iterative reconstruction method has been extensively studied. However, its utility pertinent to multislice helical 4D CT for radiotherapy with respect to imaging quality, dose, and time has not been thoroughly addressed. As the beginning of such an investigation, this work carries out the initial comparison of reconstructed imaging quality between sparsity regularized iterative method and analytic method through static phantom studies using a state-of-art 128-channel multi-slice Siemens helical CT scanner. Methods: In our iterative method, tensor framelet (TF) is chosen as the regularization method for its superior performance from total variation regularization in terms of reduced piecewise-constant artifacts and improved imaging quality that has been demonstrated in our prior work. On the other hand, X-ray transforms and its adjoints are computed on-the-fly through GPU implementation using our previous developed fast parallel algorithms with O(1) complexity per computing thread. For comparison, both FDK (approximate analytic method) and Katsevich algorithm (exact analytic method) are used for multislice helical CT image reconstruction. Results: The phantom experimental data with different imaging doses were acquired using a state-of-art 128-channel multi-slice Siemens helical CT scanner. The reconstructed image quality was compared between TF-based iterative method, FDK and Katsevich algorithm with the quantitative analysis for characterizing signal-to-noise ratio, image contrast, and spatial resolution of high-contrast and low-contrast objects. Conclusion: The experimental results suggest that our tensor framelet regularized iterative reconstruction algorithm improves the helical CT imaging quality from FDK and Katsevich algorithm for static experimental phantom studies that have been performed

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

Energy Technology Data Exchange (ETDEWEB)

Narasimhadhan, A.V.; Rajgopal, Kasi

2011-07-01

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

Statistical image reconstruction for transmission tomography using relaxed ordered subset algorithms

International Nuclear Information System (INIS)

Kole, J S

2005-01-01

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

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Intra-patient comparison of reduced-dose model-based iterative reconstruction with standard-dose adaptive statistical iterative reconstruction in the CT diagnosis and follow-up of urolithiasis

Energy Technology Data Exchange (ETDEWEB)

Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth [Peninsula Radiology Academy, Plymouth (United Kingdom); Vardhanabhuti, Varut [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); University of Hong Kong, Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, Pokfulam (China); Stuckey, Colin; Gutteridge, Catherine [Plymouth Hospitals NHS Trust, Plymouth (United Kingdom); Hyde, Christopher [University of Exeter Medical School, St Luke' s Campus, Exeter (United Kingdom); Roobottom, Carl [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); Plymouth Hospitals NHS Trust, Plymouth (United Kingdom)

2017-10-15

To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. (orig.)

Tomographic Reconstruction of Tracer Gas Concentration Profiles in a Room with the Use of a Single OP-FTIR and Two Iterative Algorithms: ART and PWLS.

Science.gov (United States)

Park, Doo Y; Fessier, Jeffrey A; Yost, Michael G; Levine, Steven P

2000-03-01

Computed tomographic (CT) reconstructions of air contaminant concentration fields were conducted in a room-sized chamber employing a single open-path Fourier transform infrared (OP-FTIR) instrument and a combination of 52 flat mirrors and 4 retroreflectors. A total of 56 beam path data were repeatedly collected for around 1 hr while maintaining a stable concentration gradient. The plane of the room was divided into 195 pixels (13 × 15) for reconstruction. The algebraic reconstruction technique (ART) failed to reconstruct the original concentration gradient patterns for most cases. These poor results were caused by the "highly underdetermined condition" in which the number of unknown values (156 pixels) exceeds that of known data (56 path integral concentrations) in the experimental setting. A new CT algorithm, called the penalized weighted least-squares (PWLS), was applied to remedy this condition. The peak locations were correctly positioned in the PWLS-CT reconstructions. A notable feature of the PWLS-CT reconstructions was a significant reduction of highly irregular noise peaks found in the ART-CT reconstructions. However, the peak heights were slightly reduced in the PWLS-CT reconstructions due to the nature of the PWLS algorithm. PWLS could converge on the original concentration gradient even when a fairly high error was embedded into some experimentally measured path integral concentrations. It was also found in the simulation tests that the PWLS algorithm was very robust with respect to random errors in the path integral concentrations. This beam geometry and the use of a single OP-FTIR scanning system, in combination with the PWLS algorithm, is a system applicable to both environmental and industrial settings.

Objective assessment of image quality and dose reduction in CT iterative reconstruction

Energy Technology Data Exchange (ETDEWEB)

Vaishnav, J. Y., E-mail: jay.vaishnav@fda.hhs.gov; Jung, W. C. [Diagnostic X-Ray Systems Branch, Office of In Vitro Diagnostic Devices and Radiological Health, Center for Devices and Radiological Health, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993 (United States); Popescu, L. M.; Zeng, R.; Myers, K. J. [Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, United States Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993 (United States)

2014-07-15

Purpose: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose in CT diagnostic imaging. As these algorithms become available on the market, a standardizable method of quantifying the dose reduction that a particular IR method can achieve would be valuable. Such a method would assist manufacturers in making promotional claims about dose reduction, buyers in comparing different devices, physicists in independently validating the claims, and the United States Food and Drug Administration in regulating the labeling of CT devices. However, the nonlinear nature of commercially available IR algorithms poses challenges to objectively assessing image quality, a necessary step in establishing the amount of dose reduction that a given IR algorithm can achieve without compromising that image quality. This review paper seeks to consolidate information relevant to objectively assessing the quality of CT IR images, and thereby measuring the level of dose reduction that a given IR algorithm can achieve. Methods: The authors discuss task-based methods for assessing the quality of CT IR images and evaluating dose reduction. Results: The authors explain and review recent literature on signal detection and localization tasks in CT IR image quality assessment, the design of an appropriate phantom for these tasks, possible choices of observers (including human and model observers), and methods of evaluating observer performance. Conclusions: Standardizing the measurement of dose reduction is a problem of broad interest to the CT community and to public health. A necessary step in the process is the objective assessment of CT image quality, for which various task-based methods may be suitable. This paper attempts to consolidate recent literature that is relevant to the development and implementation of task-based methods for the assessment of CT IR image quality.

Objective assessment of image quality and dose reduction in CT iterative reconstruction

International Nuclear Information System (INIS)

Vaishnav, J. Y.; Jung, W. C.; Popescu, L. M.; Zeng, R.; Myers, K. J.

2014-01-01

Purpose: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose in CT diagnostic imaging. As these algorithms become available on the market, a standardizable method of quantifying the dose reduction that a particular IR method can achieve would be valuable. Such a method would assist manufacturers in making promotional claims about dose reduction, buyers in comparing different devices, physicists in independently validating the claims, and the United States Food and Drug Administration in regulating the labeling of CT devices. However, the nonlinear nature of commercially available IR algorithms poses challenges to objectively assessing image quality, a necessary step in establishing the amount of dose reduction that a given IR algorithm can achieve without compromising that image quality. This review paper seeks to consolidate information relevant to objectively assessing the quality of CT IR images, and thereby measuring the level of dose reduction that a given IR algorithm can achieve. Methods: The authors discuss task-based methods for assessing the quality of CT IR images and evaluating dose reduction. Results: The authors explain and review recent literature on signal detection and localization tasks in CT IR image quality assessment, the design of an appropriate phantom for these tasks, possible choices of observers (including human and model observers), and methods of evaluating observer performance. Conclusions: Standardizing the measurement of dose reduction is a problem of broad interest to the CT community and to public health. A necessary step in the process is the objective assessment of CT image quality, for which various task-based methods may be suitable. This paper attempts to consolidate recent literature that is relevant to the development and implementation of task-based methods for the assessment of CT IR image quality

Motion estimation and compensation in dynamic spiral CT reconstruction; Estimation et compensation de mouvement en reconstruction dynamique de tomodensitometrie helicoidale

Energy Technology Data Exchange (ETDEWEB)

Kimdon, J.; Grangeat, P.; Koenig, A.; Bonnet, St

2004-07-01

Respiratory and cardiac motion causes blurring in dynamic X-ray Computed Tomography (CT). Fast scans reduce this problem, but they require a higher radiation dose per time period to maintain the signal to noise ratio of the resulting images, thereby magnifying the health risk to the patient. As an alternative to increased radiation, our team has already developed a cone-beam reconstruction algorithm based on a dynamic particle model that estimates, predicts, and compensates for respiratory motion in circular X-ray CT. The current paper presents an extension of this method to spiral CT, applicable to modern multi-slice scanners that take advantage of the speed and dose benefits of helical trajectories. We adapted all three main areas of the algorithm: backprojection, prediction, and compensation/accumulation. In backprojection, we changed the longitudinal re-binning technique, filter direction, and the method of enforcing the data sufficiency requirements. For prediction, we had to be careful of objects appearing and disappearing as the scanner bed advanced. For compensation/accumulation, we controlled the reconstruction time and combined images to cover a greater longitudinal extent for each phase in the respiratory or cardiac cycle. Tests with moving numerical phantoms demonstrate that the algorithm successfully improves the temporal resolution of the images without increasing the dose or reducing the signal-to-noise ratio. (authors)

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

International Nuclear Information System (INIS)

Wu, P; Mao, T; Gong, S; Wang, J; Niu, T; Sheng, K; Xie, Y

2016-01-01

Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimization trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

Energy Technology Data Exchange (ETDEWEB)

Wu, P; Mao, T; Gong, S; Wang, J; Niu, T [Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Institute of Translational Medicine, Zhejiang University, Hangzhou, Zhejiang (China); Sheng, K [Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA (United States); Xie, Y [Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong (China)

2016-06-15

Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimization trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R

Ultrafast and scalable cone-beam CT reconstruction using MapReduce in a cloud computing environment.

Science.gov (United States)

Meng, Bowen; Pratx, Guillem; Xing, Lei

2011-12-01

Four-dimensional CT (4DCT) and cone beam CT (CBCT) are widely used in radiation therapy for accurate tumor target definition and localization. However, high-resolution and dynamic image reconstruction is computationally demanding because of the large amount of data processed. Efficient use of these imaging techniques in the clinic requires high-performance computing. The purpose of this work is to develop a novel ultrafast, scalable and reliable image reconstruction technique for 4D CBCT∕CT using a parallel computing framework called MapReduce. We show the utility of MapReduce for solving large-scale medical physics problems in a cloud computing environment. In this work, we accelerated the Feldcamp-Davis-Kress (FDK) algorithm by porting it to Hadoop, an open-source MapReduce implementation. Gated phases from a 4DCT scans were reconstructed independently. Following the MapReduce formalism, Map functions were used to filter and backproject subsets of projections, and Reduce function to aggregate those partial backprojection into the whole volume. MapReduce automatically parallelized the reconstruction process on a large cluster of computer nodes. As a validation, reconstruction of a digital phantom and an acquired CatPhan 600 phantom was performed on a commercial cloud computing environment using the proposed 4D CBCT∕CT reconstruction algorithm. Speedup of reconstruction time is found to be roughly linear with the number of nodes employed. For instance, greater than 10 times speedup was achieved using 200 nodes for all cases, compared to the same code executed on a single machine. Without modifying the code, faster reconstruction is readily achievable by allocating more nodes in the cloud computing environment. Root mean square error between the images obtained using MapReduce and a single-threaded reference implementation was on the order of 10(-7). Our study also proved that cloud computing with MapReduce is fault tolerant: the reconstruction completed

Impact of the adaptive statistical iterative reconstruction technique on image quality in ultra-low-dose CT

International Nuclear Information System (INIS)

Xu, Yan; He, Wen; Chen, Hui; Hu, Zhihai; Li, Juan; Zhang, Tingting

2013-01-01

Aim: To evaluate the relationship between different noise indices (NIs) and radiation dose and to compare the effect of different reconstruction algorithm applications for ultra-low-dose chest computed tomography (CT) on image quality improvement and the accuracy of volumetric measurement of ground-glass opacity (GGO) nodules using a phantom study. Materials and methods: A 11 cm thick transverse phantom section with a chest wall, mediastinum, and 14 artificial GGO nodules with known volumes (919.93 ± 64.05 mm 3 ) was constructed. The phantom was scanned on a Discovery CT 750HD scanner with five different NIs (NIs = 20, 30, 40, 50, and 60). All data were reconstructed with a 0.625 mm section thickness using the filtered back-projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and Veo model-base iterative reconstruction algorithms. Image noise was measured in six regions of interest (ROIs). Nodule volumes were measured using a commercial volumetric software package. The image quality and the volume measurement errors were analysed. Results: Image noise increased dramatically from 30.7 HU at NI 20 to 122.4 HU at NI 60, with FBP reconstruction. Conversely, Veo reconstruction effectively controlled the noise increase, with an increase from 9.97 HU at NI 20 to only 15.1 HU at NI 60. Image noise at NI 60 with Veo was even lower (50.8%) than that at NI 20 with FBP. The contrast-to-noise ratio (CNR) of Veo at NI 40 was similar to that of FBP at NI 20. All artificial GGO nodules were successfully identified and measured with an average relative volume measurement error with Veo at NI 60 of 4.24%, comparable to a value of 10.41% with FBP at NI 20. At NI 60, the radiation dose was only one-tenth that at NI 20. Conclusion: The Veo reconstruction algorithms very effectively reduced image noise compared with the conventional FBP reconstructions. Using ultra-low-dose CT scanning and Veo reconstruction, GGOs can be detected and quantified with an acceptable

WE-D-18A-04: How Iterative Reconstruction Algorithms Affect the MTFs of Variable-Contrast Targets in CT Images

Energy Technology Data Exchange (ETDEWEB)

Dodge, C.T.; Rong, J. [MD Anderson Cancer Center, Houston, TX (United States); Dodge, C.W. [Methodist Hospital, Houston, TX (United States)

2014-06-15

Purpose: To determine how filtered back-projection (FBP), adaptive statistical (ASiR), and model based (MBIR) iterative reconstruction algorithms affect the measured modulation transfer functions (MTFs) of variable-contrast targets over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP401 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 24 mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 2.5mm thickness, 0.984 pitch. The images were reconstructed using GE's Standard kernel with FBP; 20%, 40% and 70% ASiR; and MBIR. A task-based MTF (MTFtask) was computed for six cylindrical targets: 2 low-contrast (Polystyrene, LDPE), 2 medium-contrast (Delrin, PMP), and 2 high-contrast (Teflon, air). MTFtask was used to compare the performance of reconstruction algorithms with decreasing CTDIvol from 24mGy, which is currently used in the clinic. Results: For the air target and 75% dose savings (6 mGy), MBIR MTFtask at 5 lp/cm measured 0.24, compared to 0.20 for 70% ASiR and 0.11 for FBP. Overall, for both high-contrast targets, MBIR MTFtask improved with increasing CTDIvol and consistently outperformed ASiR and FBP near the system's Nyquist frequency. Conversely, for Polystyrene at 6 mGy, MBIR (0.10) and 70% ASiR (0.07) MTFtask was lower than for FBP (0.18). For medium and low-contrast targets, FBP remains the best overall algorithm for improved resolution at low CTDIvol (1–6 mGy) levels, whereas MBIR is comparable at higher dose levels (12–24 mGy). Conclusion: MBIR improved the MTF of small, high-contrast targets compared to FBP and ASiR at doses of 50%–12.5% of those currently used in the clinic. However, for imaging low- and mediumcontrast targets, FBP performed the best across all dose levels. For assessing MTF from different reconstruction algorithms, task-based MTF measurements are necessary.

WE-D-18A-04: How Iterative Reconstruction Algorithms Affect the MTFs of Variable-Contrast Targets in CT Images

International Nuclear Information System (INIS)

Dodge, C.T.; Rong, J.; Dodge, C.W.

2014-01-01

Purpose: To determine how filtered back-projection (FBP), adaptive statistical (ASiR), and model based (MBIR) iterative reconstruction algorithms affect the measured modulation transfer functions (MTFs) of variable-contrast targets over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP401 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 24 mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 2.5mm thickness, 0.984 pitch. The images were reconstructed using GE's Standard kernel with FBP; 20%, 40% and 70% ASiR; and MBIR. A task-based MTF (MTFtask) was computed for six cylindrical targets: 2 low-contrast (Polystyrene, LDPE), 2 medium-contrast (Delrin, PMP), and 2 high-contrast (Teflon, air). MTFtask was used to compare the performance of reconstruction algorithms with decreasing CTDIvol from 24mGy, which is currently used in the clinic. Results: For the air target and 75% dose savings (6 mGy), MBIR MTFtask at 5 lp/cm measured 0.24, compared to 0.20 for 70% ASiR and 0.11 for FBP. Overall, for both high-contrast targets, MBIR MTFtask improved with increasing CTDIvol and consistently outperformed ASiR and FBP near the system's Nyquist frequency. Conversely, for Polystyrene at 6 mGy, MBIR (0.10) and 70% ASiR (0.07) MTFtask was lower than for FBP (0.18). For medium and low-contrast targets, FBP remains the best overall algorithm for improved resolution at low CTDIvol (1–6 mGy) levels, whereas MBIR is comparable at higher dose levels (12–24 mGy). Conclusion: MBIR improved the MTF of small, high-contrast targets compared to FBP and ASiR at doses of 50%–12.5% of those currently used in the clinic. However, for imaging low- and mediumcontrast targets, FBP performed the best across all dose levels. For assessing MTF from different reconstruction algorithms, task-based MTF measurements are necessary

The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique.

Science.gov (United States)

Kwon, Heejin; Cho, Jinhan; Oh, Jongyeong; Kim, Dongwon; Cho, Junghyun; Kim, Sanghyun; Lee, Sangyun; Lee, Jihyun

2015-10-01

iterative reconstruction. Use of the ASIR-V algorithm decreased image noise and increased image quality when compared with the ASIR and FBP methods. These results suggest that high-quality low-dose CT may represent a new clinical option.

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

Energy Technology Data Exchange (ETDEWEB)

Chen, Baiyu [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 and Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 (United States); Barnhart, Huiman [Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27705 (United States); Richard, Samuel [Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 and Department of Radiology, Duke University, Durham, North Carolina 27705 (United States); Robins, Marthony [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Colsher, James [Department of Radiology, Duke University, Durham, North Carolina 27705 (United States); Samei, Ehsan [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Carl E. Ravin Advanced Imaging Laboratories, Duke University, Durham, North Carolina 27705 (United States); Department of Radiology, Duke University, Durham, North Carolina 27705 (United States); Department of Physics, Department of Biomedical Engineering, and Department of Electronic and Computer Engineering, Duke University, Durham, North Carolina 27705 (United States)

2013-11-15

Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

International Nuclear Information System (INIS)

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

2013-01-01

Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of

Could new reconstruction CT techniques challenge MRI for the detection of brain metastases in the context of initial lung cancer staging?

Energy Technology Data Exchange (ETDEWEB)

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

2018-02-15

To evaluate the diagnostic performance of brain CT images reconstructed with a model-based iterative algorithm performed at usual and reduced dose. 115 patients with histologically proven lung cancer were prospectively included over 15 months. Patients underwent two CT acquisitions at the initial staging, performed on a 256-slice MDCT, at standard (CTDIvol: 41.4 mGy) and half dose (CTDIvol: 20.7 mGy). Both image datasets were reconstructed with filtered back projection (FBP) and iterative model-based reconstruction (IMR) algorithms. Brain MRI was considered as the reference. Two blinded independent readers analysed the images. Ninety-three patients underwent all examinations. At the standard dose, eight patients presented 17 and 15 lesions on IMR and FBP CT images, respectively. At half-dose, seven patients presented 15 and 13 lesions on IMR and FBP CT images, respectively. The test could not highlight any significant difference between the standard dose IMR and the half-dose FBP techniques (p-value = 0.12). MRI showed 46 metastases on 11 patients. Specificity, negative and positive predictive values were calculated (98.9-100 %, 93.6-94.6 %, 75-100 %, respectively, for all CT techniques). No significant difference could be demonstrated between the two CT reconstruction techniques. (orig.)

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

International Nuclear Information System (INIS)

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

1995-01-01

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

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)

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)

Limited angle CT reconstruction by simultaneous spatial and Radon domain regularization based on TV and data-driven tight frame

Science.gov (United States)

Zhang, Wenkun; Zhang, Hanming; Wang, Linyuan; Cai, Ailong; Li, Lei; Yan, Bin

2018-02-01

Limited angle computed tomography (CT) reconstruction is widely performed in medical diagnosis and industrial testing because of the size of objects, engine/armor inspection requirements, and limited scan flexibility. Limited angle reconstruction necessitates usage of optimization-based methods that utilize additional sparse priors. However, most of conventional methods solely exploit sparsity priors of spatial domains. When CT projection suffers from serious data deficiency or various noises, obtaining reconstruction images that meet the requirement of quality becomes difficult and challenging. To solve this problem, this paper developed an adaptive reconstruction method for limited angle CT problem. The proposed method simultaneously uses spatial and Radon domain regularization model based on total variation (TV) and data-driven tight frame. Data-driven tight frame being derived from wavelet transformation aims at exploiting sparsity priors of sinogram in Radon domain. Unlike existing works that utilize pre-constructed sparse transformation, the framelets of the data-driven regularization model can be adaptively learned from the latest projection data in the process of iterative reconstruction to provide optimal sparse approximations for given sinogram. At the same time, an effective alternating direction method is designed to solve the simultaneous spatial and Radon domain regularization model. The experiments for both simulation and real data demonstrate that the proposed algorithm shows better performance in artifacts depression and details preservation than the algorithms solely using regularization model of spatial domain. Quantitative evaluations for the results also indicate that the proposed algorithm applying learning strategy performs better than the dual domains algorithms without learning regularization model

An Efficient Augmented Lagrangian Method for Statistical X-Ray CT Image Reconstruction.

Science.gov (United States)

Li, Jiaojiao; Niu, Shanzhou; Huang, Jing; Bian, Zhaoying; Feng, Qianjin; Yu, Gaohang; Liang, Zhengrong; Chen, Wufan; Ma, Jianhua

2015-01-01

Statistical iterative reconstruction (SIR) for X-ray computed tomography (CT) under the penalized weighted least-squares criteria can yield significant gains over conventional analytical reconstruction from the noisy measurement. However, due to the nonlinear expression of the objective function, most exiting algorithms related to the SIR unavoidably suffer from heavy computation load and slow convergence rate, especially when an edge-preserving or sparsity-based penalty or regularization is incorporated. In this work, to address abovementioned issues of the general algorithms related to the SIR, we propose an adaptive nonmonotone alternating direction algorithm in the framework of augmented Lagrangian multiplier method, which is termed as "ALM-ANAD". The algorithm effectively combines an alternating direction technique with an adaptive nonmonotone line search to minimize the augmented Lagrangian function at each iteration. To evaluate the present ALM-ANAD algorithm, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present ALM-ANAD algorithm can achieve noticeable gains over the classical nonlinear conjugate gradient algorithm and state-of-the-art split Bregman algorithm in terms of noise reduction, contrast-to-noise ratio, convergence rate, and universal quality index metrics.

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

Science.gov (United States)

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

2017-07-01

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

Parallel statistical image reconstruction for cone-beam x-ray CT on a shared memory computation platform

International Nuclear Information System (INIS)

Kole, J S; Beekman, F J

2005-01-01

Statistical reconstruction methods offer possibilities of improving image quality as compared to analytical methods, but current reconstruction times prohibit routine clinical applications. To reduce reconstruction times we have parallelized a statistical reconstruction algorithm for cone-beam x-ray CT, the ordered subset convex algorithm (OSC), and evaluated it on a shared memory computer. Two different parallelization strategies were developed: one that employs parallelism by computing the work for all projections within a subset in parallel, and one that divides the total volume into parts and processes the work for each sub-volume in parallel. Both methods are used to reconstruct a three-dimensional mathematical phantom on two different grid densities. The reconstructed images are binary identical to the result of the serial (non-parallelized) algorithm. The speed-up factor equals approximately 30 when using 32 to 40 processors, and scales almost linearly with the number of cpus for both methods. The huge reduction in computation time allows us to apply statistical reconstruction to clinically relevant studies for the first time

A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods

International Nuclear Information System (INIS)

Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

2014-01-01

As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate O(1/k 2 ). In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques. (paper)

A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

Science.gov (United States)

Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

2014-06-21

As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

The combination of a reduction in contrast agent dose with low tube voltage and an adaptive statistical iterative reconstruction algorithm in CT enterography: Effects on image quality and radiation dose.

Science.gov (United States)

Feng, Cui; Zhu, Di; Zou, Xianlun; Li, Anqin; Hu, Xuemei; Li, Zhen; Hu, Daoyu

2018-03-01

To investigate the subjective and quantitative image quality and radiation exposure of CT enterography (CTE) examination performed at low tube voltage and low concentration of contrast agent with adaptive statistical iterative reconstruction (ASIR) algorithm, compared with conventional CTE.One hundred thirty-seven patients with suspected or proved gastrointestinal diseases underwent contrast enhanced CTE in a multidetector computed tomography (MDCT) scanner. All cases were assigned to 2 groups. Group A (n = 79) underwent CT with low tube voltage based on patient body mass index (BMI) (BMI contrast agent (270 mg I/mL), the images were reconstructed with standard filtered back projection (FBP) algorithm and 50% ASIR algorithm. Group B (n = 58) underwent conventional CTE with 120 kVp and 350 mg I/mL contrast agent, the images were reconstructed with FBP algorithm. The computed tomography dose index volume (CTDIvol), dose length product (DLP), effective dose (ED), and total iodine dosage were calculated and compared. The CT values, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) of the normal bowel wall, gastrointestinal lesions, and mesenteric vessels were assessed and compared. The subjective image quality was assessed independently and blindly by 2 radiologists using a 5-point Likert scale.The differences of values for CTDIvol (8.64 ± 2.72 vs 11.55 ± 3.95, P  .05) and all image quality scores were greater than or equal to 3 (moderate). Fifty percent ASIR-A group images provided lower image noise, but similar or higher quantitative image quality in comparison with FBP-B group images.Compared with the conventional protocol, CTE performed at low tube voltage, low concentration of contrast agent with 50% ASIR algorithm produce a diagnostically acceptable image quality with a mean ED of 6.34 mSv and a total iodine dose reduction of 26.1%.

Image quality in children with low-radiation chest CT using adaptive statistical iterative reconstruction and model-based iterative reconstruction.

Directory of Open Access Journals (Sweden)

Jihang Sun

Full Text Available OBJECTIVE: To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR and a full model-based iterative reconstruction (MBIR algorithm. METHODS: Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years who received low-dose chest CT scans were included. Age-dependent noise index (NI was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP, and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV, muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR was calculated. RESULT: In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP. CONCLUSION: Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.

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

Science.gov (United States)

Liu, Li; Lin, Weikai; Jin, Mingwu

2015-01-01

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

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.)

Coronary CT angiography: Comparison of a novel iterative reconstruction with filtered back projection for reconstruction of low-dose CT—Initial experience

International Nuclear Information System (INIS)

Takx, Richard A.P.; Schoepf, U. Joseph; Moscariello, Antonio; Das, Marco; Rowe, Garrett; Schoenberg, Stefan O.; Fink, Christian; Henzler, Thomas

2013-01-01

Objective: To prospectively compare subjective and objective image quality in 20% tube current coronary CT angiography (cCTA) datasets between an iterative reconstruction algorithm (SAFIRE) and traditional filtered back projection (FBP). Materials and methods: Twenty patients underwent a prospectively ECG-triggered dual-step cCTA protocol using 2nd generation dual-source CT (DSCT). CT raw data was reconstructed using standard FBP at full-dose (Group 1 a) and 80% tube current reduced low-dose (Group 1 b). The low-dose raw data was additionally reconstructed using iterative raw data reconstruction (Group 2 ). Attenuation and image noise were measured in three regions of interest and signal-to-noise-ratio (SNR) as well as contrast-to-noise-ratio (CNR) was calculated. Subjective diagnostic image quality was evaluated using a 4-point Likert scale. Results: Mean image noise of group 2 was lowered by 22% on average when compared to group 1 b (p 2 compared to group 1 b (p 2 (1.88 ± 0.63) was also rated significantly higher when compared to group 1 b (1.58 ± 0.63, p = 0.004). Conclusions: Image quality of 80% tube current reduced iteratively reconstructed cCTA raw data is significantly improved when compared to standard FBP and consequently may improve the diagnostic accuracy of cCTA

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

International Nuclear Information System (INIS)

Young, S; Lo, P; Hoffman, J; Wahi-Anwar, M; Brown, M; McNitt-Gray, M; Noo, F

2016-01-01

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT_wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

Energy Technology Data Exchange (ETDEWEB)

Young, S; Lo, P; Hoffman, J; Wahi-Anwar, M; Brown, M; McNitt-Gray, M [UCLA School of Medicine, Los Angeles, CA (United States); Noo, F [University of Utah, Salt Lake City, UT (United States)

2016-06-15

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modules in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range

Review article - An evaluation of SAFIRE's potential to reduce the dose received by paediatric patients undergoing CT: a narrative review : Iterative reconstruction in ct

NARCIS (Netherlands)

Buissink, Carst; Vallinga, Anique; Rook, Jan Willem; Sanderud, Audun; Vouillamoze, Audrey

2015-01-01

Introduction: The purpose of this review is to gather and analyse current research publications to evaluate Sinogram-Affirmed Iterative Reconstruction (SAFIRE). The aim of this review is to investigate whether this algorithm is capable of reducing the dose delivered during CT imaging while

The impact of CT radiation dose reduction and iterative reconstruction algorithms from four different vendors on coronary calcium scoring

Energy Technology Data Exchange (ETDEWEB)

Willemink, Martin J.; Takx, Richard A.P.; Jong, Pim A. de; Budde, Ricardo P.J.; Schilham, Arnold M.R.; Leiner, Tim [Utrecht University Medical Center, Department of Radiology, Utrecht (Netherlands); Bleys, Ronald L.A.W. [Utrecht University Medical Center, Department of Anatomy, Utrecht (Netherlands); Das, Marco; Wildberger, Joachim E. [Maastricht University Medical Center, Department of Radiology, Maastricht (Netherlands); Prokop, Mathias [Radboud University Nijmegen Medical Center, Department of Radiology, Nijmegen (Netherlands); Buls, Nico; Mey, Johan de [UZ Brussel, Department of Radiology, Brussels (Belgium)

2014-09-15

To analyse the effects of radiation dose reduction and iterative reconstruction (IR) algorithms on coronary calcium scoring (CCS). Fifteen ex vivo human hearts were examined in an anthropomorphic chest phantom using computed tomography (CT) systems from four vendors and examined at four dose levels using unenhanced prospectively ECG-triggered protocols. Tube voltage was 120 kV and tube current differed between protocols. CT data were reconstructed with filtered back projection (FBP) and reduced dose CT data with IR. CCS was quantified with Agatston scores, calcification mass and calcification volume. Differences were analysed with the Friedman test. Fourteen hearts showed coronary calcifications. Dose reduction with FBP did not significantly change Agatston scores, calcification volumes and calcification masses (P > 0.05). Maximum differences in Agatston scores were 76, 26, 51 and 161 units, in calcification volume 97, 27, 42 and 162 mm{sup 3}, and in calcification mass 23, 23, 20 and 48 mg, respectively. IR resulted in a trend towards lower Agatston scores and calcification volumes with significant differences for one vendor (P < 0.05). Median relative differences between reference FBP and reduced dose IR for Agatston scores remained within 2.0-4.6 %, 1.0-5.3 %, 1.2-7.7 % and 2.6-4.5 %, for calcification volumes within 2.4-3.9 %, 1.0-5.6 %, 1.1-6.4 % and 3.7-4.7 %, for calcification masses within 1.9-4.1 %, 0.9-7.8 %, 2.9-4.7 % and 2.5-3.9 %, respectively. IR resulted in increased, decreased or similar calcification masses. CCS derived from standard FBP acquisitions was not affected by radiation dose reductions up to 80 %. IR resulted in a trend towards lower Agatston scores and calcification volumes. (orig.)

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties

Science.gov (United States)

Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Asma, Evren; Kinahan, Paul E.

2015-01-01

Extremely low-dose CT acquisitions for the purpose of PET attenuation correction will have a high level of noise and biasing artifacts due to factors such as photon starvation. This work explores a priori knowledge appropriate for CT iterative image reconstruction for PET attenuation correction. We investigate the maximum a posteriori (MAP) framework with cluster-based, multinomial priors for the direct reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction was modeled as a Poisson log-likelihood with prior terms consisting of quadratic (Q) and mixture (M) distributions. The attenuation map is assumed to have values in 4 clusters: air+background, lung, soft tissue, and bone. Under this assumption, the MP was a mixture probability density function consisting of one exponential and three Gaussian distributions. The relative proportion of each cluster was jointly estimated during each voxel update of direct iterative coordinate decent (dICD) method. Noise-free data were generated from NCAT phantom and Poisson noise was added. Reconstruction with FBP (ramp filter) was performed on the noise-free (ground truth) and noisy data. For the noisy data, dICD reconstruction was performed with the combination of different prior strength parameters (β and γ) of Q- and M-penalties. The combined quadratic and mixture penalties reduces the RMSE by 18.7% compared to post-smoothed iterative reconstruction and only 0.7% compared to quadratic alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of quadratic and mixture priors offers regularization of both variance and bias and is a potential method to derive attenuation maps with negligible patient dose. However, the small improvement in quantitative accuracy relative to the substantial increase in algorithm complexity does not currently justify the use of mixture-based PET attenuation priors for reconstruction of CT

Low-dose CT image reconstruction using gain intervention-based dictionary learning

Science.gov (United States)

Pathak, Yadunath; Arya, K. V.; Tiwari, Shailendra

2018-05-01

Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.

Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

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

Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

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

Hybrid spectral CT reconstruction.

Directory of Open Access Journals (Sweden)

Darin P Clark

Full Text Available Current photon counting x-ray detector (PCD technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID. In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM. Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with

Hybrid spectral CT reconstruction

Science.gov (United States)

Clark, Darin P.

2017-01-01

Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral

Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

International Nuclear Information System (INIS)

Stassi, D.; Ma, H.; Schmidt, T. G.; Dutta, S.; Soderman, A.; Pazzani, D.; Gros, E.; Okerlund, D.

2016-01-01

Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three

Determination of optimal parameters for three-dimensional reconstruction images of central airways using helical CT

International Nuclear Information System (INIS)

Hirose, Takahumi; Akata, Soichi; Matsuno, Naoto; Nagao, Takeshi; Abe, Kimihiko

2002-01-01

Three-dimensional (3D) image reconstruction of central airways using helical CT requires several user-defined parameters that exceed the requirements of conventional CT. The purpose of this study was to evaluate the optimal parameters for 3D images of central airways using helical CT. In our experimental study using a piglet immediately after sacrifice, 3D images of the central airway were evaluated with changes of 3D imaging parameters, such as detector collimation (1, 2, 3 and 6 mm), table speed (1, 2, 3 and 5 mm/sec), tube electric current (50, 100, 150, 200 and 250 mA), reconstruction interval (0.3, 0.5, 1, 2 and 3 mm), algorithm (mediastinum and lung) and interpolation method (180 deg and 360 deg). To minimize detector collimation, table speed, and reconstruction interval could provide the best 3D images of the central airway. Stair-step artifacts could also be reduced with a slow table speed. However, decreasing the collimation and table speed decreases not only the effective section thickness but also the scan coverage that can be achieved with a helical CT. For routine diagnosis, we conclude that optimal parameters for 3D images of the central airway are to minimize the table speed necessary to cover the volume of interest and to set detector collimation to 1/2 of the table speed. The reconstruction intervals should also be selected at up to 1/2 of the detector collimation, but with trade-offs of increased image processing time, data storage requirements, and physician time for image review. Regarding to tube electric current, 200 mA or more was necessary. Pixel noise increased with the algorithm for the lung. The 180 deg interpolation is better than 360 deg interpolation due to thin effective section thickness. (author)

Three-dimensional fracture visualisation of multidetector CT of the skull base in trauma patients: comparison of three reconstruction algorithms

International Nuclear Information System (INIS)

Ringl, Helmut; Schernthaner, Ruediger; Philipp, Marcel O.; Metz-Schimmerl, Sylvia; Czerny, Christian; Weber, Michael; Steiner-Ringl, Andrea; Peloschek, Philipp; Herold, Christian J.; Schima, Wolfgang; Gaebler, Christian

2009-01-01

The purpose of this study was to retrospectively assess the detection rate of skull-base fractures for three different three-dimensional (3D) reconstruction methods of cranial CT examinations in trauma patients. A total of 130 cranial CT examinations of patients with previous head trauma were subjected to 3D reconstruction of the skull base, using solid (SVR) and transparent (TVR) volume-rendering technique and maximum intensity projection (MIP). Three radiologists independently evaluated all reconstructions as well as standard high-resolution multiplanar reformations (HR-MPRs). Mean fracture detection rates for all readers reading rotating reconstructions were 39, 36, 61 and 64% for SVR, TVR, MIP and HR-MPR respectively. Although not significantly different from HR-MPR with respect to sensitivity (P = 0.9), MIP visualised 18% of fractures that were not reported in HR-MPR. Because of the relatively low detection rate using HR-MPRs alone, we recommend reading MIP reconstructions in addition to the obligatory HR-MPRs to improve fracture detection. (orig.)

Cranial CT with adaptive statistical iterative reconstruction: improved image quality with concomitant radiation dose reduction.

Science.gov (United States)

Rapalino, O; Kamalian, Shervin; Kamalian, Shahmir; Payabvash, S; Souza, L C S; Zhang, D; Mukta, J; Sahani, D V; Lev, M H; Pomerantz, S R

2012-04-01

To safeguard patient health, there is great interest in CT radiation-dose reduction. The purpose of this study was to evaluate the impact of an iterative-reconstruction algorithm, ASIR, on image-quality measures in reduced-dose head CT scans for adult patients. Using a 64-section scanner, we analyzed 100 reduced-dose adult head CT scans at 6 predefined levels of ASIR blended with FBP reconstruction. These scans were compared with 50 CT scans previously obtained at a higher routine dose without ASIR reconstruction. SNR and CNR were computed from Hounsfield unit measurements of normal GM and WM of brain parenchyma. A blinded qualitative analysis was performed in 10 lower-dose CT datasets compared with higher-dose ones without ASIR. Phantom data analysis was also performed. Lower-dose scans without ASIR had significantly lower mean GM and WM SNR (P = .003) and similar GM-WM CNR values compared with higher routine-dose scans. However, at ASIR levels of 20%-40%, there was no statistically significant difference in SNR, and at ASIR levels of ≥60%, the SNR values of the reduced-dose scans were significantly higher (P ASIR levels of ≥40% (P ASIR levels ≥60% (P ASIR in adult head CT scans reduces image noise and increases low-contrast resolution, while allowing lower radiation doses without affecting spatial resolution.

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

International Nuclear Information System (INIS)

Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka

2014-01-01

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

Energy Technology Data Exchange (ETDEWEB)

Shieh, Chun-Chien [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006, Australia and Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia); Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J., E-mail: paul.keall@sydney.edu.au [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006 (Australia); Kuncic, Zdenka [Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia)

2014-04-15

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

Application of three-dimensional CT reconstruction cranioplasty

International Nuclear Information System (INIS)

Yan Shuli; Yun Yongxing; Wan Kunming; Qiu Jian

2011-01-01

Objective: To study the application of three-dimensional CT reconstruction in cranioplasty. Methods: 46 patients with skull defect were divided into two group. One group underwent CT examination and three-dimensional reconstruction, and then the Titanium nets production company manufactured corresponding titanium meshes were shaped those data before the operation. The other group received traditional operation in which titanium meshes were shaped during operation. The average time of operation were compared. Results: The average time of operation of the first group is 86.6±13.6 mins, and that of the second group is 115±15.0 mins. The difference of average operation time between the two groups was statistically significant. Conclusion: Three-dimensional CT reconstruction techniques contribute to shorten the average operation time, reduce the intensity of neurosurgeon's work and the patien's risk. (authors)

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)

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

International Nuclear Information System (INIS)

Guo, Yumeng; Zeng, Li

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-01-11

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

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

International Nuclear Information System (INIS)

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

2005-01-01

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

CT and MRI post-processing reconstructions in maxillo-facial trauma

International Nuclear Information System (INIS)

Olszycki, M.; Grzelak, P.; Stanczyk, L.; Kozakiewicz, M.; Arkuszewski, P.

2004-01-01

The aim of the study is to evaluate the reliability of CT and MR imaging and their post-processing reconstructions in the cases of facial trauma. CT studies were performed in 34 patients: 13 suspected of sinus fractures, 20 with orbital fractures and 1 with broken supraorbital bone fragment. MR imaging was also performed in 16 of these patients. The CT data were reconstructed in the 2D and 3D mode. The CT and MR images were digitally fused using an own program. The CT and MR images, their reconstructions and their fusion were evaluated according to the quality of visualization of a pathological lesions. Surgery was the method of reference. The reconstructed CT images allowed to recognize properly maxillary-oral fenestration in 5 cases. In 20 patients with orbital fracture, CT 3D reformations visualized well the morphology of the fissure. In 13 of these patients,the small bone fragments and orbital soft tissues prolapsed towards the maxillary sinus were depicted. Among the 16 patients who underwent MR examination, in 6 cases we revealed dislocation of the inferior rectus muscle towards the sinus, whereas in 9 cases MR images clearly excluded this pathology. In 1 patient, the digitally fused CT/MR images allowed to determine the actual position of small bone fragment within the muscle. In 1 patient with broken supraorbital bone fragment, evaluation of the 3D model allowed to exclude communication with intracranial space. In the next 8 patients with maxillo-zygomatic injures, the CT reconstructions did not support the diagnosis. The surgery correlated well with the post-processing CT and CT/MR fused images, contrary to the original CT ones which often were diagnostically insufficient. Spiral CT 2D and 3D-reconstructed images of the face allow to depict clearly the anatomical spatial relationships and the position, course and displacement of fractured fragments; thus, they support the surgery. The MR images of these patients reveal soft tissues clearly. The digital

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)

SU-E-I-45: Reconstruction of CT Images From Sparsely-Sampled Data Using the Logarithmic Barrier Method

International Nuclear Information System (INIS)

Xu, H

2014-01-01

Purpose: To develop and investigate whether the logarithmic barrier (LB) method can result in high-quality reconstructed CT images using sparsely-sampled noisy projection data Methods: The objective function is typically formulated as the sum of the total variation (TV) and a data fidelity (DF) term with a parameter λ that governs the relative weight between them. Finding the optimized value of λ is a critical step for this approach to give satisfactory results. The proposed LB method avoid using λ by constructing the objective function as the sum of the TV and a log function whose augment is the DF term. Newton's method was used to solve the optimization problem. The algorithm was coded in MatLab2013b. Both Shepp-Logan phantom and a patient lung CT image were used for demonstration of the algorithm. Measured data were simulated by calculating the projection data using radon transform. A Poisson noise model was used to account for the simulated detector noise. The iteration stopped when the difference of the current TV and the previous one was less than 1%. Results: Shepp-Logan phantom reconstruction study shows that filtered back-projection (FBP) gives high streak artifacts for 30 and 40 projections. Although visually the streak artifacts are less pronounced for 64 and 90 projections in FBP, the 1D pixel profiles indicate that FBP gives noisier reconstructed pixel values than LB does. A lung image reconstruction is presented. It shows that use of 64 projections gives satisfactory reconstructed image quality with regard to noise suppression and sharp edge preservation. Conclusion: This study demonstrates that the logarithmic barrier method can be used to reconstruct CT images from sparsely-amped data. The number of projections around 64 gives a balance between the over-smoothing of the sharp demarcation and noise suppression. Future study may extend to CBCT reconstruction and improvement on computation speed

Three-dimensional monochromatic x-ray CT

Science.gov (United States)

Saito, Tsuneo; Kudo, Hiroyuki; Takeda, Tohoru; Itai, Yuji; Tokumori, Kenji; Toyofuku, Fukai; Hyodo, Kazuyuki; Ando, Masami; Nishimura, Ktsuyuki; Uyama, Chikao

1995-08-01

In this paper, we describe a 3D computed tomography (3D CT) using monochromatic x-rays generated by synchrotron radiation, which performs a direct reconstruction of 3D volume image of an object from its cone-beam projections. For the develpment of 3D CT, scanning orbit of x-ray source to obtain complete 3D information about an object and corresponding 3D image reconstruction algorithm are considered. Computer simulation studies demonstrate the validities of proposed scanning method and reconstruction algorithm. A prototype experimental system of 3D CT was constructed. Basic phantom examinations and specific material CT image by energy subtraction obtained in this experimental system are shown.

Impact of iterative reconstruction on CT coronary calcium quantification

DEFF Research Database (Denmark)

Kurata, Akira; Dharampal, Anoeshka; Dedic, Admir

2013-01-01

We evaluated the influence of sinogram-affirmed iterative reconstruction (SAFIRE) on the coronary artery calcium (CAC) score by computed tomography (CT).......We evaluated the influence of sinogram-affirmed iterative reconstruction (SAFIRE) on the coronary artery calcium (CAC) score by computed tomography (CT)....

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Science.gov (United States)

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

2010-04-01

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

A GREIT-type linear reconstruction algorithm for EIT using eigenimages

International Nuclear Information System (INIS)

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

2013-01-01

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

Effect of Scanning and Reconstruction Parameters on Three Dimensional Volume and CT Value Measurement of Pulmonary Nodules: A Phantom Study

Directory of Open Access Journals (Sweden)

Datong SU

2017-08-01

Full Text Available Background and objective The computed tomography (CT follow-up of indeterminate pulmonary nodules aiming to evaluate the change of the volume and CT value is the common strategy in clinic. The CT dose needs to considered on serious CT scans in addition to the measurement accuracy. The purpose of this study is to quantify the precision of pulmonary nodule volumetric measurement and CT value measurement with various tube currents and reconstruction algorithms in a phantom study with dual-energy CT. Methods A chest phantom containing 9 artificial spherical solid nodules with known diameter (D=2.5 mm, 5 mm, 10 mm and density (-100 HU, 60 HU and 100 HU was scanned using a 64-row detector CT canner at 120 Kilovolt & various currents (10 mA, 20 mA, 50 mA, 80 mA,100 mA, 150 mA and 350 mA. Raw data were reconstructed with filtered back projection and three levels of adaptive statistical iterative reconstruction algorithm (FBP, ASIR; 30%, 50% and 80%. Automatic volumetric measurements were performed using commercially available software. The relative volume error (RVE and the absolute attenuation error (AAE between the software measures and the reference-standard were calculated. Analyses of the variance were performed to evaluate the effect of reconstruction methods, different scan parameters, nodule size and attenuation on the RPE. Results The software substantially overestimated the very small (D=2.5 mm nodule's volume [mean RVE: (100.8%±28%] and underestimated it attenuation [mean AAE: (-756±80 HU]. The mean RVEs of nodule with diameter as 5 mm and 10 mm were small [(-0.9%±1.1% vs (0.9%±1.4%], however, the mean AAEs [(-243±26 HU vs (-129±7 HU] were large. The ANOVA analysis for repeated measurements showed that different tube current and reconstruction algorithm had no significant effect on the volumetric measurements for nodules with diameter of 5 mm and 10 mm (F=5.60, P=0.10 vs F=11.13, P=0.08, but significant effects on the measurement of CT

Impact of respiratory-correlated CT sorting algorithms on the choice of margin definition for free-breathing lung radiotherapy treatments.

Science.gov (United States)

Thengumpallil, Sheeba; Germond, Jean-François; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

2016-06-01

To investigate the impact of Toshiba phase- and amplitude-sorting algorithms on the margin strategies for free-breathing lung radiotherapy treatments in the presence of breathing variations. 4D CT of a sphere inside a dynamic thorax phantom was acquired. The 4D CT was reconstructed according to the phase- and amplitude-sorting algorithms. The phantom was moved by reproducing amplitude, frequency, and a mix of amplitude and frequency variations. Artefact analysis was performed for Mid-Ventilation and ITV-based strategies on the images reconstructed by phase- and amplitude-sorting algorithms. The target volume deviation was assessed by comparing the target volume acquired during irregular motion to the volume acquired during regular motion. The amplitude-sorting algorithm shows reduced artefacts for only amplitude variations while the phase-sorting algorithm for only frequency variations. For amplitude and frequency variations, both algorithms perform similarly. Most of the artefacts are blurring and incomplete structures. We found larger artefacts and volume differences for the Mid-Ventilation with respect to the ITV strategy, resulting in a higher relative difference of the surface distortion value which ranges between maximum 14.6% and minimum 4.1%. The amplitude- is superior to the phase-sorting algorithm in the reduction of motion artefacts for amplitude variations while phase-sorting for frequency variations. A proper choice of 4D CT sorting algorithm is important in order to reduce motion artefacts, especially if Mid-Ventilation strategy is used. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Emergency assessment of patients with acute abdominal pain using low-dose CT with iterative reconstruction: a comparative study

Energy Technology Data Exchange (ETDEWEB)

Poletti, Pierre-Alexandre; Becker, Minerva; Becker, Christoph D.; Zaidi, Habib; Platon, Alexandra [University Hospital of Geneva, Department of Radiology, Geneva (Switzerland); Halfon Poletti, Alice; Rutschmann, Olivier T. [University Hospital of Geneva, Department of Community, Primary Care and Emergency Medicine, Geneva (Switzerland); Perneger, Thomas [University Hospital of Geneva, Division of Clinical Epidemiology, Geneva (Switzerland)

2017-08-15

To determine if radiation dose delivered by contrast-enhanced CT (CECT) for acute abdominal pain can be reduced to the dose administered in abdominal radiography (<2.5 mSv) using low-dose CT (LDCT) with iterative reconstruction algorithms. One hundred and fifty-one consecutive patients requiring CECT for acute abdominal pain were included, and their body mass index (BMI) was calculated. CECT was immediately followed by LDCT. LDCT series was processed using 1) 40% iterative reconstruction algorithm blended with filtered back projection (LDCT-IR-FBP) and 2) model-based iterative reconstruction algorithm (LDCT-MBIR). LDCT-IR-FBP and LDCT-MBIR images were reviewed independently by two board-certified radiologists (Raters 1 and 2). Abdominal pathology was revealed on CECT in 120 (79%) patients. In those with BMI <30, accuracies for correct diagnosis by Rater 1 with LDCT-IR-FBP and LDCT-MBIR, when compared to CECT, were 95.4% (104/109) and 99% (108/109), respectively, and 92.7% (101/109) and 100% (109/109) for Rater 2. In patients with BMI ≥30, accuracies with LDCT-IR-FBP and LDCT-MBIR were 88.1% (37/42) and 90.5% (38/42) for Rater 1 and 78.6% (33/42) and 92.9% (39/42) for Rater 2. The radiation dose delivered by CT to non-obese patients with acute abdominal pain can be safely reduced to levels close to standard radiography using LDCT-MBIR. (orig.)

Comparison of adaptive statistical iterative reconstruction (ASiRTM) and model-based iterative reconstruction (VeoTM) for paediatric abdominal CT examinations: an observer performance study of diagnostic image quality

International Nuclear Information System (INIS)

Hultenmo, Maria; Caisander, Haakan; Mack, Karsten; Thilander-Klang, Anne

2016-01-01

The diagnostic image quality of 75 paediatric abdominal computed tomography (CT) examinations reconstructed with two different iterative reconstruction (IR) algorithms-adaptive statistical IR (ASiR TM ) and model-based IR (Veo TM )-was compared. Axial and coronal images were reconstructed with 70 % ASiR with the Soft TM convolution kernel and with the Veo algorithm. The thickness of the reconstructed images was 2.5 or 5 mm depending on the scanning protocol used. Four radiologists graded the delineation of six abdominal structures and the diagnostic usefulness of the image quality. The Veo reconstruction significantly improved the visibility of most of the structures compared with ASiR in all subgroups of images. For coronal images, the Veo reconstruction resulted in significantly improved ratings of the diagnostic use of the image quality compared with the ASiR reconstruction. This was not seen for the axial images. The greatest improvement using Veo reconstruction was observed for the 2.5 mm coronal slices. (authors)

Improved image quality with simultaneously reduced radiation exposure: Knowledge-based iterative model reconstruction algorithms for coronary CT angiography in a clinical setting.

Science.gov (United States)

André, Florian; Fortner, Philipp; Vembar, Mani; Mueller, Dirk; Stiller, Wolfram; Buss, Sebastian J; Kauczor, Hans-Ulrich; Katus, Hugo A; Korosoglou, Grigorios

The aim of this study was to assess the potential for radiation dose reduction using knowledge-based iterative model reconstruction (K-IMR) algorithms in combination with ultra-low dose body mass index (BMI)-adapted protocols in coronary CT angiography (coronary CTA). Forty patients undergoing clinically indicated coronary CTA were randomly assigned to two groups with BMI-adapted (I: quality was significantly better in the ULD group using K-IMR CR 1 compared to FBP, iD 2 and iD 5 in the LD group, resulting in fewer non-diagnostic coronary segments (2.4% vs. 11.6%, 9.2% and 6.1%; p quality compared to LD protocols with FBP or hybrid iterative algorithms. Therefore, K-IMR allows for coronary CTA examinations with high diagnostic value and very low radiation exposure in clinical routine. Copyright © 2017 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Assessment of noise reduction potential and image quality improvement of a new generation adaptive statistical iterative reconstruction (ASIR-V) in chest CT.

Science.gov (United States)

Tang, Hui; Yu, Nan; Jia, Yongjun; Yu, Yong; Duan, Haifeng; Han, Dong; Ma, Guangming; Ren, Chenglong; He, Taiping

2018-01-01

To evaluate the image quality improvement and noise reduction in routine dose, non-enhanced chest CT imaging by using a new generation adaptive statistical iterative reconstruction (ASIR-V) in comparison with ASIR algorithm. 30 patients who underwent routine dose, non-enhanced chest CT using GE Discovery CT750HU (GE Healthcare, Waukesha, WI) were included. The scan parameters included tube voltage of 120 kVp, automatic tube current modulation to obtain a noise index of 14HU, rotation speed of 0.6 s, pitch of 1.375:1 and slice thickness of 5 mm. After scanning, all scans were reconstructed with the recommended level of 40%ASIR for comparison purpose and different percentages of ASIR-V from 10% to 100% in a 10% increment. The CT attenuation values and SD of the subcutaneous fat, back muscle and descending aorta were measured at the level of tracheal carina of all reconstructed images. The signal-to-noise ratio (SNR) was calculated with SD representing image noise. The subjective image quality was independently evaluated by two experienced radiologists. For all ASIR-V images, the objective image noise (SD) of fat, muscle and aorta decreased and SNR increased along with increasing ASIR-V percentage. The SD of 30% ASIR-V to 100% ASIR-V was significantly lower than that of 40% ASIR (p ASIR-V reconstructions had good diagnostic acceptability. However, the 50% ASIR-V to 70% ASIR-V series showed significantly superior visibility of small structures when compared with the 40% ASIR and ASIR-V of other percentages (p ASIR-V was the best series of all ASIR-V images, with a highest subjective image quality. The image sharpness was significantly decreased in images reconstructed by 80% ASIR-V and higher. In routine dose, non-enhanced chest CT, ASIR-V shows greater potential in reducing image noise and artefacts and maintaining image sharpness when compared to the recommended level of 40%ASIR algorithm. Combining both the objective and subjective evaluation of images, non

Split-Bregman-based sparse-view CT reconstruction

Energy Technology Data Exchange (ETDEWEB)

Vandeghinste, Bert; Vandenberghe, Stefaan [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Goossens, Bart; Pizurica, Aleksandra; Philips, Wilfried [Ghent Univ. (Belgium). Image Processing and Interpretation Research Group (IPI); Beenhouwer, Jan de [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Wilrijk (Belgium). The Vision Lab; Staelens, Steven [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Edegem (Belgium). Molecular Imaging Centre Antwerp

2011-07-01

Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied to more complex images. It could thus be beneficial to use other regularizers within medical imaging. We propose a general regularization method, based on a split-Bregman approach. We show results for this framework combined with a total variation denoising operator, in comparison to ASD-POCS. We show that sparse-view reconstruction and noise regularization is possible. This general method will allow us to investigate other regularizers in the context of regularized CT reconstruction, and decrease the acquisition times in {mu}CT. (orig.)

Coronary artery plaques: Cardiac CT with model-based and adaptive-statistical iterative reconstruction technique

International Nuclear Information System (INIS)

Scheffel, Hans; Stolzmann, Paul; Schlett, Christopher L.; Engel, Leif-Christopher; Major, Gyöngi Petra; Károlyi, Mihály; Do, Synho; Maurovich-Horvat, Pál; Hoffmann, Udo

2012-01-01

Objectives: To compare image quality of coronary artery plaque visualization at CT angiography with images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model based iterative reconstruction (MBIR) techniques. Methods: The coronary arteries of three ex vivo human hearts were imaged by CT and reconstructed with FBP, ASIR and MBIR. Coronary cross-sectional images were co-registered between the different reconstruction techniques and assessed for qualitative and quantitative image quality parameters. Readers were blinded to the reconstruction algorithm. Results: A total of 375 triplets of coronary cross-sectional images were co-registered. Using MBIR, 26% of the images were rated as having excellent overall image quality, which was significantly better as compared to ASIR and FBP (4% and 13%, respectively, all p < 0.001). Qualitative assessment of image noise demonstrated a noise reduction by using ASIR as compared to FBP (p < 0.01) and further noise reduction by using MBIR (p < 0.001). The contrast-to-noise-ratio (CNR) using MBIR was better as compared to ASIR and FBP (44 ± 19, 29 ± 15, 26 ± 9, respectively; all p < 0.001). Conclusions: Using MBIR improved image quality, reduced image noise and increased CNR as compared to the other available reconstruction techniques. This may further improve the visualization of coronary artery plaque and allow radiation reduction.

Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

International Nuclear Information System (INIS)

Wang, Jing; Gu, Xuejun

2013-01-01

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstruction to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion

Color-coded volume rendering for three-dimensional reconstructions of CT data

International Nuclear Information System (INIS)

Rieker, O.; Mildenberger, P.; Thelen, M.

1999-01-01

Purpose: To evaluate a technique of colored three-dimensional reconstructions without segmentation. Material and methods: Color-coded volume rendered images were reconstructed from the volume data of 25 thoracic, abdominal, musculoskeletal, and vascular helical CT scans using commercial software. The CT volume rendered voxels were encoded with color in the following manner. Opacity, hue, lightness, and chroma were assigned to each of four classes defined by CT number. Color-coded reconstructions were compared to the corresponding grey-scale coded reconstructions. Results: Color-coded volume rendering enabled realistic visualization of pathologic findings when there was sufficient difference in CT density. Segmentation was necessary in some cases to demonstrate small details in a complex volume. Conclusion: Color-coded volume rendering allowed lifelike visualisation of CT volumes without the need of segmentation in most cases. (orig.) [de

SU-F-I-49: Vendor-Independent, Model-Based Iterative Reconstruction On a Rotating Grid with Coordinate-Descent Optimization for CT Imaging Investigations

International Nuclear Information System (INIS)

Young, S; Hoffman, J; McNitt-Gray, M; Noo, F

2016-01-01

Purpose: Iterative reconstruction methods show promise for improving image quality and lowering the dose in helical CT. We aim to develop a novel model-based reconstruction method that offers potential for dose reduction with reasonable computation speed and storage requirements for vendor-independent reconstruction from clinical data on a normal desktop computer. Methods: In 2012, Xu proposed reconstructing on rotating slices to exploit helical symmetry and reduce the storage requirements for the CT system matrix. Inspired by this concept, we have developed a novel reconstruction method incorporating the stored-system-matrix approach together with iterative coordinate-descent (ICD) optimization. A penalized-least-squares objective function with a quadratic penalty term is solved analytically voxel-by-voxel, sequentially iterating along the axial direction first, followed by the transaxial direction. 8 in-plane (transaxial) neighbors are used for the ICD algorithm. The forward problem is modeled via a unique approach that combines the principle of Joseph’s method with trilinear B-spline interpolation to enable accurate reconstruction with low storage requirements. Iterations are accelerated with multi-CPU OpenMP libraries. For preliminary evaluations, we reconstructed (1) a simulated 3D ellipse phantom and (2) an ACR accreditation phantom dataset exported from a clinical scanner (Definition AS, Siemens Healthcare). Image quality was evaluated in the resolution module. Results: Image quality was excellent for the ellipse phantom. For the ACR phantom, image quality was comparable to clinical reconstructions and reconstructions using open-source FreeCT-wFBP software. Also, we did not observe any deleterious impact associated with the utilization of rotating slices. The system matrix storage requirement was only 4.5GB, and reconstruction time was 50 seconds per iteration. Conclusion: Our reconstruction method shows potential for furthering research in low

SU-F-I-49: Vendor-Independent, Model-Based Iterative Reconstruction On a Rotating Grid with Coordinate-Descent Optimization for CT Imaging Investigations

Energy Technology Data Exchange (ETDEWEB)

Young, S; Hoffman, J; McNitt-Gray, M [UCLA School of Medicine, Los Angeles, CA (United States); Noo, F [University of Utah, Salt Lake City, UT (United States)

2016-06-15

Purpose: Iterative reconstruction methods show promise for improving image quality and lowering the dose in helical CT. We aim to develop a novel model-based reconstruction method that offers potential for dose reduction with reasonable computation speed and storage requirements for vendor-independent reconstruction from clinical data on a normal desktop computer. Methods: In 2012, Xu proposed reconstructing on rotating slices to exploit helical symmetry and reduce the storage requirements for the CT system matrix. Inspired by this concept, we have developed a novel reconstruction method incorporating the stored-system-matrix approach together with iterative coordinate-descent (ICD) optimization. A penalized-least-squares objective function with a quadratic penalty term is solved analytically voxel-by-voxel, sequentially iterating along the axial direction first, followed by the transaxial direction. 8 in-plane (transaxial) neighbors are used for the ICD algorithm. The forward problem is modeled via a unique approach that combines the principle of Joseph’s method with trilinear B-spline interpolation to enable accurate reconstruction with low storage requirements. Iterations are accelerated with multi-CPU OpenMP libraries. For preliminary evaluations, we reconstructed (1) a simulated 3D ellipse phantom and (2) an ACR accreditation phantom dataset exported from a clinical scanner (Definition AS, Siemens Healthcare). Image quality was evaluated in the resolution module. Results: Image quality was excellent for the ellipse phantom. For the ACR phantom, image quality was comparable to clinical reconstructions and reconstructions using open-source FreeCT-wFBP software. Also, we did not observe any deleterious impact associated with the utilization of rotating slices. The system matrix storage requirement was only 4.5GB, and reconstruction time was 50 seconds per iteration. Conclusion: Our reconstruction method shows potential for furthering research in low

Single-slice rebinning method for helical cone-beam CT

International Nuclear Information System (INIS)

Noo, F.; Defrise, M.; Clackdoyle, R.

1999-01-01

In this paper, we present reconstruction results from helical cone-beam CT data, obtained using a simple and fast algorithm, which we call the CB-SSRB algorithm. This algorithm combines the single-slice rebinning method of PET imaging with the weighting schemes of spiral CT algorithms. The reconstruction is approximate but can be performed using 2D multislice fan-beam filtered backprojection. The quality of the results is surprisingly good, and far exceeds what one might expect, even when the pitch of the helix is large. In particular, with this algorithm comparable quality is obtained using helical cone-beam data with a normalized pitch of 10 to that obtained using standard spiral CT reconstruction with a normalized pitch of 2. (author)

DQS advisor: a visual interface and knowledge-based system to balance dose, quality, and reconstruction speed in iterative CT reconstruction with application to NLM-regularization

International Nuclear Information System (INIS)

Zheng, Z; Papenhausen, E; Mueller, K

2013-01-01

Motivated by growing concerns with regards to the x-ray dose delivered to the patient, low-dose computed tomography (CT) has gained substantial interest in recent years. However, achieving high-quality CT reconstructions from the limited projection data collected at reduced x-ray radiation is challenging, and iterative algorithms have been shown to perform much better than conventional analytical schemes in these cases. A problem with iterative methods in general is that they require users to set many parameters, and if set incorrectly high reconstruction time and/or low image quality are likely consequences. Since the interactions among parameters can be complex and thus effective settings can be difficult to identify for a given scanning scenario, these choices are often left to a highly-experienced human expert. To help alleviate this problem, we devise a computer-based assistant for this purpose, called dose, quality and speed (DQS)-advisor. It allows users to balance the three most important CT metrics–-DQS-–by ways of an intuitive visual interface. Using a known gold-standard, the system uses the ant-colony optimization algorithm to generate the most effective parameter settings for a comprehensive set of DQS configurations. A visual interface then presents the numerical outcome of this optimization, while a matrix display allows users to compare the corresponding images. The interface allows users to intuitively trade-off GPU-enabled reconstruction speed with quality and dose, while the system picks the associated parameter settings automatically. Further, once the knowledge has been generated, it can be used to correctly set the parameters for any new CT scan taken at similar scenarios. (paper)

Motion-compensated PET image reconstruction with respiratory-matched attenuation correction using two low-dose inhale and exhale CT images

International Nuclear Information System (INIS)

Nam, Woo Hyun; Ahn, Il Jun; Ra, Jong Beom; Kim, Kyeong Min; Kim, Byung Il

2013-01-01

Positron emission tomography (PET) is widely used for diagnosis and follow up assessment of radiotherapy. However, thoracic and abdominal PET suffers from false staging and incorrect quantification of the radioactive uptake of lesion(s) due to respiratory motion. Furthermore, respiratory motion-induced mismatch between a computed tomography (CT) attenuation map and PET data often leads to significant artifacts in the reconstructed PET image. To solve these problems, we propose a unified framework for respiratory-matched attenuation correction and motion compensation of respiratory-gated PET. For the attenuation correction, the proposed algorithm manipulates a 4D CT image virtually generated from two low-dose inhale and exhale CT images, rather than a real 4D CT image which significantly increases the radiation burden on a patient. It also utilizes CT-driven motion fields for motion compensation. To realize the proposed algorithm, we propose an improved region-based approach for non-rigid registration between body CT images, and we suggest a selection scheme of 3D CT images that are respiratory-matched to each respiratory-gated sinogram. In this work, the proposed algorithm was evaluated qualitatively and quantitatively by using patient datasets including lung and/or liver lesion(s). Experimental results show that the method can provide much clearer organ boundaries and more accurate lesion information than existing algorithms by utilizing two low-dose CT images. (paper)

Model-based iterative reconstruction for reduction of radiation dose in abdominopelvic CT: comparison to adaptive statistical iterative reconstruction.

Science.gov (United States)

Yasaka, Koichiro; Katsura, Masaki; Akahane, Masaaki; Sato, Jiro; Matsuda, Izuru; Ohtomo, Kuni

2013-12-01

To evaluate dose reduction and image quality of abdominopelvic computed tomography (CT) reconstructed with model-based iterative reconstruction (MBIR) compared to adaptive statistical iterative reconstruction (ASIR). In this prospective study, 85 patients underwent referential-, low-, and ultralow-dose unenhanced abdominopelvic CT. Images were reconstructed with ASIR for low-dose (L-ASIR) and ultralow-dose CT (UL-ASIR), and with MBIR for ultralow-dose CT (UL-MBIR). Image noise was measured in the abdominal aorta and iliopsoas muscle. Subjective image analyses and a lesion detection study (adrenal nodules) were conducted by two blinded radiologists. A reference standard was established by a consensus panel of two different radiologists using referential-dose CT reconstructed with filtered back projection. Compared to low-dose CT, there was a 63% decrease in dose-length product with ultralow-dose CT. UL-MBIR had significantly lower image noise than L-ASIR and UL-ASIR (all pASIR and UL-ASIR (all pASIR in diagnostic acceptability (p>0.65), or diagnostic performance for adrenal nodules (p>0.87). MBIR significantly improves image noise and streak artifacts compared to ASIR, and can achieve radiation dose reduction without severely compromising image quality.

Model-based Iterative Reconstruction: Effect on Patient Radiation Dose and Image Quality in Pediatric Body CT

Science.gov (United States)

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

CT of the chest with model-based, fully iterative reconstruction: comparison with adaptive statistical iterative reconstruction.

Science.gov (United States)

Ichikawa, Yasutaka; Kitagawa, Kakuya; Nagasawa, Naoki; Murashima, Shuichi; Sakuma, Hajime

2013-08-09

The recently developed model-based iterative reconstruction (MBIR) enables significant reduction of image noise and artifacts, compared with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP). The purpose of this study was to evaluate lesion detectability of low-dose chest computed tomography (CT) with MBIR in comparison with ASIR and FBP. Chest CT was acquired with 64-slice CT (Discovery CT750HD) with standard-dose (5.7 ± 2.3 mSv) and low-dose (1.6 ± 0.8 mSv) conditions in 55 patients (aged 72 ± 7 years) who were suspected of lung disease on chest radiograms. Low-dose CT images were reconstructed with MBIR, ASIR 50% and FBP, and standard-dose CT images were reconstructed with FBP, using a reconstructed slice thickness of 0.625 mm. Two observers evaluated the image quality of abnormal lung and mediastinal structures on a 5-point scale (Score 5 = excellent and score 1 = non-diagnostic). The objective image noise was also measured as the standard deviation of CT intensity in the descending aorta. The image quality score of enlarged mediastinal lymph nodes on low-dose MBIR CT (4.7 ± 0.5) was significantly improved in comparison with low-dose FBP and ASIR CT (3.0 ± 0.5, p = 0.004; 4.0 ± 0.5, p = 0.02, respectively), and was nearly identical to the score of standard-dose FBP image (4.8 ± 0.4, p = 0.66). Concerning decreased lung attenuation (bulla, emphysema, or cyst), the image quality score on low-dose MBIR CT (4.9 ± 0.2) was slightly better compared to low-dose FBP and ASIR CT (4.5 ± 0.6, p = 0.01; 4.6 ± 0.5, p = 0.01, respectively). There were no significant differences in image quality scores of visualization of consolidation or mass, ground-glass attenuation, or reticular opacity among low- and standard-dose CT series. Image noise with low-dose MBIR CT (11.6 ± 1.0 Hounsfield units (HU)) were significantly lower than with low-dose ASIR (21.1 ± 2.6 HU, p standard-dose FBP CT (16.6 ± 2.3 HU, p 70%, MBIR can provide

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

MO-DE-207A-07: Filtered Iterative Reconstruction (FIR) Via Proximal Forward-Backward Splitting: A Synergy of Analytical and Iterative Reconstruction Method for CT

International Nuclear Information System (INIS)

Gao, H

2016-01-01

Purpose: This work is to develop a general framework, namely filtered iterative reconstruction (FIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality. Methods: FIR is formulated as a combination of filtered data fidelity and sparsity regularization, and then solved by proximal forward-backward splitting (PFBS) algorithm. As a result, the image reconstruction decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is in turn weighted together with previous image iterate to form next image iterate. Since the eigenvalues of AR-projection operator are close to the unity, PFBS based FIR has a fast convergence. Results: The proposed FIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts. Conclusion: FIR is proposed to incorporate AR into IR, with an efficient image reconstruction algorithm based on PFBS. The CBCT results suggest that FIR synergizes AR and IR with improved image quality and reduced axial and half-fan artifacts. The authors was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000), and the Shanghai Pujiang Talent Program (#14PJ1404500).

UV Reconstruction Algorithm And Diurnal Cycle Variability

Science.gov (United States)

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

2009-03-01

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

Diagnostic Performance of an Advanced Modeled Iterative Reconstruction Algorithm for Low-Contrast Detectability with a Third-Generation Dual-Source Multidetector CT Scanner: Potential for Radiation Dose Reduction in a Multireader Study.

Science.gov (United States)

Solomon, Justin; Mileto, Achille; Ramirez-Giraldo, Juan Carlos; Samei, Ehsan

2015-06-01

To assess the effect of radiation dose reduction on low-contrast detectability by using an advanced modeled iterative reconstruction (ADMIRE; Siemens Healthcare, Forchheim, Germany) algorithm in a contrast-detail phantom with a third-generation dual-source multidetector computed tomography (CT) scanner. A proprietary phantom with a range of low-contrast cylindrical objects, representing five contrast levels (range, 5-20 HU) and three sizes (range, 2-6 mm) was fabricated with a three-dimensional printer and imaged with a third-generation dual-source CT scanner at various radiation dose index levels (range, 0.74-5.8 mGy). Image data sets were reconstructed by using different section thicknesses (range, 0.6-5.0 mm) and reconstruction algorithms (filtered back projection [FBP] and ADMIRE with a strength range of three to five). Eleven independent readers blinded to technique and reconstruction method assessed all data sets in two reading sessions by measuring detection accuracy with a two-alternative forced choice approach (first session) and by scoring the total number of visible object groups (second session). Dose reduction potentials based on both reading sessions were estimated. Results between FBP and ADMIRE were compared by using both paired t tests and analysis of variance tests at the 95% significance level. During the first session, detection accuracy increased with increasing contrast, size, and dose index (diagnostic accuracy range, 50%-87%; interobserver variability, ±7%). When compared with FBP, ADMIRE improved detection accuracy by 5.2% on average across the investigated variables (P material is available for this article. RSNA, 2015

SU-E-I-45: Reconstruction of CT Images From Sparsely-Sampled Data Using the Logarithmic Barrier Method

Energy Technology Data Exchange (ETDEWEB)

Xu, H [Department of Radiation Oncology, Dalhousie University, Halifax, NS (Canada)

2014-06-01

Purpose: To develop and investigate whether the logarithmic barrier (LB) method can result in high-quality reconstructed CT images using sparsely-sampled noisy projection data Methods: The objective function is typically formulated as the sum of the total variation (TV) and a data fidelity (DF) term with a parameter λ that governs the relative weight between them. Finding the optimized value of λ is a critical step for this approach to give satisfactory results. The proposed LB method avoid using λ by constructing the objective function as the sum of the TV and a log function whose augment is the DF term. Newton's method was used to solve the optimization problem. The algorithm was coded in MatLab2013b. Both Shepp-Logan phantom and a patient lung CT image were used for demonstration of the algorithm. Measured data were simulated by calculating the projection data using radon transform. A Poisson noise model was used to account for the simulated detector noise. The iteration stopped when the difference of the current TV and the previous one was less than 1%. Results: Shepp-Logan phantom reconstruction study shows that filtered back-projection (FBP) gives high streak artifacts for 30 and 40 projections. Although visually the streak artifacts are less pronounced for 64 and 90 projections in FBP, the 1D pixel profiles indicate that FBP gives noisier reconstructed pixel values than LB does. A lung image reconstruction is presented. It shows that use of 64 projections gives satisfactory reconstructed image quality with regard to noise suppression and sharp edge preservation. Conclusion: This study demonstrates that the logarithmic barrier method can be used to reconstruct CT images from sparsely-amped data. The number of projections around 64 gives a balance between the over-smoothing of the sharp demarcation and noise suppression. Future study may extend to CBCT reconstruction and improvement on computation speed.

Feasibility of low-dose CT with model-based iterative image reconstruction in follow-up of patients with testicular cancer

International Nuclear Information System (INIS)

Murphy, Kevin P.; Crush, Lee; O’Neill, Siobhan B.; Foody, James; Breen, Micheál; Brady, Adrian; Kelly, Paul J.; Power, Derek G.; Sweeney, Paul; Bye, Jackie; O’Connor, Owen J.; Maher, Michael M.; O’Regan, Kevin N.

2016-01-01

•Radiologists should endeavour to minimise radiation exposure to patients with testicular cancer.•Iterative reconstruction algorithms permit CT imaging at lower radiation doses.•Image quality for reduced-dose CT–MBIR is at least comparable to conventional dose.•No loss of diagnostic accuracy apparent with reduced-dose CT–MBIR. Radiologists should endeavour to minimise radiation exposure to patients with testicular cancer. Iterative reconstruction algorithms permit CT imaging at lower radiation doses. Image quality for reduced-dose CT–MBIR is at least comparable to conventional dose. No loss of diagnostic accuracy apparent with reduced-dose CT–MBIR. We examine the performance of pure model-based iterative reconstruction with reduced-dose CT in follow-up of patients with early-stage testicular cancer. Sixteen patients (mean age 35.6 ± 7.4 years) with stage I or II testicular cancer underwent conventional dose (CD) and low-dose (LD) CT acquisition during CT surveillance. LD data was reconstructed with model-based iterative reconstruction (LD–MBIR). Datasets were objectively and subjectively analysed at 8 anatomical levels. Two blinded clinical reads were compared to gold-standard assessment for diagnostic accuracy. Mean radiation dose reduction of 67.1% was recorded. Mean dose measurements for LD–MBIR were: thorax – 66 ± 11 mGy cm (DLP), 1.0 ± 0.2 mSv (ED), 2.0 ± 0.4 mGy (SSDE); abdominopelvic – 128 ± 38 mGy cm (DLP), 1.9 ± 0.6 mSv (ED), 3.0 ± 0.6 mGy (SSDE). Objective noise and signal-to-noise ratio values were comparable between the CD and LD–MBIR images. LD–MBIR images were superior (p < 0.001) with regard to subjective noise, streak artefact, 2-plane contrast resolution, 2-plane spatial resolution and diagnostic acceptability. All patients were correctly categorised as positive, indeterminate or negative for metastatic disease by 2 readers on LD–MBIR and CD datasets. MBIR facilitated a 67% reduction in radiation dose whilst

Three-dimensional focus of attention for iterative cone-beam micro-CT reconstruction

International Nuclear Information System (INIS)

Benson, T M; Gregor, J

2006-01-01

Three-dimensional iterative reconstruction of high-resolution, circular orbit cone-beam x-ray CT data is often considered impractical due to the demand for vast amounts of computer cycles and associated memory. In this paper, we show that the computational burden can be reduced by limiting the reconstruction to a small, well-defined portion of the image volume. We first discuss using the support region defined by the set of voxels covered by all of the projection views. We then present a data-driven preprocessing technique called focus of attention that heuristically separates both image and projection data into object and background before reconstruction, thereby further reducing the reconstruction region of interest. We present experimental results for both methods based on mouse data and a parallelized implementation of the SIRT algorithm. The computational savings associated with the support region are substantial. However, the results for focus of attention are even more impressive in that only about one quarter of the computer cycles and memory are needed compared with reconstruction of the entire image volume. The image quality is not compromised by either method

Wind reconstruction algorithm for Viking Lander 1

Science.gov (United States)

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

2017-06-01

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

Wind reconstruction algorithm for Viking Lander 1

Directory of Open Access Journals (Sweden)

T. Kynkäänniemi

2017-06-01

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

X-ray differential phase-contrast tomographic reconstruction with a phase line integral retrieval filter

International Nuclear Information System (INIS)

Fu, Jian; Hu, Xinhua; Li, Chen

2015-01-01

We report an alternative reconstruction technique for x-ray differential phase-contrast computed tomography (DPC-CT). This approach is based on a new phase line integral projection retrieval filter, which is rooted in the derivative property of the Fourier transform and counteracts the differential nature of the DPC-CT projections. It first retrieves the phase line integral from the DPC-CT projections. Then the standard filtered back-projection (FBP) algorithms popular in x-ray absorption-contrast CT are directly applied to the retrieved phase line integrals to reconstruct the DPC-CT images. Compared with the conventional DPC-CT reconstruction algorithms, the proposed method removes the Hilbert imaginary filter and allows for the direct use of absorption-contrast FBP algorithms. Consequently, FBP-oriented image processing techniques and reconstruction acceleration softwares that have already been successfully used in absorption-contrast CT can be directly adopted to improve the DPC-CT image quality and speed up the reconstruction

A fast sparse reconstruction algorithm for electrical tomography

International Nuclear Information System (INIS)

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

2014-01-01

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

Noise properties of CT images reconstructed by use of constrained total-variation, data-discrepancy minimization

DEFF Research Database (Denmark)

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

2015-01-01

Purpose: The authors develop and investigate iterative image reconstruction algorithms based on data-discrepancy minimization with a total-variation (TV) constraint. The various algorithms are derived with different data-discrepancy measures reflecting the maximum likelihood (ML) principle......: An incremental algorithm framework is developed for this purpose. The instances of the incremental algorithms are derived for solving optimization problems including a data fidelity objective function combined with a constraint on the image TV. For the data fidelity term the authors, compare application....... Simulations demonstrate the iterative algorithms and the resulting image statistical properties for low-dose CT data acquired with sparse projection view angle sampling. Of particular interest is to quantify improvement of image statistical properties by use of the ML data fidelity term. Methods...

Selected event reconstruction algorithms for the CBM experiment at FAIR

International Nuclear Information System (INIS)

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

2014-01-01

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

Diagnostic value of 3 D CT surface reconstruction in spinal fractures

Energy Technology Data Exchange (ETDEWEB)

Koesling, S. [Department of Radiology, Univ. of Leipzig (Germany); Dietrich, K. [Department of Radiology, Univ. of Leipzig (Germany); Steinecke, R. [Department of Radiology, Univ. of Leipzig (Germany); Kloeppel, R. [Department of Radiology, Univ. of Leipzig (Germany); Schulz, H.G. [Department of Radiology, Univ. of Leipzig (Germany)

1997-02-01

Our purpose was to evaluate the diagnostic value of three-dimensional (3 D) CT surface reconstruction in spinal fractures in comparison with axial and reformatted images. A total of 50 patients with different CT-proven spinal fractures were analysed retrospectively. Based on axial scans and reformatted images, the spinal fractures were classified according to several classifications as Magerl for the thoraco-lumbar and lower cervical spine by one radiologist. Another radiologist performed 3 D CT surface reconstructions with the aim of characterizing the different types of spinal fractures. A third radiologist classified the 3 D CT surface reconstruction according to the Magerl classification. The results of the blinded reading process were compared. It was checked to see in which type and subgroup 3 D surface reconstructions were helpful. Readers one and two obtained the same results in the classification. The 3 D surface reconstruction did not yield any additional diagnostic information concerning type A and B injuries. Indeed, the full extent of the fracture could be easier recognized with axial and reformatted images in all cases. In 10 cases of C injuries, the dislocation of parts of vertebrae could be better recognized with the help of 3 D reconstructions. A 3 D CT surface reconstruction is only useful in rotational and shear vertebral injuries (Magerl type C injury). (orig.). With 4 figs., 1 tab.

Methods of X-ray CT image reconstruction from few projections; Methodes de reconstruction d'images a partir d'un faible nombre de projections en tomographie par rayons X

Energy Technology Data Exchange (ETDEWEB)

Wang, H.

2011-10-24

To improve the safety (low dose) and the productivity (fast acquisition) of a X-ray CT system, we want to reconstruct a high quality image from a small number of projections. The classical reconstruction algorithms generally fail since the reconstruction procedure is unstable and suffers from artifacts. A new approach based on the recently developed 'Compressed Sensing' (CS) theory assumes that the unknown image is in some sense 'sparse' or 'compressible', and the reconstruction is formulated through a non linear optimization problem (TV/l1 minimization) by enhancing the sparsity. Using the pixel (or voxel in 3D) as basis, to apply the CS framework in CT one usually needs a 'sparsifying' transform, and combines it with the 'X-ray projector' which applies on the pixel image. In this thesis, we have adapted a 'CT-friendly' radial basis of Gaussian family called 'blob' to the CS-CT framework. The blob has better space-frequency localization properties than the pixel, and many operations, such as the X-ray transform, can be evaluated analytically and are highly parallelizable (on GPU platform). Compared to the classical Kaisser-Bessel blob, the new basis has a multi-scale structure: an image is the sum of dilated and translated radial Mexican hat functions. The typical medical objects are compressible under this basis, so the sparse representation system used in the ordinary CS algorithms is no more needed. 2D simulations show that the existing TV and l1 algorithms are more efficient and the reconstructions have better visual quality than the equivalent approach based on the pixel or wavelet basis. The new approach has also been validated on 2D experimental data, where we have observed that in general the number of projections can be reduced to about 50%, without compromising the image quality. (author) [French] Afin d'ameliorer la surete (faible dose) et la productivite (acquisition rapide) du

Radiation Dose Reduction of Chest CT with Iterative Reconstruction in Image Space - Part I: Studies on Image Quality Using Dual Source CT

International Nuclear Information System (INIS)

Hwang, Hye Jeon; Seo, Joon Beom; Lee, Jin Seong; Song, Jae Woo; Lee, Hyun Joo; Lim, Chae Hun; Kim, Song Soo

2012-01-01

To determine whether the image quality (IQ) is improved with iterative reconstruction in image space (IRIS), and whether IRIS can be used for radiation reduction in chest CT. Standard dose chest CT (SDCT) in 50 patients and low dose chest CT (LDCT) in another 50 patients were performed, using a dual-source CT, with 120 kVp and same reference mAs (50 mAs for SDCT and 25 mAs for LDCT) employed to both tubes by modifying a dual-energy scan mode. Full-dose data were obtained by combining the data from both tubes and half-dose data were separated from a single tube. These were reconstructed by using a filtered back projection (FBP) and IRIS: full-dose FBP (F-FBP); full-dose IRIS (F-IRIS); half-dose FBP (H-FBP) and half-dose IRIS (H-IRIS). Objective noise was measured. The subjective IQ was evaluated by radiologists for the followings: noise, contrast and sharpness of mediastinum and lung. Objective noise was significantly lower in H-IRIS than in F-FBP (p < 0.01). In both SDCT and LDCT, the IQ scores were highest in F-IRIS, followed by F-FBP, H-IRIS and H-FBP, except those for sharpness of mediastinum, which tended to be higher in FBP. When comparing CT images between the same dose and different reconstruction (F-IRIS/F-FBP and H-IRIS/H-FBP) algorithms, scores tended to be higher in IRIS than in FBP, being more distinct in half-dose images. However, despite the use of IRIS, the scores were lower in H-IRIS than in F-FBP. IRIS generally helps improve the IQ, being more distinct at the reduced radiation. However, reduced radiation by half results in IQ decrease even when using IRIS in chest CT.

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

International Nuclear Information System (INIS)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

2015-01-01

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of

Cardiac motion correction based on partial angle reconstructed images in x-ray CT

Energy Technology Data Exchange (ETDEWEB)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr [Department of Electrical Engineering, KAIST, Daejeon 305-701 (Korea, Republic of)

2015-05-15

Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of

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.

The use of anatomical information for molecular image reconstruction algorithms: Attention/Scatter correction, motion compensation, and noise reduction

Energy Technology Data Exchange (ETDEWEB)

Chun, Se Young [School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan (Korea, Republic of)

2016-03-15

PET and SPECT are important tools for providing valuable molecular information about patients to clinicians. Advances in nuclear medicine hardware technologies and statistical image reconstruction algorithms enabled significantly improved image quality. Sequentially or simultaneously acquired anatomical images such as CT and MRI from hybrid scanners are also important ingredients for improving the image quality of PET or SPECT further. High-quality anatomical information has been used and investigated for attenuation and scatter corrections, motion compensation, and noise reduction via post-reconstruction filtering and regularization in inverse problems. In this article, we will review works using anatomical information for molecular image reconstruction algorithms for better image quality by describing mathematical models, discussing sources of anatomical information for different cases, and showing some examples.

Simulation and experimental studies of three-dimensional (3D) image reconstruction from insufficient sampling data based on compressed-sensing theory for potential applications to dental cone-beam CT

International Nuclear Information System (INIS)

Je, U.K.; Lee, M.S.; Cho, H.S.; Hong, D.K.; Park, Y.O.; Park, C.K.; Cho, H.M.; Choi, S.I.; Woo, T.H.

2015-01-01

In practical applications of three-dimensional (3D) tomographic imaging, there are often challenges for image reconstruction from insufficient sampling data. In computed tomography (CT), for example, image reconstruction from sparse views and/or limited-angle (<360°) views would enable fast scanning with reduced imaging doses to the patient. In this study, we investigated and implemented a reconstruction algorithm based on the compressed-sensing (CS) theory, which exploits the sparseness of the gradient image with substantially high accuracy, for potential applications to low-dose, high-accurate dental cone-beam CT (CBCT). We performed systematic simulation works to investigate the image characteristics and also performed experimental works by applying the algorithm to a commercially-available dental CBCT system to demonstrate its effectiveness for image reconstruction in insufficient sampling problems. We successfully reconstructed CBCT images of superior accuracy from insufficient sampling data and evaluated the reconstruction quality quantitatively. Both simulation and experimental demonstrations of the CS-based reconstruction from insufficient data indicate that the CS-based algorithm can be applied directly to current dental CBCT systems for reducing the imaging doses and further improving the image quality

Evaluation and comparison of contrast to noise ratio and signal to noise ratio according to change of reconstruction on breast PET/CT

Energy Technology Data Exchange (ETDEWEB)

Lee, Young Jae [Dept. of Nuclear Medicine, Seoul National University Hospital, Seoul (Korea, Republic of); Lee, Eul Kyu [Dept. of Radiology, Inje Paik University Hospital Jeo-dong, Seoul (Korea, Republic of); Kim, Ki Won [Dept. of Radiology, Kyung Hee University Hospital at Gang-dong, Seoul (Korea, Republic of); Jeong, Hoi Woun [Dept. of Radiological Technology, The Baekseok Culture University, Cheonan (Korea, Republic of); Lyu, Kwang Yeul; Park, Hoon Hee; Son, Jin Hyun; Min, Jung Whan [Dept. of Radiological Technology, The Shingu University, Sungnam (Korea, Republic of)

2017-03-15

The purpose of this study was to measure contrast to noise ratio (CNR) and signal to noise ratio (SNR) according to change of reconstruction from region of interest (ROI) in breast positron emission tomography- computed tomography (PET-CT), and to analyze the CNR and SNR statically. We examined images of breast PET-CT of 100 patients in a University-affiliated hospital, Seoul, Korea. Each patient's image of breast PET-CT were calculated by using Image J. Differences of CNR and SNR among four reconstruction algorithms were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p<0.05). We have analysis socio-demographical variables, CNR and SNR according to reconstruction images, 95% confidence according to CNR and SNR of reconstruction and difference in a mean of CNR and SNR. SNR results, with the quality of distributions in the order of PSF{sub T}OF, Iterative and Iterative-TOF, FBP-TOF. CNR, with the quality of distributions in the order of PSF{sub T}OF, Iterative and Iterative-TOF, FBP-TOF. CNR and SNR of PET-CT reconstruction methods of the breast would be useful to evaluate breast diseases.

Implementation of a cone-beam reconstruction algorithm for the single-circle source orbit with embedded misalignment correction using homogeneous coordinates

International Nuclear Information System (INIS)

Karolczak, Marek; Schaller, Stefan; Engelke, Klaus; Lutz, Andreas; Taubenreuther, Ulrike; Wiesent, Karl; Kalender, Willi

2001-01-01

We present an efficient implementation of an approximate cone-beam image reconstruction algorithm for application in tomography, which accounts for scanner mechanical misalignment. The implementation is based on the algorithm proposed by Feldkamp et al. [J. Opt. Soc. Am. A 6, 612-619 (1984)] and is directed at circular scan paths. The algorithm has been developed for the purpose of reconstructing volume data from projections acquired in an experimental x-ray microtomography (μCT) scanner [Engelke et al., Der Radiologe 39, 203-212 (1999)]. To mathematically model misalignment we use matrix notation with homogeneous coordinates to describe the scanner geometry, its misalignment, and the acquisition process. For convenience analysis is carried out for x-ray CT scanners, but it is applicable to any tomographic modality, where two-dimensional projection acquisition in cone beam geometry takes place, e.g., single photon emission computerized tomography. We derive an algorithm assuming misalignment errors to be small enough to weight and filter original projections and to embed compensation for misalignment in the backprojection. We verify the algorithm on simulations of virtual phantoms and scans of a physical multidisk (Defrise) phantom

Application of CT three-dimensional reconstruction in elbow injury

International Nuclear Information System (INIS)

Liang Wenhua; Qian Li

2009-01-01

Objective: To investigate the application of multi-slice spiral CT in fracture of elbow, and to study the value of different methods of the reconstruction. Methods: Thin line cross-section spiral CT scan was carried out in 13 cases with elbow injury, three-dimensional reconstruction was completed later. Several reconstructed image quality to display f the elbow fracture and dislocation were analyzed and compared. Results: 13 cases (17) elbow trauma included humeral media epicondyle fracture, humeral external epicondyle fracture, intercondylar fracture, olecranal fracture and radial head fracture. Among them, X-ray film showed negative in three sites, showed suspect fractures in 2 cases, and only showed single fracture in 2 cases. MPR reconstruction image could not only identify the diagnosis of fracture, but also provide further multi-angle display on fracture line and the extent of articular surface involvement. Surface reconstruction technology could exclude the impact of passive elbow flexion and display elbow injury more intuitively. Conclusion The elbow fracture dislocation could be showed clearly in multi-slice spiral CT, especially for complex fractures, with unmatched advantages compared to X-ray for clinical diagnosis and treatment determination. (authors)

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

Science.gov (United States)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

Low-dose X-ray CT reconstruction via dictionary learning.

Science.gov (United States)

Xu, Qiong; Yu, Hengyong; Mou, Xuanqin; Zhang, Lei; Hsieh, Jiang; Wang, Ge

2012-09-01

Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures.

Advanced reconstruction algorithms for electron tomography: From comparison to combination

Energy Technology Data Exchange (ETDEWEB)

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

2013-04-15

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

Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers

International Nuclear Information System (INIS)

Tseng, Hsin-Wu; Kupinski, Matthew A.; Fan, Jiahua; Sainath, Paavana; Hsieh, Jiang

2014-01-01

Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR). Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG).A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves. Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors’ task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%–67% (head phantom) and 68%–82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%–75% for head phantom and 67%–77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images. Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the

Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source

Science.gov (United States)

Mason, Jonathan H.; Perelli, Alessandro; Nailon, William H.; Davies, Mike E.

2017-11-01

Quantifying material mass and electron density from computed tomography (CT) reconstructions can be highly valuable in certain medical practices, such as radiation therapy planning. However, uniquely parameterising the x-ray attenuation in terms of mass or electron density is an ill-posed problem when a single polyenergetic source is used with a spectrally indiscriminate detector. Existing approaches to single source polyenergetic modelling often impose consistency with a physical model, such as water-bone or photoelectric-Compton decompositions, which will either require detailed prior segmentation or restrictive energy dependencies, and may require further calibration to the quantity of interest. In this work, we introduce a data centric approach to fitting the attenuation with piecewise-linear functions directly to mass or electron density, and present a segmentation-free statistical reconstruction algorithm for exploiting it, with the same order of complexity as other iterative methods. We show how this allows both higher accuracy in attenuation modelling, and demonstrate its superior quantitative imaging, with numerical chest and metal implant data, and validate it with real cone-beam CT measurements.

Does iterative reconstruction lower CT radiation dose: evaluation of 15,000 examinations.

Directory of Open Access Journals (Sweden)

Peter B Noël

Full Text Available PURPOSE: Evaluation of 15,000 computed tomography (CT examinations to investigate if iterative reconstruction (IR reduces sustainably radiation exposure. METHOD AND MATERIALS: Information from 15,000 CT examinations was collected, including all aspects of the exams such as scan parameter, patient information, and reconstruction instructions. The examinations were acquired between January 2010 and December 2012, while after 15 months a first generation IR algorithm was installed. To collect the necessary information from PACS, RIS, MPPS and structured reports a Dose Monitoring System was developed. To harvest all possible information an optical character recognition system was integrated, for example to collect information from the screenshot CT-dose report. The tool transfers all data to a database for further processing such as the calculation of effective dose and organ doses. To evaluate if IR provides a sustainable dose reduction, the effective dose values were statistically analyzed with respect to protocol type, diagnostic indication, and patient population. RESULTS: IR has the potential to reduce radiation dose significantly. Before clinical introduction of IR the average effective dose was 10.1±7.8mSv and with IR 8.9±7.1mSv (p*=0.01. Especially in CTA, with the possibility to use kV reduction protocols, such as in aortic CTAs (before IR: average14.2±7.8mSv; median11.4mSv /with IR:average9.9±7.4mSv; median7.4mSv, or pulmonary CTAs (before IR: average9.7±6.2mSV; median7.7mSv /with IR: average6.4±4.7mSv; median4.8mSv the dose reduction effect is significant(p*=0.01. On the contrary for unenhanced low-dose scans of the cranial (for example sinuses the reduction is not significant (before IR:average6.6±5.8mSv; median3.9mSv/with IR:average6.0±3.1mSV; median3.2mSv. CONCLUSION: The dose aspect remains a priority in CT research. Iterative reconstruction algorithms reduce sustainably and significantly radiation dose in the clinical routine

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

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.)

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

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.)

Tensor-based Dictionary Learning for Spectral CT Reconstruction

Science.gov (United States)

Zhang, Yanbo; Wang, Ge

2016-01-01

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

Tensor-Based Dictionary Learning for Spectral CT Reconstruction.

Science.gov (United States)

Zhang, Yanbo; Mou, Xuanqin; Wang, Ge; Yu, Hengyong

2017-01-01

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods.

Synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON): A statistical model based iterative image reconstruction method to eliminate limited-view artifacts and to mitigate the temporal-average artifacts in time-resolved CT.

Science.gov (United States)

Chen, Guang-Hong; Li, Yinsheng

2015-08-01

In x-ray computed tomography (CT), a violation of the Tuy data sufficiency condition leads to limited-view artifacts. In some applications, it is desirable to use data corresponding to a narrow temporal window to reconstruct images with reduced temporal-average artifacts. However, the need to reduce temporal-average artifacts in practice may result in a violation of the Tuy condition and thus undesirable limited-view artifacts. In this paper, the authors present a new iterative reconstruction method, synchronized multiartifact reduction with tomographic reconstruction (SMART-RECON), to eliminate limited-view artifacts using data acquired within an ultranarrow temporal window that severely violates the Tuy condition. In time-resolved contrast enhanced CT acquisitions, image contrast dynamically changes during data acquisition. Each image reconstructed from data acquired in a given temporal window represents one time frame and can be denoted as an image vector. Conventionally, each individual time frame is reconstructed independently. In this paper, all image frames are grouped into a spatial-temporal image matrix and are reconstructed together. Rather than the spatial and/or temporal smoothing regularizers commonly used in iterative image reconstruction, the nuclear norm of the spatial-temporal image matrix is used in SMART-RECON to regularize the reconstruction of all image time frames. This regularizer exploits the low-dimensional structure of the spatial-temporal image matrix to mitigate limited-view artifacts when an ultranarrow temporal window is desired in some applications to reduce temporal-average artifacts. Both numerical simulations in two dimensional image slices with known ground truth and in vivo human subject data acquired in a contrast enhanced cone beam CT exam have been used to validate the proposed SMART-RECON algorithm and to demonstrate the initial performance of the algorithm. Reconstruction errors and temporal fidelity of the reconstructed

Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction?

International Nuclear Information System (INIS)

Pan, Xiaochuan; Sidky, Emil Y; Vannier, Michael

2009-01-01

Despite major advances in x-ray sources, detector arrays, gantry mechanical design and especially computer performance, one component of computed tomography (CT) scanners has remained virtually constant for the past 25 years—the reconstruction algorithm. Fundamental advances have been made in the solution of inverse problems, especially tomographic reconstruction, but these works have not been translated into clinical and related practice. The reasons are not obvious and seldom discussed. This review seeks to examine the reasons for this discrepancy and provides recommendations on how it can be resolved. We take the example of field of compressive sensing (CS), summarizing this new area of research from the eyes of practical medical physicists and explaining the disconnection between theoretical and application-oriented research. Using a few issues specific to CT, which engineers have addressed in very specific ways, we try to distill the mathematical problem underlying each of these issues with the hope of demonstrating that there are interesting mathematical problems of general importance that can result from in depth analysis of specific issues. We then sketch some unconventional CT-imaging designs that have the potential to impact on CT applications, if the link between applied mathematicians and engineers/physicists were stronger. Finally, we close with some observations on how the link could be strengthened. There is, we believe, an important opportunity to rapidly improve the performance of CT and related tomographic imaging techniques by addressing these issues. (topical review)

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

Pulmonary sequestration: diagnosis with three dimensional reconstruction using spiral CT

International Nuclear Information System (INIS)

Nie Yongkang; Zhao Shaohong; Cai Zulong; Yang Li; Zhao Hong; Zhang Ailian; Huang Hui

2003-01-01

Objective: To evaluate the role of three dimensional (3D) reconstruction using spiral CT in the diagnosis of pulmonary sequestration. Methods: Ten patients with pulmonary sequestration were analyzed. The diagnoses were confirmed by angiography in 2 patients, by operation in 2 patients, and by CT angiography in 6 patients. All patients were examined with Philips SR 7000 or GE Lightspeed Plus scanner. CT images were transferred to a workstation and 3D reconstruction was performed. All images were reviewed and analyzed by two radiologists. Results: Among 10 patients, the pulmonary sequestration was in the right lower lobe in 1 patient and in the left lower lobe in 9 patients. Anomalous systemic arteries originated from thoracic aorta in 8 patients and from celiac artery in 2 patients. On plain CT scan, there were 4 patients with patchy opacities, 3 patients with hilar mass accompanying vascular engorgement and profusion in adjacent parenchyma, 2 patients with finger-like appendage surrounded by hyper-inflated lung, and 1 patient with lung mass-like lesion. Enhanced CT revealed anomalous systemic arteries in 9 patients and drainage vein in 7 patients. Maximum intensity projection (MIP) and curvilinear reconstruction could depict the abnormal systemic artery and drainage vein in sequestration. Surface shadow display (SSD) and volume rendering (VR) could delineate the anomalous systemic artery. Conclusion: 3D reconstruction with enhanced spiral CT can depict anomalous systemic artery and drainage vein and it is the first method of choice in diagnosing pulmonary sequestration

SU-F-J-23: Field-Of-View Expansion in Cone-Beam CT Reconstruction by Use of Prior Information

Energy Technology Data Exchange (ETDEWEB)

Haga, A; Magome, T; Nakano, M; Nakagawa, K [University of Tokyo Hospital, Tokyo (Japan); Kotoku, J [Teikyo University, Tokyo (Japan)

2016-06-15

Purpose: Cone-beam CT (CBCT) has become an integral part of online patient setup in an image-guided radiation therapy (IGRT). In addition, the utility of CBCT for dose calculation has actively been investigated. However, the limited size of field-of-view (FOV) and resulted CBCT image with a lack of peripheral area of patient body prevents the reliability of dose calculation. In this study, we aim to develop an FOV expanded CBCT in IGRT system to allow the dose calculation. Methods: Three lung cancer patients were selected in this study. We collected the cone-beam projection images in the CBCT-based IGRT system (X-ray volume imaging unit, ELEKTA), where FOV size of the provided CBCT with these projections was 410 × 410 mm{sup 2} (normal FOV). Using these projections, CBCT with a size of 728 × 728 mm{sup 2} was reconstructed by a posteriori estimation algorithm including a prior image constrained compressed sensing (PICCS). The treatment planning CT was used as a prior image. To assess the effectiveness of FOV expansion, a dose calculation was performed on the expanded CBCT image with region-of-interest (ROI) density mapping method, and it was compared with that of treatment planning CT as well as that of CBCT reconstructed by filtered back projection (FBP) algorithm. Results: A posteriori estimation algorithm with PICCS clearly visualized an area outside normal FOV, whereas the FBP algorithm yielded severe streak artifacts outside normal FOV due to under-sampling. The dose calculation result using the expanded CBCT agreed with that using treatment planning CT very well; a maximum dose difference was 1.3% for gross tumor volumes. Conclusion: With a posteriori estimation algorithm, FOV in CBCT can be expanded. Dose comparison results suggested that the use of expanded CBCTs is acceptable for dose calculation in adaptive radiation therapy. This study has been supported by KAKENHI (15K08691).

Low-Dose X-ray CT Reconstruction via Dictionary Learning

Science.gov (United States)

Xu, Qiong; Zhang, Lei; Hsieh, Jiang; Wang, Ge

2013-01-01

Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures. PMID:22542666

SU-F-P-45: Clinical Experience with Radiation Dose Reduction of CT Examinations Using Iterative Reconstruction Algorithms

Energy Technology Data Exchange (ETDEWEB)

Weir, V [Baylor Scott and White Healthcare System, Dallas, TX (United States); Zhang, J [University of Kentucky, Lexington, KY (United States)

2016-06-15

Purpose: Iterative reconstruction (IR) algorithms have been adopted by medical centers in the past several years. IR has a potential to substantially reduce patient dose while maintaining or improving image quality. This study characterizes dose reductions in clinical settings for CT examinations using IR. Methods: We retrospectively analyzed dose information from patients who underwent abdomen/pelvis CT examinations with and without contrast media in multiple locations of our Healthcare system. A total of 743 patients scanned with ASIR on 64 slice GE lightspeed VCTs at three sites, and 30 patients scanned with SAFIRE on a Siemens 128 slice Definition Flash in one site was retrieved. For comparison, patient data (n=291) from a GE scanner and patient data (n=61) from two Siemens scanners where filtered back-projection (FBP) was used was collected retrospectively. 30% and 10% ASIR, and SAFIRE Level 2 was used. CTDIvol, Dose-length-product (DLP), weight and height from all patients was recorded. Body mass index (BMI) was calculated accordingly. To convert CTDIvol to SSDE, AP and lateral dimensions at the mid-liver level was measured for each patient. Results: Compared with FBP, 30% ASIR reduces dose by 44.1% (SSDE: 12.19mGy vs. 21.83mGy), while 10% ASIR reduced dose by 20.6% (SSDE 17.32mGy vs. 21.83). Use of SAFIRE reduced dose by 61.4% (SSDE: 8.77mGy vs. 22.7mGy). The geometric mean for patients scanned with ASIR was larger than for patients scanned with FBP (geometric mean is 297.48 mmm vs. 284.76 mm). The same trend was observed for the Siemens scanner where SAFIRE was used (geometric mean: 316 mm with SAFIRE vs. 239 mm with FBP). Patient size differences suggest that further dose reduction is possible. Conclusion: Our data confirmed that in clinical practice IR can significantly reduce dose to patients who undergo CT examinations, while meeting diagnostic requirements for image quality.

SU-F-P-45: Clinical Experience with Radiation Dose Reduction of CT Examinations Using Iterative Reconstruction Algorithms

International Nuclear Information System (INIS)

Weir, V; Zhang, J

2016-01-01

Purpose: Iterative reconstruction (IR) algorithms have been adopted by medical centers in the past several years. IR has a potential to substantially reduce patient dose while maintaining or improving image quality. This study characterizes dose reductions in clinical settings for CT examinations using IR. Methods: We retrospectively analyzed dose information from patients who underwent abdomen/pelvis CT examinations with and without contrast media in multiple locations of our Healthcare system. A total of 743 patients scanned with ASIR on 64 slice GE lightspeed VCTs at three sites, and 30 patients scanned with SAFIRE on a Siemens 128 slice Definition Flash in one site was retrieved. For comparison, patient data (n=291) from a GE scanner and patient data (n=61) from two Siemens scanners where filtered back-projection (FBP) was used was collected retrospectively. 30% and 10% ASIR, and SAFIRE Level 2 was used. CTDIvol, Dose-length-product (DLP), weight and height from all patients was recorded. Body mass index (BMI) was calculated accordingly. To convert CTDIvol to SSDE, AP and lateral dimensions at the mid-liver level was measured for each patient. Results: Compared with FBP, 30% ASIR reduces dose by 44.1% (SSDE: 12.19mGy vs. 21.83mGy), while 10% ASIR reduced dose by 20.6% (SSDE 17.32mGy vs. 21.83). Use of SAFIRE reduced dose by 61.4% (SSDE: 8.77mGy vs. 22.7mGy). The geometric mean for patients scanned with ASIR was larger than for patients scanned with FBP (geometric mean is 297.48 mmm vs. 284.76 mm). The same trend was observed for the Siemens scanner where SAFIRE was used (geometric mean: 316 mm with SAFIRE vs. 239 mm with FBP). Patient size differences suggest that further dose reduction is possible. Conclusion: Our data confirmed that in clinical practice IR can significantly reduce dose to patients who undergo CT examinations, while meeting diagnostic requirements for image quality.

WE-G-207-02: Full Sequential Projection Onto Convex Sets (FS-POCS) for X-Ray CT Reconstruction

International Nuclear Information System (INIS)

Liu, L; Han, Y; Jin, M

2015-01-01

Purpose: To develop an iterative reconstruction method for X-ray CT, in which the reconstruction can quickly converge to the desired solution with much reduced projection views. Methods: The reconstruction is formulated as a convex feasibility problem, i.e. the solution is an intersection of three convex sets: 1) data fidelity (DF) set – the L2 norm of the difference of observed projections and those from the reconstructed image is no greater than an error bound; 2) non-negativity of image voxels (NN) set; and 3) piecewise constant (PC) set - the total variation (TV) of the reconstructed image is no greater than an upper bound. The solution can be found by applying projection onto convex sets (POCS) sequentially for these three convex sets. Specifically, the algebraic reconstruction technique and setting negative voxels as zero are used for projection onto the DF and NN sets, respectively, while the projection onto the PC set is achieved by solving a standard Rudin, Osher, and Fatemi (ROF) model. The proposed method is named as full sequential POCS (FS-POCS), which is tested using the Shepp-Logan phantom and the Catphan600 phantom and compared with two similar algorithms, TV-POCS and CP-TV. Results: Using the Shepp-Logan phantom, the root mean square error (RMSE) of reconstructed images changing along with the number of iterations is used as the convergence measurement. In general, FS- POCS converges faster than TV-POCS and CP-TV, especially with fewer projection views. FS-POCS can also achieve accurate reconstruction of cone-beam CT of the Catphan600 phantom using only 54 views, comparable to that of FDK using 364 views. Conclusion: We developed an efficient iterative reconstruction for sparse-view CT using full sequential POCS. The simulation and physical phantom data demonstrated the computational efficiency and effectiveness of FS-POCS

A very fast implementation of 2D iterative reconstruction algorithms

DEFF Research Database (Denmark)

Toft, Peter Aundal; Jensen, Peter James

1996-01-01

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

Two-and three-dimensional CT reconstruction

International Nuclear Information System (INIS)

Fishman, E.K.; Ney, D.R.; Magid, D.

1990-01-01

This paper determines the optimal imaging sequence for creating two- and three-dimensional (2D/3D) skeletal reconstructions from CT data. A cadaver femur, a bone phantom, and a surgically created fracture were scanned with varying protocols to determine the optimal protocol for creating 2D/3D images. The scanning protocols used varying section thickness (2, 4, and 8 mm) as well as scan spacing (2, 3, 4 and 8 mm). All images were reconstructed into 2D data sets with a bicubic interpolation and 3D datasets with volumetric rendering. The results were reviewed by two reviewers to determine the quality of images reconstruction

Research on compressive sensing reconstruction algorithm based on total variation model

Science.gov (United States)

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

2017-12-01

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

Application of low-tube current with iterative model reconstruction on Philips Brilliance iCT Elite FHD in the accuracy of spinal QCT using a European spine phantom.

Science.gov (United States)

Wu, Yan; Jiang, Yaojun; Han, Xueli; Wang, Mingyue; Gao, Jianbo

2018-02-01

To investigate the repeatability and accuracy of quantitative CT (QCT) measurement of bone mineral density (BMD) by low-mAs using iterative model reconstruction (IMR) technique based on phantom model. European spine phantom (ESP) was selected and measured on the Philips Brilliance iCT Elite FHD machine for 10 times. Data were transmitted to the QCT PRO workstation to measure BMD (mg/cm 3 ) of the ESP (L1, L2, L3). Scanning method: the voltage of X-ray tube is 120 kV, the electric current of X-ray tube output in five respective groups A-E were: 20, 30, 40, 50 and 60 mAs. Reconstruction: all data were reconstructed using filtered back projection (FBP), IR levels of hybrid iterative reconstruction (iDose 4 , levels 1, 2, 3, 4, 5, 6 were used) and IMR (levels 1, 2, 3 were used). ROIs were placed in the middle of L1, L2 and L3 spine phantom in each group. CT values, noise and contrast-to-noise ratio (CNR) were measured and calculated. One-way analysis of variance (ANOVA) was used to compare BMD values of different mAs and different IMR. Radiation dose [volume CT dose index (CTDI vol ) and dose length product (DLP)] was positively correlated with tube current. In L1 with low BMD, different mAs in FBP showed P0.05, indicating no difference in BMD. And P>0.05 was observed among BMD of spine phantom in L1, L2 and L3 under same mAs joined with varied iterative reconstruction. The BMD in L1 varied greatly during FBP reconstruction, and less variation was observed in reconstruction of IMR [1] and IMR [2]. The BMD of L2 changed more during FBP reconstruction, where less was observed in IMR [2]. The BMD of L3 varied greatly during FBP reconstruction, and was less varied in all levels of iDose 4 and reconstruction of IMR [2]. In addition, along with continuous mAs incensement, the CNRs in various algorithms continued to increase. Among them, CNR with the FBP algorithm is the lowest, and CNR of the IMR [3] algorithm is the highest. Repeated measurements of BMD with QCT in the ESP

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-15

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

Reconstruction of CT images by the Bayes- back projection method

CERN Document Server

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 ...

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

Directory of Open Access Journals (Sweden)

Wei Yu

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

Advanced single-slice rebinning for tilted spiral cone-beam CT

International Nuclear Information System (INIS)

Kachelriess, Marc; Fuchs, Theo; Schaller, Stefan; Kalender, Willi A.

2001-01-01

Future medical CT scanners and today's micro CT scanners demand cone-beam reconstruction algorithms that are capable of reconstructing data acquired from a tilted spiral trajectory where the vector of rotation is not necessarily parallel to the vector of table increment. For the medical CT scanner this case of nonparallel object motion is met for nonzero gantry tilt: the table moves into a direction that is not perpendicular to the plane of rotation. Since this is not a special application of medical CT but rather a daily routine in head exams, there is a strong need for corresponding reconstruction algorithms. In contrast to medical CT, where the special case of nonperpendicular motion is used on purpose, micro CT scanners cannot avoid aberrations of the rotational axis and the table increment vector due to alignment problems. Especially for those micro CT scanners that have the lifting stage mounted on the rotation table (in contrast to setups where the lifting stage holds the rotation table), this kind of misalignment is equivalent to a gantry tilt. We therefore generalize the advanced single-slice rebinning algorithm (ASSR), which is considered a very promising approach for medical cone-beam reconstruction due to its high image quality and its high reconstruction speed [Med. Phys. 27, 754-772 (2000)], to the case of tilted gantries. We evaluate this extended ASSR approach (which we will denote as ASSR + , for convenience) in comparison to the original ASSR algorithm using simulated phantom data for reconstruction. For the case of nonparallel object motion ASSR + shows significant improvements over ASSR, however, its computational complexity is slightly increased due to the broken symmetry of the spiral trajectory

Scout-view assisted interior micro-CT

International Nuclear Information System (INIS)

Sharma, Kriti Sen; Narayanan, Shree; Agah, Masoud; Holzner, Christian; Vasilescu, Dragoş M; Jin, Xin; Hoffman, Eric A; Yu, Hengyong; Wang, Ge

2013-01-01

Micro computed tomography (micro-CT) is a widely-used imaging technique. A challenge of micro-CT is to quantitatively reconstruct a sample larger than the field-of-view (FOV) of the detector. This scenario is characterized by truncated projections and associated image artifacts. However, for such truncated scans, a low resolution scout scan with an increased FOV is frequently acquired so as to position the sample properly. This study shows that the otherwise discarded scout scans can provide sufficient additional information to uniquely and stably reconstruct the interior region of interest. Two interior reconstruction methods are designed to utilize the multi-resolution data without significant computational overhead. While most previous studies used numerically truncated global projections as interior data, this study uses truly hybrid scans where global and interior scans were carried out at different resolutions. Additionally, owing to the lack of standard interior micro-CT phantoms, we designed and fabricated novel interior micro-CT phantoms for this study to provide means of validation for our algorithms. Finally, two characteristic samples from separate studies were scanned to show the effect of our reconstructions. The presented methods show significant improvements over existing reconstruction algorithms. (paper)

Reduced-dose abdominopelvic CT using hybrid iterative reconstruction in suspected left-sided colonic diverticulitis

Energy Technology Data Exchange (ETDEWEB)

Laqmani, Azien; Dulz, Simon; Behzadi, Cyrus; Schmidt-Holtz, Jakob; Wassenberg, Felicia; Adam, Gerhard; Regier, Marc [University Medical Center Hamburg-Eppendorf, Department of Diagnostic and Interventional Radiology, Hamburg (Germany); Veldhoen, Simon [University Medical Center Wuerzburg, Department of Diagnostic and Interventional Radiology, Wuerzburg (Germany); Derlin, Thorsten [Hannover Medical School, Department of Nuclear Medicine, Hannover (Germany); Sehner, Susanne [University Medical Center Hamburg-Eppendorf, Department of Medical Biometry and Epidemiology, Hamburg (Germany); Nagel, Hans-Dieter [Scientific and Application-oriented Studies and Consulting in Radiology (SASCRAD), Buchholz (Germany)

2016-01-15

To assess the effect of hybrid iterative reconstruction (HIR) and filtered back projection (FBP) on abdominopelvic CT with reduced-dose (RD-APCT) in the evaluation of acute left-sided colonic diverticulitis (ALCD). Twenty-five consecutive patients with suspected ALCD who underwent RD-APCT (mean CTDIvol 11.2 ± 4.2 mGy) were enrolled in this study. Raw data were reconstructed using FBP and two increasing HIR levels, L4 and L6. Two radiologists assessed image quality, image noise and reviewer confidence in interpreting findings of ALCD, including wall thickening, pericolic fat inflammation, pericolic abscess, and contained or free extraluminal air. Objective image noise (OIN) was measured. OIN was reduced up to 54 % with HIR compared to FBP. Subjective image quality of HIR images was superior to FBP; subjective image noise was reduced. The detection rate of extraluminal air was higher with HIR L6. Reviewer confidence in interpreting CT findings of ALCD significantly improved with application of HIR. RD-APCT with HIR offers superior image quality and lower image noise compared to FBP, allowing a high level of reviewer confidence in interpreting CT findings in ALCD. HIR facilitates detection of ALCD findings that may be missed with the FBP algorithm. (orig.)

Application status of three-dimensional CT reconstruction in hepatobiliary surgery

Directory of Open Access Journals (Sweden)

JIANG Chao

2017-02-01

Full Text Available With the development of imaging technology, three-dimensional CT reconstruction has been widely used in hepatobiliary surgery. Three-dimensional CT reconstruction can divide and reconstruct two-dimensional images into three-dimensional images and clearly show the location of lesion and its relationship with the intrahepatic bile duct system. It has an important value in the preoperative assessment of liver volume, diagnosis and treatment decision-making process, intraoperative precise operation, and postoperative individualized management, and promotes the constant development of hepatobiliary surgery and minimally invasive technology, and therefore, it holds promise for clinical application.

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Ali, I; Ahmad, S [University of Oklahoma Health Sciences, Oklahoma City, OK (United States); Alsbou, N [Department of Electrical and Computer Engineering, Ada, OH (United States)

2014-06-01

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embedded into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract

Designing on ICT reconstruction software based on DSP techniques

International Nuclear Information System (INIS)

Liu Jinhui; Xiang Xincheng

2006-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-07-01

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

A new iterative algorithm to reconstruct the refractive index.

Science.gov (United States)

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

2007-06-21

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

Pediatric chest HRCT using the iDose4 Hybrid Iterative Reconstruction Algorithm: Which iDose level to choose?

International Nuclear Information System (INIS)

Smarda, M; Alexopoulou, E; Mazioti, A; Kordolaimi, S; Ploussi, A; Efstathopoulos, E; Priftis, K

2015-01-01

Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our department's 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions. (paper)

Dose reduction with adaptive statistical iterative reconstruction for paediatric CT: phantom study and clinical experience on chest and abdomen CT.

Science.gov (United States)

Gay, F; Pavia, Y; Pierrat, N; Lasalle, S; Neuenschwander, S; Brisse, H J

2014-01-01

To assess the benefit and limits of iterative reconstruction of paediatric chest and abdominal computed tomography (CT). The study compared adaptive statistical iterative reconstruction (ASIR) with filtered back projection (FBP) on 64-channel MDCT. A phantom study was first performed using variable tube potential, tube current and ASIR settings. The assessed image quality indices were the signal-to-noise ratio (SNR), the noise power spectrum, low contrast detectability (LCD) and spatial resolution. A clinical retrospective study of 26 children (M:F = 14/12, mean age: 4 years, range: 1-9 years) was secondarily performed allowing comparison of 18 chest and 14 abdominal CT pairs, one with a routine CT dose and FBP reconstruction, and the other with 30 % lower dose and 40 % ASIR reconstruction. Two radiologists independently compared the images for overall image quality, noise, sharpness and artefacts, and measured image noise. The phantom study demonstrated a significant increase in SNR without impairment of the LCD or spatial resolution, except for tube current values below 30-50 mA. On clinical images, no significant difference was observed between FBP and reduced dose ASIR images. Iterative reconstruction allows at least 30 % dose reduction in paediatric chest and abdominal CT, without impairment of image quality. • Iterative reconstruction helps lower radiation exposure levels in children undergoing CT. • Adaptive statistical iterative reconstruction (ASIR) significantly increases SNR without impairing spatial resolution. • For abdomen and chest CT, ASIR allows at least a 30 % dose reduction.

SU-D-12A-05: Iterative Reconstruction Techniques to Enable Intrinsic Respiratory Gated CT in Mice

Energy Technology Data Exchange (ETDEWEB)

Sun, T; Sun, N; Tan, S [Huazhong University of Science and Technology, Wuhan, Hubei (China); Liu, Y; Mistry, N [University of Maryland School of Medicine, Baltimore, MD (United States)

2014-06-01

Purpose: Longitudinal studies of lung function in mice need the ability to image different phases of ventilation in free-breathing mice using retrospective gating. However, retrospective gating often produces under-sampled and uneven angular samples, resulting in severe reconstruction artifacts when using traditional FDK based reconstruction algorithms. We wanted to demonstrate the utility of iterative reconstruction method to enable intrinsic respiratory gating in small-animal CT. Methods: Free-breathing mice were imaged using a Siemens Inveon PET/micro-CT system. Evenly distributed projection images were acquired at 360 angles. Retrospective respiratory gating was performed using an intrinsic marker based on the average intensity in a region covering the diaphragm. Projections were classified into 4 and 6 phases (finer temporal resolution) resulting in 138 and 67 projections respectively. Reconstruction was carried out using 3 Methods: conventional FDK, iterative penalized least-square (PWLS) with total variation (TV), and PWLS with edge-preserving penalty. The performance of the methods was compared using contrast-to-noise (CNR) in a region of interest (ROI). Line profile through a specific region was plotted to evaluate the preserving of edges. Results: In both the cases with 4 and 6 phases, inadequate and non-uniform angular sampling results in artifacts using conventional FDK. However, such artifacts are minimized using both the iterative methods. Using both 4 and 6 phases, the iterative techniques outperformed FDK in terms of CNR and maintaining sharp edges. This is further evidenced especially with increased artifacts using FDK for 6 phases. Conclusion: This work indicates fewer artifacts and better image details can be achieved with iterative reconstruction methods in non-uniform under-sampled reconstruction. Using iterative methods can enable free-breathing intrinsic respiratory gating in small-animal CT. Further studies are needed to compare the

Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique

Energy Technology Data Exchange (ETDEWEB)

Katsura, Masaki; Matsuda, Izuru; Akahane, Masaaki; Sato, Jiro; Akai, Hiroyuki; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni [University of Tokyo, Department of Radiology, Graduate School of Medicine, Bunkyo-ku, Tokyo (Japan)

2012-08-15

To prospectively evaluate dose reduction and image quality characteristics of chest CT reconstructed with model-based iterative reconstruction (MBIR) compared with adaptive statistical iterative reconstruction (ASIR). One hundred patients underwent reference-dose and low-dose unenhanced chest CT with 64-row multidetector CT. Images were reconstructed with 50 % ASIR-filtered back projection blending (ASIR50) for reference-dose CT, and with ASIR50 and MBIR for low-dose CT. Two radiologists assessed the images in a blinded manner for subjective image noise, artefacts and diagnostic acceptability. Objective image noise was measured in the lung parenchyma. Data were analysed using the sign test and pair-wise Student's t-test. Compared with reference-dose CT, there was a 79.0 % decrease in dose-length product with low-dose CT. Low-dose MBIR images had significantly lower objective image noise (16.93 {+-} 3.00) than low-dose ASIR (49.24 {+-} 9.11, P < 0.01) and reference-dose ASIR images (24.93 {+-} 4.65, P < 0.01). Low-dose MBIR images were all diagnostically acceptable. Unique features of low-dose MBIR images included motion artefacts and pixellated blotchy appearances, which did not adversely affect diagnostic acceptability. Diagnostically acceptable chest CT images acquired with nearly 80 % less radiation can be obtained using MBIR. MBIR shows greater potential than ASIR for providing diagnostically acceptable low-dose CT images without severely compromising image quality. (orig.)

Adaptive patch-based POCS approach for super resolution reconstruction of 4D-CT lung data

International Nuclear Information System (INIS)

Wang, Tingting; Cao, Lei; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

2015-01-01

Image enhancement of lung four-dimensional computed tomography (4D-CT) data is highly important because image resolution remains a crucial point in lung cancer radiotherapy. In this paper, we proposed a method for lung 4D-CT super resolution (SR) by using an adaptive-patch-based projection onto convex sets (POCS) approach, which is in contrast with the global POCS SR algorithm, to recover fine details with lesser artifacts in images. The main contribution of this patch-based approach is that the interfering local structure from other phases can be rejected by employing a similar patch adaptive selection strategy. The effectiveness of our approach is demonstrated through experiments on simulated images and real lung 4D-CT datasets. A comparison with previously published SR reconstruction methods highlights the favorable characteristics of the proposed method. (paper)

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

Science.gov (United States)

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

2017-08-01

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

Duality reconstruction algorithm for use in electrical impedance tomography

International Nuclear Information System (INIS)

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

1996-01-01

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

Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

Science.gov (United States)

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.

Feature constrained compressed sensing CT image reconstruction from incomplete data via robust principal component analysis of the database

International Nuclear Information System (INIS)

Wu, Dufan; Li, Liang; Zhang, Li

2013-01-01

In computed tomography (CT), incomplete data problems such as limited angle projections often cause artifacts in the reconstruction results. Additional prior knowledge of the image has shown the potential for better results, such as a prior image constrained compressed sensing algorithm. While a pre-full-scan of the same patient is not always available, massive well-reconstructed images of different patients can be easily obtained from clinical multi-slice helical CTs. In this paper, a feature constrained compressed sensing (FCCS) image reconstruction algorithm was proposed to improve the image quality by using the prior knowledge extracted from the clinical database. The database consists of instances which are similar to the target image but not necessarily the same. Robust principal component analysis is employed to retrieve features of the training images to sparsify the target image. The features form a low-dimensional linear space and a constraint on the distance between the image and the space is used. A bi-criterion convex program which combines the feature constraint and total variation constraint is proposed for the reconstruction procedure and a flexible method is adopted for a good solution. Numerical simulations on both the phantom and real clinical patient images were taken to validate our algorithm. Promising results are shown for limited angle problems. (paper)

l0 regularization based on a prior image incorporated non-local means for limited-angle X-ray CT reconstruction.

Science.gov (United States)

Zhang, Lingli; Zeng, Li; Guo, Yumeng

2018-03-15

Restricted by the scanning environment in some CT imaging modalities, the acquired projection data are usually incomplete, which may lead to a limited-angle reconstruction problem. Thus, image quality usually suffers from the slope artifacts. The objective of this study is to first investigate the distorted domains of the reconstructed images which encounter the slope artifacts and then present a new iterative reconstruction method to address the limited-angle X-ray CT reconstruction problem. The presented framework of new method exploits the structural similarity between the prior image and the reconstructed image aiming to compensate the distorted edges. Specifically, the new method utilizes l0 regularization and wavelet tight framelets to suppress the slope artifacts and pursue the sparsity. New method includes following 4 steps to (1) address the data fidelity using SART; (2) compensate for the slope artifacts due to the missed projection data using the prior image and modified nonlocal means (PNLM); (3) utilize l0 regularization to suppress the slope artifacts and pursue the sparsity of wavelet coefficients of the transformed image by using iterative hard thresholding (l0W); and (4) apply an inverse wavelet transform to reconstruct image. In summary, this method is referred to as "l0W-PNLM". Numerical implementations showed that the presented l0W-PNLM was superior to suppress the slope artifacts while preserving the edges of some features as compared to the commercial and other popular investigative algorithms. When the image to be reconstructed is inconsistent with the prior image, the new method can avoid or minimize the distorted edges in the reconstructed images. Quantitative assessments also showed that applying the new method obtained the highest image quality comparing to the existing algorithms. This study demonstrated that the presented l0W-PNLM yielded higher image quality due to a number of unique characteristics, which include that (1) it utilizes

Effects of defect pixel correction algorithms for x-ray detectors on image quality in planar projection and volumetric CT data sets

International Nuclear Information System (INIS)

Kuttig, Jan; Steiding, Christian; Hupfer, Martin; Karolczak, Marek; Kolditz, Daniel

2015-01-01

In this study we compared various defect pixel correction methods for reducing artifact appearance within projection images used for computed tomography (CT) reconstructions.Defect pixel correction algorithms were examined with respect to their artifact behaviour within planar projection images as well as in volumetric CT reconstructions. We investigated four algorithms: nearest neighbour, linear and adaptive linear interpolation, and a frequency-selective spectral-domain approach.To characterise the quality of each algorithm in planar image data, we inserted line defects of varying widths and orientations into images. The structure preservation of each algorithm was analysed by corrupting and correcting the image of a slit phantom pattern and by evaluating its line spread function (LSF). The noise preservation was assessed by interpolating corrupted flat images and estimating the noise power spectrum (NPS) of the interpolated region.For the volumetric investigations, we examined the structure and noise preservation within a structured aluminium foam, a mid-contrast cone-beam phantom and a homogeneous Polyurethane (PUR) cylinder.The frequency-selective algorithm showed the best structure and noise preservation for planar data of the correction methods tested. For volumetric data it still showed the best noise preservation, whereas the structure preservation was outperformed by the linear interpolation.The frequency-selective spectral-domain approach in the correction of line defects is recommended for planar image data, but its abilities within high-contrast volumes are restricted. In that case, the application of a simple linear interpolation might be the better choice to correct line defects within projection images used for CT. (paper)

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.)

Speeding up image reconstruction in computed tomography

CERN Multimedia

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...

Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique

International Nuclear Information System (INIS)

Katsura, Masaki; Matsuda, Izuru; Akahane, Masaaki; Sato, Jiro; Akai, Hiroyuki; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni

2012-01-01

To prospectively evaluate dose reduction and image quality characteristics of chest CT reconstructed with model-based iterative reconstruction (MBIR) compared with adaptive statistical iterative reconstruction (ASIR). One hundred patients underwent reference-dose and low-dose unenhanced chest CT with 64-row multidetector CT. Images were reconstructed with 50 % ASIR-filtered back projection blending (ASIR50) for reference-dose CT, and with ASIR50 and MBIR for low-dose CT. Two radiologists assessed the images in a blinded manner for subjective image noise, artefacts and diagnostic acceptability. Objective image noise was measured in the lung parenchyma. Data were analysed using the sign test and pair-wise Student's t-test. Compared with reference-dose CT, there was a 79.0 % decrease in dose-length product with low-dose CT. Low-dose MBIR images had significantly lower objective image noise (16.93 ± 3.00) than low-dose ASIR (49.24 ± 9.11, P < 0.01) and reference-dose ASIR images (24.93 ± 4.65, P < 0.01). Low-dose MBIR images were all diagnostically acceptable. Unique features of low-dose MBIR images included motion artefacts and pixellated blotchy appearances, which did not adversely affect diagnostic acceptability. Diagnostically acceptable chest CT images acquired with nearly 80 % less radiation can be obtained using MBIR. MBIR shows greater potential than ASIR for providing diagnostically acceptable low-dose CT images without severely compromising image quality. (orig.)

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)

Model-based iterative reconstruction and adaptive statistical iterative reconstruction: dose-reduced CT for detecting pancreatic calcification

International Nuclear Information System (INIS)

Yasaka, Koichiro; Katsura, Masaki; Akahane, Masaaki; Sato, Jiro; Matsuda, Izuru; Ohtomo, Kuni

2016-01-01

Iterative reconstruction methods have attracted attention for reducing radiation doses in computed tomography (CT). To investigate the detectability of pancreatic calcification using dose-reduced CT reconstructed with model-based iterative construction (MBIR) and adaptive statistical iterative reconstruction (ASIR). This prospective study approved by Institutional Review Board included 85 patients (57 men, 28 women; mean age, 69.9 years; mean body weight, 61.2 kg). Unenhanced CT was performed three times with different radiation doses (reference-dose CT [RDCT], low-dose CT [LDCT], ultralow-dose CT [ULDCT]). From RDCT, LDCT, and ULDCT, images were reconstructed with filtered-back projection (R-FBP, used for establishing reference standard), ASIR (L-ASIR), and MBIR and ASIR (UL-MBIR and UL-ASIR), respectively. A lesion (pancreatic calcification) detection test was performed by two blinded radiologists with a five-point certainty level scale. Dose-length products of RDCT, LDCT, and ULDCT were 410, 97, and 36 mGy-cm, respectively. Nine patients had pancreatic calcification. The sensitivity for detecting pancreatic calcification with UL-MBIR was high (0.67–0.89) compared to L-ASIR or UL-ASIR (0.11–0.44), and a significant difference was seen between UL-MBIR and UL-ASIR for one reader (P = 0.014). The area under the receiver-operating characteristic curve for UL-MBIR (0.818–0.860) was comparable to that for L-ASIR (0.696–0.844). The specificity was lower with UL-MBIR (0.79–0.92) than with L-ASIR or UL-ASIR (0.96–0.99), and a significant difference was seen for one reader (P < 0.01). In UL-MBIR, pancreatic calcification can be detected with high sensitivity, however, we should pay attention to the slightly lower specificity

Model-based iterative reconstruction and adaptive statistical iterative reconstruction: dose-reduced CT for detecting pancreatic calcification.

Science.gov (United States)

Yasaka, Koichiro; Katsura, Masaki; Akahane, Masaaki; Sato, Jiro; Matsuda, Izuru; Ohtomo, Kuni

2016-01-01

Iterative reconstruction methods have attracted attention for reducing radiation doses in computed tomography (CT). To investigate the detectability of pancreatic calcification using dose-reduced CT reconstructed with model-based iterative construction (MBIR) and adaptive statistical iterative reconstruction (ASIR). This prospective study approved by Institutional Review Board included 85 patients (57 men, 28 women; mean age, 69.9 years; mean body weight, 61.2 kg). Unenhanced CT was performed three times with different radiation doses (reference-dose CT [RDCT], low-dose CT [LDCT], ultralow-dose CT [ULDCT]). From RDCT, LDCT, and ULDCT, images were reconstructed with filtered-back projection (R-FBP, used for establishing reference standard), ASIR (L-ASIR), and MBIR and ASIR (UL-MBIR and UL-ASIR), respectively. A lesion (pancreatic calcification) detection test was performed by two blinded radiologists with a five-point certainty level scale. Dose-length products of RDCT, LDCT, and ULDCT were 410, 97, and 36 mGy-cm, respectively. Nine patients had pancreatic calcification. The sensitivity for detecting pancreatic calcification with UL-MBIR was high (0.67-0.89) compared to L-ASIR or UL-ASIR (0.11-0.44), and a significant difference was seen between UL-MBIR and UL-ASIR for one reader (P = 0.014). The area under the receiver-operating characteristic curve for UL-MBIR (0.818-0.860) was comparable to that for L-ASIR (0.696-0.844). The specificity was lower with UL-MBIR (0.79-0.92) than with L-ASIR or UL-ASIR (0.96-0.99), and a significant difference was seen for one reader (P < 0.01). In UL-MBIR, pancreatic calcification can be detected with high sensitivity, however, we should pay attention to the slightly lower specificity.

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

Applicability of 3D-CT facial reconstruction for forensic individual identification

Energy Technology Data Exchange (ETDEWEB)

Rocha, Sara dos Santos [Sao Paulo Univ., SP (Brazil). Odontologia Forense; Ramos, Dalton Luiz de Paula [Sao Paulo Univ., SP (Brazil). Dept. of Odontologia Social; Cavalcanti, Marcelo de Gusmao Paraiso [Sao Paulo Univ., SP (Brazil). Dept. de Radiologia

2003-03-01

Computed tomography (CT) is used in several clinical dentistry applications even by axial slices and two and three-dimensional reconstructed images (2D-CT and 3D-CT). The purpose of the current study is to assess the precision of linear measurements made in 3D-CT using cranio metric patterns for individual identification in Forensic Dentistry. Five cadaver heads were submitted to a spiral computed tomography using axial slices, and 3D-CT reconstructions were obtained by volume rendering technique with computer graphics tools. Ten (10) cranio metric measurements were determined in 3D-CT images by two examiners independently, twice each, and the standard error of intra- and inter-examiner measurements was assessed. The results demonstrated a low standard error of those measurements, from 0.85% to 3.09%. In conclusion, the linear measurements obtained in osseous and soft tissue structures were considered to be precise in 3D-CT with high imaging quality and resolution. (author)

Applicability of 3D-CT facial reconstruction for forensic individual identification

International Nuclear Information System (INIS)

Rocha, Sara dos Santos; Ramos, Dalton Luiz de Paula; Cavalcanti, Marcelo de Gusmao Paraiso

2003-01-01

Computed tomography (CT) is used in several clinical dentistry applications even by axial slices and two and three-dimensional reconstructed images (2D-CT and 3D-CT). The purpose of the current study is to assess the precision of linear measurements made in 3D-CT using cranio metric patterns for individual identification in Forensic Dentistry. Five cadaver heads were submitted to a spiral computed tomography using axial slices, and 3D-CT reconstructions were obtained by volume rendering technique with computer graphics tools. Ten (10) cranio metric measurements were determined in 3D-CT images by two examiners independently, twice each, and the standard error of intra- and inter-examiner measurements was assessed. The results demonstrated a low standard error of those measurements, from 0.85% to 3.09%. In conclusion, the linear measurements obtained in osseous and soft tissue structures were considered to be precise in 3D-CT with high imaging quality and resolution. (author)

Accelerated barrier optimization compressed sensing (ABOCS) for CT reconstruction with improved convergence

International Nuclear Information System (INIS)

Niu, Tianye; Fruhauf, Quentin; Petrongolo, Michael; Zhu, Lei; Ye, Xiaojing

2014-01-01

Recently, we proposed a new algorithm of accelerated barrier optimization compressed sensing (ABOCS) for iterative CT reconstruction. The previous implementation of ABOCS uses gradient projection (GP) with a Barzilai–Borwein (BB) step-size selection scheme (GP-BB) to search for the optimal solution. The algorithm does not converge stably due to its non-monotonic behavior. In this paper, we further improve the convergence of ABOCS using the unknown-parameter Nesterov (UPN) method and investigate the ABOCS reconstruction performance on clinical patient data. Comparison studies are carried out on reconstructions of computer simulation, a physical phantom and a head-and-neck patient. In all of these studies, the ABOCS results using UPN show more stable and faster convergence than those of the GP-BB method and a state-of-the-art Bregman-type method. As shown in the simulation study of the Shepp–Logan phantom, UPN achieves the same image quality as those of GP-BB and the Bregman-type methods, but reduces the iteration numbers by up to 50% and 90%, respectively. In the Catphan©600 phantom study, a high-quality image with relative reconstruction error (RRE) less than 3% compared to the full-view result is obtained using UPN with 17% projections (60 views). In the conventional filtered-backprojection reconstruction, the corresponding RRE is more than 15% on the same projection data. The superior performance of ABOCS with the UPN implementation is further demonstrated on the head-and-neck patient. Using 25% projections (91 views), the proposed method reduces the RRE from 21% as in the filtered backprojection (FBP) results to 7.3%. In conclusion, we propose UPN for ABOCS implementation. As compared to GP-BB and the Bregman-type methods, the new method significantly improves the convergence with higher stability and fewer iterations. (paper)

Iterative concurrent reconstruction algorithms for emission computed tomography

International Nuclear Information System (INIS)

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

1994-01-01

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

Respiratory-gated segment reconstruction for radiation treatment planning using 256-slice CT-scanner during free breathing

Science.gov (United States)

Mori, Shinichiro; Endo, Masahiro; Kohno, Ryosuke; Minohara, Shinichi; Kohno, Kazutoshi; Asakura, Hiroshi; Fujiwara, Hideaki; Murase, Kenya

2005-04-01

The conventional respiratory-gated CT scan technique includes anatomic motion induced artifacts due to the low temporal resolution. They are a significant source of error in radiotherapy treatment planning for the thorax and upper abdomen. Temporal resolution and image quality are important factors to minimize planning target volume margin due to the respiratory motion. To achieve high temporal resolution and high signal-to-noise ratio, we developed a respiratory gated segment reconstruction algorithm and adapted it to Feldkamp-Davis-Kress algorithm (FDK) with a 256-detector row CT. The 256-detector row CT could scan approximately 100 mm in the cranio-caudal direction with 0.5 mm slice thickness in one rotation. Data acquisition for the RS-FDK relies on the assistance of the respiratory sensing system by a cine scan mode (table remains stationary). We evaluated RS-FDK in phantom study with the 256-detector row CT and compared it with full scan (FS-FDK) and HS-FDK results with regard to volume accuracy and image noise, and finally adapted the RS-FDK to an animal study. The RS-FDK gave a more accurate volume than the others and it had the same signal-to-noise ratio as the FS-FDK. In the animal study, the RS-FDK visualized the clearest edges of the liver and pulmonary vessels of all the algorithms. In conclusion, the RS-FDK algorithm has a capability of high temporal resolution and high signal-to-noise ratio. Therefore it will be useful when combined with new radiotherapy techniques including image guided radiation therapy (IGRT) and 4D radiation therapy.

Cone-beam local reconstruction based on a Radon inversion transformation

International Nuclear Information System (INIS)

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

2012-01-01

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