Can clinical CT data improve forensic reconstruction?

PubMed

Schuh, P; Scheurer, E; Fritz, K; Pavlic, M; Hassler, E; Rienmüller, R; Yen, K

2013-05-01

In accidents resulting in severe injuries, a clinical forensic examination is generally abandoned in the initial phase due to high-priority clinical needs. However, in many cases, data from clinical computed tomography (CT) examinations are available. The goals of this prospective study were (a) to evaluate clinical CT data as a basis for forensic reconstruction of the sequence of events, (b) to assess if forensic radiological follow-up reading improves the forensic diagnostic benefit compared to the written clinical radiological reports, and (c) to evaluate if full data storage including additional reconstructed 0.6-mm slices enhances forensic analysis. Clinical CT data of 15 living individuals with imaging of at least the head, thorax, and abdomen following polytrauma were examined regarding the forensic evaluation of the sequence of events. Additionally, 0.6-mm slices and 3D images were reconstructed for forensic purposes and used for the evaluation. At the forensic radiological readings, additional traumatic findings were observed in ten of the 15 patients. The main weakness of the clinical reports was that they were not detailed enough, particularly regarding the localization of injuries and description of wound morphology. In seven cases, however, forensic conclusions were possible on the basis of the written clinical reports, whereas in five cases forensic reconstruction required specific follow-up reading. The additional 0.6-mm slices were easily available and with improved 3D image quality and forensic diagnostics. In conclusion, the use of clinical CT data can considerably support forensic expertise regarding reconstruction issues. Forensic follow-up reading as well as the use of additional thin slices for 3D analysis can further improve its benefit for forensic reconstruction purposes.

CT image reconstruction with half precision floating-point values.

PubMed

Maaß, Clemens; Baer, Matthias; Kachelrieß, Marc

2011-07-01

Analytic CT image reconstruction is a computationally demanding task. Currently, the even more demanding iterative reconstruction algorithms find their way into clinical routine because their image quality is superior to analytic image reconstruction. The authors thoroughly analyze a so far unconsidered but valuable tool of tomorrow's reconstruction hardware (CPU and GPU) that allows implementing the forward projection and backprojection steps, which are the computationally most demanding parts of any reconstruction algorithm, much more efficiently. Instead of the standard 32 bit floating-point values (float), a recently standardized floating-point value with 16 bit (half) is adopted for data representation in image domain and in rawdata domain. The reduction in the total data amount reduces the traffic on the memory bus, which is the bottleneck of today's high-performance algorithms, by 50%. In CT simulations and CT measurements, float reconstructions (gold standard) and half reconstructions are visually compared via difference images and by quantitative image quality evaluation. This is done for analytical reconstruction (filtered backprojection) and iterative reconstruction (ordered subset SART). The magnitude of quantization noise, which is caused by a reduction in the data precision of both rawdata and image data during image reconstruction, is negligible. This is clearly shown for filtered backprojection and iterative ordered subset SART reconstruction. In filtered backprojection, the implementation of the backprojection should be optimized for low data precision if the image data are represented in half format. In ordered subset SART image reconstruction, no adaptations are necessary and the convergence speed remains unchanged. Half precision floating-point values allow to speed up CT image reconstruction without compromising image quality.

Shading correction assisted iterative cone-beam CT reconstruction

NASA Astrophysics Data System (ADS)

Yang, Chunlin; Wu, Pengwei; Gong, Shutao; Wang, Jing; Lyu, Qihui; Tang, Xiangyang; Niu, Tianye

2017-11-01

Recent advances in total variation (TV) technology enable accurate CT image reconstruction from highly under-sampled and noisy projection data. The standard iterative reconstruction algorithms, which work well in conventional CT imaging, fail to perform as expected in cone beam CT (CBCT) applications, wherein the non-ideal physics issues, including scatter and beam hardening, are more severe. These physics issues result in large areas of shading artifacts and cause deterioration to the piecewise constant property assumed in reconstructed images. To overcome this obstacle, we incorporate a shading correction scheme into low-dose CBCT reconstruction and propose a clinically acceptable and stable three-dimensional iterative reconstruction method that is referred to as the shading correction assisted iterative reconstruction. In the proposed method, we modify the TV regularization term by adding a shading compensation image to the reconstructed image to compensate for the shading artifacts while leaving the data fidelity term intact. This compensation image is generated empirically, using image segmentation and low-pass filtering, and updated in the iterative process whenever necessary. When the compensation image is determined, the objective function is minimized using the fast iterative shrinkage-thresholding algorithm accelerated on a graphic processing unit. The proposed method is evaluated using CBCT projection data of the Catphan© 600 phantom and two pelvis patients. Compared with the iterative reconstruction without shading correction, the proposed method reduces the overall CT number error from around 200 HU to be around 25 HU and increases the spatial uniformity by a factor of 20 percent, given the same number of sparsely sampled projections. A clinically acceptable and stable iterative reconstruction algorithm for CBCT is proposed in this paper. Differing from the existing algorithms, this algorithm incorporates a shading correction scheme into the low

CT reconstruction techniques for improved accuracy of lung CT airway measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, A.; Ranallo, F. N.; Judy, P. F.

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 betweenmore » 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

Investigation of iterative image reconstruction in low-dose breast CT

NASA Astrophysics Data System (ADS)

Bian, Junguo; Yang, Kai; Boone, John M.; Han, Xiao; Sidky, Emil Y.; Pan, Xiaochuan

2014-06-01

There is interest in developing computed tomography (CT) dedicated to breast-cancer imaging. Because breast tissues are radiation-sensitive, the total radiation exposure in a breast-CT scan is kept low, often comparable to a typical two-view mammography exam, thus resulting in a challenging low-dose-data-reconstruction problem. In recent years, evidence has been found that suggests that iterative reconstruction may yield images of improved quality from low-dose data. In this work, based upon the constrained image total-variation minimization program and its numerical solver, i.e., the adaptive steepest descent-projection onto the convex set (ASD-POCS), we investigate and evaluate iterative image reconstructions from low-dose breast-CT data of patients, with a focus on identifying and determining key reconstruction parameters, devising surrogate utility metrics for characterizing reconstruction quality, and tailoring the program and ASD-POCS to the specific reconstruction task under consideration. The ASD-POCS reconstructions appear to outperform the corresponding clinical FDK reconstructions, in terms of subjective visualization and surrogate utility metrics.

Limiting CT radiation dose in children with craniosynostosis: phantom study using model-based iterative reconstruction.

PubMed

Kaasalainen, Touko; Palmu, Kirsi; Lampinen, Anniina; Reijonen, Vappu; Leikola, Junnu; Kivisaari, Riku; Kortesniemi, Mika

2015-09-01

Medical professionals need to exercise particular caution when developing CT scanning protocols for children who require multiple CT studies, such as those with craniosynostosis. To evaluate the utility of ultra-low-dose CT protocols with model-based iterative reconstruction techniques for craniosynostosis imaging. We scanned two pediatric anthropomorphic phantoms with a 64-slice CT scanner using different low-dose protocols for craniosynostosis. We measured organ doses in the head region with metal-oxide-semiconductor field-effect transistor (MOSFET) dosimeters. Numerical simulations served to estimate organ and effective doses. We objectively and subjectively evaluated the quality of images produced by adaptive statistical iterative reconstruction (ASiR) 30%, ASiR 50% and Veo (all by GE Healthcare, Waukesha, WI). Image noise and contrast were determined for different tissues. Mean organ dose with the newborn phantom was decreased up to 83% compared to the routine protocol when using ultra-low-dose scanning settings. Similarly, for the 5-year phantom the greatest radiation dose reduction was 88%. The numerical simulations supported the findings with MOSFET measurements. The image quality remained adequate with Veo reconstruction, even at the lowest dose level. Craniosynostosis CT with model-based iterative reconstruction could be performed with a 20-μSv effective dose, corresponding to the radiation exposure of plain skull radiography, without compromising required image quality.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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. 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 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (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. 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

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

PubMed Central

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

Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET

NASA Astrophysics Data System (ADS)

Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan

2016-02-01

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

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

PubMed Central

Grosser, Oliver S.; Kupitz, Dennis; Ruf, Juri; Czuczwara, Damian; Steffen, Ingo G.; Furth, Christian; Thormann, Markus; Loewenthal, David; Ricke, Jens; Amthauer, Holger

2015-01-01

Background 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. Methodology/Principal Findings 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). Conclusion/Significance 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. PMID:26390216

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

PubMed

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.

Deformable known component model-based reconstruction for coronary CT angiography

NASA Astrophysics Data System (ADS)

Zhang, X.; Tilley, S.; Xu, S.; Mathews, A.; McVeigh, E. R.; Stayman, J. W.

2017-03-01

Purpose: Atherosclerosis detection remains challenging in coronary CT angiography for patients with cardiac implants. Pacing electrodes of a pacemaker or lead components of a defibrillator can create substantial blooming and streak artifacts in the heart region, severely hindering the visualization of a plaque of interest. We present a novel reconstruction method that incorporates a deformable model for metal leads to eliminate metal artifacts and improve anatomy visualization even near the boundary of the component. Methods: The proposed reconstruction method, referred as STF-dKCR, includes a novel parameterization of the component that integrates deformation, a 3D-2D preregistration process that estimates component shape and position, and a polyenergetic forward model for x-ray propagation through the component where the spectral properties are jointly estimated. The methodology was tested on physical data of a cardiac phantom acquired on a CBCT testbench. The phantom included a simulated vessel, a metal wire emulating a pacing lead, and a small Teflon sphere attached to the vessel wall, mimicking a calcified plaque. The proposed method was also compared to the traditional FBP reconstruction and an interpolation-based metal correction method (FBP-MAR). Results: Metal artifacts presented in standard FBP reconstruction were significantly reduced in both FBP-MAR and STF- dKCR, yet only the STF-dKCR approach significantly improved the visibility of the small Teflon target (within 2 mm of the metal wire). The attenuation of the Teflon bead improved to 0.0481 mm-1 with STF-dKCR from 0.0166 mm-1 with FBP and from 0.0301 mm-1 with FBP-MAR - much closer to the expected 0.0414 mm-1. Conclusion: The proposed method has the potential to improve plaque visualization in coronary CT angiography in the presence of wire-shaped metal components.

Automatic estimation of detector radial position for contoured SPECT acquisition using CT images on a SPECT/CT system.

PubMed

Liu, Ruijie Rachel; Erwin, William D

2006-08-01

An algorithm was developed to estimate noncircular orbit (NCO) single-photon emission computed tomography (SPECT) detector radius on a SPECT/CT imaging system using the CT images, for incorporation into collimator resolution modeling for iterative SPECT reconstruction. Simulated male abdominal (arms up), male head and neck (arms down) and female chest (arms down) anthropomorphic phantom, and ten patient, medium-energy SPECT/CT scans were acquired on a hybrid imaging system. The algorithm simulated inward SPECT detector radial motion and object contour detection at each projection angle, employing the calculated average CT image and a fixed Hounsfield unit (HU) threshold. Calculated radii were compared to the observed true radii, and optimal CT threshold values, corresponding to patient bed and clothing surfaces, were found to be between -970 and -950 HU. The algorithm was constrained by the 45 cm CT field-of-view (FOV), which limited the detected radii to < or = 22.5 cm and led to occasional radius underestimation in the case of object truncation by CT. Two methods incorporating the algorithm were implemented: physical model (PM) and best fit (BF). The PM method computed an offset that produced maximum overlap of calculated and true radii for the phantom scans, and applied that offset as a calculated-to-true radius transformation. For the BF method, the calculated-to-true radius transformation was based upon a linear regression between calculated and true radii. For the PM method, a fixed offset of +2.75 cm provided maximum calculated-to-true radius overlap for the phantom study, which accounted for the camera system's object contour detect sensor surface-to-detector face distance. For the BF method, a linear regression of true versus calculated radius from a reference patient scan was used as a calculated-to-true radius transform. Both methods were applied to ten patient scans. For -970 and -950 HU thresholds, the combined overall average root-mean-square (rms

Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

PubMed Central

Tian, Zhen; Jia, Xun; Yuan, Kehong; Pan, Tinsu; Jiang, Steve B.

2014-01-01

High radiation dose in CT scans increases a lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with Total Variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing an energy consisting of an edge-preserving TV norm and a data fidelity term posed by the x-ray projections. The edge-preserving TV term is proposed to preferentially perform smoothing only on non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original total variation norm. During the reconstruction process, the pixels at edges would be gradually identified and given small penalty weight. Our iterative algorithm is implemented on GPU to improve its speed. We test our reconstruction algorithm on a digital NCAT phantom, a physical chest phantom, and a Catphan phantom. Reconstruction results from a conventional FBP algorithm and a TV regularization method without edge preserving penalty are also presented for comparison purpose. The experimental results illustrate that both TV-based algorithm and our edge-preserving TV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under the low dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low contrast structures and therefore maintain acceptable spatial resolution. PMID:21860076

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

PubMed

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 < 0.0005), low-dose FBP CT (30.9 ± 3.9 HU, p < 0.0005), and

Integration of prior CT into CBCT reconstruction for improved image quality via reconstruction of difference: first patient studies

NASA Astrophysics Data System (ADS)

Zhang, Hao; Gang, Grace J.; Lee, Junghoon; Wong, John; Stayman, J. Webster

2017-03-01

Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.

Spectrotemporal CT data acquisition and reconstruction at low dose

PubMed Central

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

2015-01-01

Purpose: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D + dual energy + time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. Methods: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction

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

PubMed

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 p<0.01). UL-MBIR was significantly better for subjective image noise and streak artifacts than L-ASIR and UL-ASIR (all p<0.01). There were no significant differences between UL-MBIR and L-ASIR 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.

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

PubMed

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.

A limited-angle CT reconstruction method based on anisotropic TV minimization.

PubMed

Chen, Zhiqiang; Jin, Xin; Li, Liang; Wang, Ge

2013-04-07

This paper presents a compressed sensing (CS)-inspired reconstruction method for limited-angle computed tomography (CT). Currently, CS-inspired CT reconstructions are often performed by minimizing the total variation (TV) of a CT image subject to data consistency. A key to obtaining high image quality is to optimize the balance between TV-based smoothing and data fidelity. In the case of the limited-angle CT problem, the strength of data consistency is angularly varying. For example, given a parallel beam of x-rays, information extracted in the Fourier domain is mostly orthogonal to the direction of x-rays, while little is probed otherwise. However, the TV minimization process is isotropic, suggesting that it is unfit for limited-angle CT. Here we introduce an anisotropic TV minimization method to address this challenge. The advantage of our approach is demonstrated in numerical simulation with both phantom and real CT images, relative to the TV-based reconstruction.

Tensor-based Dictionary Learning for Spectral CT Reconstruction

PubMed Central

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

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

PubMed Central

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 < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% 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

Region-of-interest image reconstruction in circular cone-beam microCT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, Seungryong; Bian, Junguo; Pelizzari, Charles A.

2007-12-15

Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolutionmore » entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.« less

Reduced Radiation Dose with Model-based Iterative Reconstruction versus Standard Dose with Adaptive Statistical Iterative Reconstruction in Abdominal CT for Diagnosis of Acute Renal Colic.

PubMed

Fontarensky, Mikael; Alfidja, Agaïcha; Perignon, Renan; Schoenig, Arnaud; Perrier, Christophe; Mulliez, Aurélien; Guy, Laurent; Boyer, Louis

2015-07-01

To evaluate the accuracy of reduced-dose abdominal computed tomographic (CT) imaging by using a new generation model-based iterative reconstruction (MBIR) to diagnose acute renal colic compared with a standard-dose abdominal CT with 50% adaptive statistical iterative reconstruction (ASIR). This institutional review board-approved prospective study included 118 patients with symptoms of acute renal colic who underwent the following two successive CT examinations: standard-dose ASIR 50% and reduced-dose MBIR. Two radiologists independently reviewed both CT examinations for presence or absence of renal calculi, differential diagnoses, and associated abnormalities. The imaging findings, radiation dose estimates, and image quality of the two CT reconstruction methods were compared. Concordance was evaluated by κ coefficient, and descriptive statistics and t test were used for statistical analysis. Intraobserver correlation was 100% for the diagnosis of renal calculi (κ = 1). Renal calculus (τ = 98.7%; κ = 0.97) and obstructive upper urinary tract disease (τ = 98.16%; κ = 0.95) were detected, and differential or alternative diagnosis was performed (τ = 98.87% κ = 0.95). MBIR allowed a dose reduction of 84% versus standard-dose ASIR 50% (mean volume CT dose index, 1.7 mGy ± 0.8 [standard deviation] vs 10.9 mGy ± 4.6; mean size-specific dose estimate, 2.2 mGy ± 0.7 vs 13.7 mGy ± 3.9; P < .001) without a conspicuous deterioration in image quality (reduced-dose MBIR vs ASIR 50% mean scores, 3.83 ± 0.49 vs 3.92 ± 0.27, respectively; P = .32) or increase in noise (reduced-dose MBIR vs ASIR 50% mean, respectively, 18.36 HU ± 2.53 vs 17.40 HU ± 3.42). Its main drawback remains the long time required for reconstruction (mean, 40 minutes). A reduced-dose protocol with MBIR allowed a dose reduction of 84% without increasing noise and without an conspicuous deterioration in image quality in patients suspected of having renal colic.

Accurate tissue characterization in low-dose CT imaging with pure iterative reconstruction.

PubMed

Murphy, Kevin P; McLaughlin, Patrick D; Twomey, Maria; Chan, Vincent E; Moloney, Fiachra; Fung, Adrian J; Chan, Faimee E; Kao, Tafline; O'Neill, Siobhan B; Watson, Benjamin; O'Connor, Owen J; Maher, Michael M

2017-04-01

We assess the ability of low-dose hybrid iterative reconstruction (IR) and 'pure' model-based IR (MBIR) images to maintain accurate Hounsfield unit (HU)-determined tissue characterization. Standard-protocol (SP) and low-dose modified-protocol (MP) CTs were contemporaneously acquired in 34 Crohn's disease patients referred for CT. SP image reconstruction was via the manufacturer's recommendations (60% FBP, filtered back projection; 40% ASiR, Adaptive Statistical iterative Reconstruction; SP-ASiR40). MP data sets underwent four reconstructions (100% FBP; 40% ASiR; 70% ASiR; MBIR). Three observers measured tissue volumes using HU thresholds for fat, soft tissue and bone/contrast on each data set. Analysis was via SPSS. Inter-observer agreement was strong for 1530 datapoints (rs > 0.9). MP-MBIR tissue volume measurement was superior to other MP reconstructions and closely correlated with the reference SP-ASiR40 images for all tissue types. MP-MBIR superiority was most marked for fat volume calculation - close SP-ASiR40 and MP-MBIR Bland-Altman plot correlation was seen with the lowest average difference (336 cm 3 ) when compared with other MP reconstructions. Hounsfield unit-determined tissue volume calculations from MP-MBIR images resulted in values comparable to SP-ASiR40 calculations and values that are superior to MP-ASiR images. Accuracy of estimation of volume of tissues (e.g. fat) using segmentation software on low-dose CT images appears optimal when reconstructed with pure IR. © 2016 The Royal Australian and New Zealand College of Radiologists.

Low-Dose X-ray CT Reconstruction via Dictionary Learning

PubMed Central

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

Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods.

PubMed

Young, Stefano; Kim, Hyun J Grace; Ko, Moe Moe; Ko, War War; Flores, Carlos; McNitt-Gray, Michael F

2015-05-01

Measuring the size of nodules on chest CT is important for lung cancer staging and measuring therapy response. 3D volumetry has been proposed as a more robust alternative to 1D and 2D sizing methods. There have also been substantial advances in methods to reduce radiation dose in CT. The purpose of this work was to investigate the effect of dose reduction and reconstruction methods on variability in 3D lung-nodule volumetry. Reduced-dose CT scans were simulated by applying a noise-addition tool to the raw (sinogram) data from clinically indicated patient scans acquired on a multidetector-row CT scanner (Definition Flash, Siemens Healthcare). Scans were simulated at 25%, 10%, and 3% of the dose of their clinical protocol (CTDIvol of 20.9 mGy), corresponding to CTDIvol values of 5.2, 2.1, and 0.6 mGy. Simulated reduced-dose data were reconstructed with both conventional filtered backprojection (B45 kernel) and iterative reconstruction methods (SAFIRE: I44 strength 3 and I50 strength 3). Three lab technologist readers contoured "measurable" nodules in 33 patients under each of the different acquisition/reconstruction conditions in a blinded study design. Of the 33 measurable nodules, 17 were used to estimate repeatability with their clinical reference protocol, as well as interdose and inter-reconstruction-method reproducibilities. The authors compared the resulting distributions of proportional differences across dose and reconstruction methods by analyzing their means, standard deviations (SDs), and t-test and F-test results. The clinical-dose repeatability experiment yielded a mean proportional difference of 1.1% and SD of 5.5%. The interdose reproducibility experiments gave mean differences ranging from -5.6% to -1.7% and SDs ranging from 6.3% to 9.9%. The inter-reconstruction-method reproducibility experiments gave mean differences of 2.0% (I44 strength 3) and -0.3% (I50 strength 3), and SDs were identical at 7.3%. For the subset of repeatability cases, inter-reconstruction

Potential benefit of the CT adaptive statistical iterative reconstruction method for pediatric cardiac diagnosis

NASA Astrophysics Data System (ADS)

Miéville, Frédéric A.; Ayestaran, Paul; Argaud, Christophe; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Gudinchet, François; Bochud, François; Verdun, Francis R.

2010-04-01

Adaptive Statistical Iterative Reconstruction (ASIR) is a new imaging reconstruction technique recently introduced by General Electric (GE). This technique, when combined with a conventional filtered back-projection (FBP) approach, is able to improve the image noise reduction. To quantify the benefits provided on the image quality and the dose reduction by the ASIR method with respect to the pure FBP one, the standard deviation (SD), the modulation transfer function (MTF), the noise power spectrum (NPS), the image uniformity and the noise homogeneity were examined. Measurements were performed on a control quality phantom when varying the CT dose index (CTDIvol) and the reconstruction kernels. A 64-MDCT was employed and raw data were reconstructed with different percentages of ASIR on a CT console dedicated for ASIR reconstruction. Three radiologists also assessed a cardiac pediatric exam reconstructed with different ASIR percentages using the visual grading analysis (VGA) method. For the standard, soft and bone reconstruction kernels, the SD is reduced when the ASIR percentage increases up to 100% with a higher benefit for low CTDIvol. MTF medium frequencies were slightly enhanced and modifications of the NPS shape curve were observed. However for the pediatric cardiac CT exam, VGA scores indicate an upper limit of the ASIR benefit. 40% of ASIR was observed as the best trade-off between noise reduction and clinical realism of organ images. Using phantom results, 40% of ASIR corresponded to an estimated dose reduction of 30% under pediatric cardiac protocol conditions. In spite of this discrepancy between phantom and clinical results, the ASIR method is as an important option when considering the reduction of radiation dose, especially for pediatric patients.

Design of CT reconstruction kernel specifically for clinical lung imaging

NASA Astrophysics Data System (ADS)

Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

2005-04-01

In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM.

PubMed

Razifar, Pasha; Sandström, Mattias; Schnieder, Harald; Långström, Bengt; Maripuu, Enn; Bengtsson, Ewert; Bergström, Mats

2005-08-25

finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images. The combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

Scatter correction, intermediate view estimation and dose characterization in megavoltage cone-beam CT imaging

NASA Astrophysics Data System (ADS)

Sramek, Benjamin Koerner

The ability to deliver conformal dose distributions in radiation therapy through intensity modulation and the potential for tumor dose escalation to improve treatment outcome has necessitated an increase in localization accuracy of inter- and intra-fractional patient geometry. Megavoltage cone-beam CT imaging using the treatment beam and onboard electronic portal imaging device is one option currently being studied for implementation in image-guided radiation therapy. However, routine clinical use is predicated upon continued improvements in image quality and patient dose delivered during acquisition. The formal statement of hypothesis for this investigation was that the conformity of planned to delivered dose distributions in image-guided radiation therapy could be further enhanced through the application of kilovoltage scatter correction and intermediate view estimation techniques to megavoltage cone-beam CT imaging, and that normalized dose measurements could be acquired and inter-compared between multiple imaging geometries. The specific aims of this investigation were to: (1) incorporate the Feldkamp, Davis and Kress filtered backprojection algorithm into a program to reconstruct a voxelized linear attenuation coefficient dataset from a set of acquired megavoltage cone-beam CT projections, (2) characterize the effects on megavoltage cone-beam CT image quality resulting from the application of Intermediate View Interpolation and Intermediate View Reprojection techniques to limited-projection datasets, (3) incorporate the Scatter and Primary Estimation from Collimator Shadows (SPECS) algorithm into megavoltage cone-beam CT image reconstruction and determine the set of SPECS parameters which maximize image quality and quantitative accuracy, and (4) evaluate the normalized axial dose distributions received during megavoltage cone-beam CT image acquisition using radiochromic film and thermoluminescent dosimeter measurements in anthropomorphic pelvic and head and

Cervical vertebrae maturation index estimates on cone beam CT: 3D reconstructions vs sagittal sections.

PubMed

Bonfim, Marco A E; Costa, André L F; Fuziy, Acácio; Ximenez, Michel E L; Cotrim-Ferreira, Flávio A; Ferreira-Santos, Rívea I

2016-01-01

The aim of this study was to evaluate the performance of CBCT three-dimensional (3D) reconstructions and sagittal sections for estimates of cervical vertebrae maturation index (CVMI). The sample consisted of 72 CBCT examinations from patients aged 8-16 years (45 females and 27 males) selected from the archives of two private clinics. Two calibrated observers (kappa scores: ≥0.901) interpreted the CBCT settings twice. Intra- and interobserver agreement for both imaging exhibition modes was analyzed by kappa statistics, which was also used to analyze the agreement between 3D reconstructions and sagittal sections. Correlations between cervical vertebrae maturation estimates and chronological age, as well as between the assessments by 3D reconstructions and sagittal sections, were analyzed using gamma Goodman-Kruskal coefficients (α = 0.05). The kappa scores evidenced almost perfect agreement between the first and second assessments of the cervical vertebrae by 3D reconstructions (0.933-0.983) and sagittal sections (0.983-1.000). Similarly, the agreement between 3D reconstructions and sagittal sections was almost perfect (kappa index: 0.983). In most divergent cases, the difference between 3D reconstructions and sagittal sections was one stage of CVMI. Strongly positive correlations (>0.8, p < 0.001) were found not only between chronological age and CVMI but also between the estimates by 3D reconstructions and sagittal sections (p < 0.001). Although CBCT imaging must not be used exclusively for this purpose, it may be suitable for skeletal maturity assessments.

Cervical vertebrae maturation index estimates on cone beam CT: 3D reconstructions vs sagittal sections

PubMed Central

Bonfim, Marco A E; Costa, André L F; Ximenez, Michel E L; Cotrim-Ferreira, Flávio A; Ferreira-Santos, Rívea I

2016-01-01

Objectives: The aim of this study was to evaluate the performance of CBCT three-dimensional (3D) reconstructions and sagittal sections for estimates of cervical vertebrae maturation index (CVMI). Methods: The sample consisted of 72 CBCT examinations from patients aged 8–16 years (45 females and 27 males) selected from the archives of two private clinics. Two calibrated observers (kappa scores: ≥0.901) interpreted the CBCT settings twice. Intra- and interobserver agreement for both imaging exhibition modes was analyzed by kappa statistics, which was also used to analyze the agreement between 3D reconstructions and sagittal sections. Correlations between cervical vertebrae maturation estimates and chronological age, as well as between the assessments by 3D reconstructions and sagittal sections, were analyzed using gamma Goodman–Kruskal coefficients (α = 0.05). Results: The kappa scores evidenced almost perfect agreement between the first and second assessments of the cervical vertebrae by 3D reconstructions (0.933–0.983) and sagittal sections (0.983–1.000). Similarly, the agreement between 3D reconstructions and sagittal sections was almost perfect (kappa index: 0.983). In most divergent cases, the difference between 3D reconstructions and sagittal sections was one stage of CVMI. Strongly positive correlations (>0.8, p < 0.001) were found not only between chronological age and CVMI but also between the estimates by 3D reconstructions and sagittal sections (p < 0.001). Conclusions: Although CBCT imaging must not be used exclusively for this purpose, it may be suitable for skeletal maturity assessments. PMID:26509559

An iterative reconstruction method for high-pitch helical luggage CT

NASA Astrophysics Data System (ADS)

Xue, Hui; Zhang, Li; Chen, Zhiqiang; Jin, Xin

2012-10-01

X-ray luggage CT is widely used in airports and railway stations for the purpose of detecting contrabands and dangerous goods that may be potential threaten to public safety, playing an important role in homeland security. An X-ray luggage CT is usually in a helical trajectory with a high pitch for achieving a high passing speed of the luggage. The disadvantage of high pitch is that conventional filtered back-projection (FBP) requires a very large slice thickness, leading to bad axial resolution and helical artifacts. Especially when severe data inconsistencies are present in the z-direction, like the ends of a scanning object, the partial volume effect leads to inaccuracy value and may cause a wrong identification. In this paper, an iterative reconstruction method is developed to improve the image quality and accuracy for a large-spacing multi-detector high-pitch helical luggage CT system. In this method, the slice thickness is set to be much smaller than the pitch. Each slice involves projection data collected in a rather small angular range, being an ill-conditioned limited-angle problem. Firstly a low-resolution reconstruction is employed to obtain images, which are used as prior images in the following process. Then iterative reconstruction is performed to obtain high-resolution images. This method enables a high volume coverage speed and a thin reconstruction slice for the helical luggage CT. We validate this method with data collected in a commercial X-ray luggage CT.

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

PubMed

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.

Test of 3D CT reconstructions by EM + TV algorithm from undersampled data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da

2013-05-06

Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry withmore » alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.« less

Multienergy CT acquisition and reconstruction with a stepped tube potential scan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Le; Xing, Yuxiang, E-mail: xingyx@mail.tsinghua.edu.cn

Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT canmore » be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the

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

PubMed

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.

A New CT Reconstruction Technique Using Adaptive Deformation Recovery and Intensity Correction (ADRIC)

PubMed Central

Zhang, You; Ma, Jianhua; Iyengar, Puneeth; Zhong, Yuncheng; Wang, Jing

2017-01-01

Purpose Sequential same-patient CT images may involve deformation-induced and non-deformation-induced voxel intensity changes. An adaptive deformation recovery and intensity correction (ADRIC) technique was developed to improve the CT reconstruction accuracy, and to separate deformation from non-deformation-induced voxel intensity changes between sequential CT images. Materials and Methods ADRIC views the new CT volume as a deformation of a prior high-quality CT volume, but with additional non-deformation-induced voxel intensity changes. ADRIC first applies the 2D-3D deformation technique to recover the deformation field between the prior CT volume and the new, to-be-reconstructed CT volume. Using the deformation-recovered new CT volume, ADRIC further corrects the non-deformation-induced voxel intensity changes with an updated algebraic reconstruction technique (‘ART-dTV’). The resulting intensity-corrected new CT volume is subsequently fed back into the 2D-3D deformation process to further correct the residual deformation errors, which forms an iterative loop. By ADRIC, the deformation field and the non-deformation voxel intensity corrections are optimized separately and alternately to reconstruct the final CT. CT myocardial perfusion imaging scenarios were employed to evaluate the efficacy of ADRIC, using both simulated data of the extended-cardiac-torso (XCAT) digital phantom and experimentally acquired porcine data. The reconstruction accuracy of the ADRIC technique was compared to the technique using ART-dTV alone, and to the technique using 2D-3D deformation alone. The relative error metric and the universal quality index metric are calculated between the images for quantitative analysis. The relative error is defined as the square root of the sum of squared voxel intensity differences between the reconstructed volume and the ‘ground-truth’ volume, normalized by the square root of the sum of squared ‘ground-truth’ voxel intensities. In addition to

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

PubMed Central

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

2016-01-01

Background Iterative reconstruction methods have attracted attention for reducing radiation doses in computed tomography (CT). Purpose To investigate the detectability of pancreatic calcification using dose-reduced CT reconstructed with model-based iterative construction (MBIR) and adaptive statistical iterative reconstruction (ASIR). Material and Methods 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. Results 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). Conclusion In UL-MBIR, pancreatic calcification can be detected with high sensitivity, however, we should pay attention to the slightly lower specificity. PMID:27110389

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

PubMed

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.

The use of adaptive statistical iterative reconstruction in pediatric head CT: a feasibility study.

PubMed

Vorona, G A; Zuccoli, G; Sutcavage, T; Clayton, B L; Ceschin, R C; Panigrahy, A

2013-01-01

Iterative reconstruction techniques facilitate CT dose reduction; though to our knowledge, no group has explored using iterative reconstruction with pediatric head CT. Our purpose was to perform a feasibility study to assess the use of ASIR in a small group of pediatric patients undergoing head CT. An Alderson-Rando head phantom was scanned at decreasing 10% mA intervals relative to our standard protocol, and each study was then reconstructed at 10% ASIR intervals. An intracranial region of interest was consistently placed to estimate noise. Our ventriculoperitoneal shunt CT protocol was subsequently modified, and patients were scanned at 20% ASIR with approximately 20% mA reductions. ASIR studies were anonymously compared with older non-ASIR studies from the same patients by 2 attending pediatric neuroradiologists for diagnostic utility, sharpness, noise, and artifacts. The phantom study demonstrated similar noise at 100% mA/0% ASIR (3.9) and 80% mA/20% ASIR (3.7). Twelve pediatric patients were scanned at reduced dose at 20% ASIR. The average CTDI(vol) and DLP values of the 20% ASIR studies were 22.4 mGy and 338.4 mGy-cm, and for the non-ASIR studies, they were 28.8 mGy and 444.5 mGy-cm, representing statistically significant decreases in the CTDI(vol) (22.1%, P = .00007) and DLP (23.9%, P = .0005) values. There were no significant differences between the ASIR studies and non-ASIR studies with respect to diagnostic acceptability, sharpness, noise, or artifacts. Our findings suggest that 20% ASIR can provide approximately 22% dose reduction in pediatric head CT without affecting image quality.

Impact of the Adaptive Statistical Iterative Reconstruction Technique on Radiation Dose and Image Quality in Bone SPECT/CT.

PubMed

Sibille, Louis; Chambert, Benjamin; Alonso, Sandrine; Barrau, Corinne; D'Estanque, Emmanuel; Al Tabaa, Yassine; Collombier, Laurent; Demattei, Christophe; Kotzki, Pierre-Olivier; Boudousq, Vincent

2016-07-01

The purpose of this study was to compare a routine bone SPECT/CT protocol using CT reconstructed with filtered backprojection (FBP) with an optimized protocol using low-dose CT images reconstructed with adaptive statistical iterative reconstruction (ASiR). In this prospective study, enrolled patients underwent bone SPECT/CT, with 1 SPECT acquisition followed by 2 randomized CT acquisitions: FBP CT (FBP; noise index, 25) and ASiR CT (70% ASiR; noise index, 40). The image quality of both attenuation-corrected SPECT and CT images was visually (5-point Likert scale, 2 interpreters) and quantitatively (contrast ratio [CR] and signal-to-noise ratio [SNR]) estimated. The CT dose index volume, dose-length product, and effective dose were compared. Seventy-five patients were enrolled in the study. Quantitative attenuation-corrected SPECT evaluation showed no inferiority for contrast ratio and SNR issued from FBP CT or ASiR CT (respectively, 13.41 ± 7.83 vs. 13.45 ± 7.99 and 2.33 ± 0.83 vs. 2.32 ± 0.84). Qualitative image analysis showed no difference between attenuation-corrected SPECT images issued from FBP CT or ASiR CT for both interpreters (respectively, 3.5 ± 0.6 vs. 3.5 ± 0.6 and 3.6 ± 0.5 vs. 3.6 ± 0.5). Quantitative CT evaluation showed no inferiority for SNR between FBP and ASiR CT images (respectively, 0.93 ± 0.16 and 1.07 ± 0.17). Qualitative image analysis showed no quality difference between FBP and ASiR CT images for both interpreters (respectively, 3.8 ± 0.5 vs. 3.6 ± 0.5 and 4.0 ± 0.1 vs. 4.0 ± 0.2). Mean CT dose index volume, dose-length product, and effective dose for ASiR CT (3.0 ± 2.0 mGy, 148 ± 85 mGy⋅cm, and 2.2 ± 1.3 mSv) were significantly lower than for FBP CT (8.5 ± 3.7 mGy, 365 ± 160 mGy⋅cm, and 5.5 ± 2.4 mSv). The use of 70% ASiR blending in bone SPECT/CT can reduce the CT radiation dose by 60%, with no sacrifice in attenuation-corrected SPECT and CT image quality, compared with the conventional protocol using FBP CT

Micro-CT images reconstruction and 3D visualization for small animal studying

NASA Astrophysics Data System (ADS)

Gong, Hui; Liu, Qian; Zhong, Aijun; Ju, Shan; Fang, Quan; Fang, Zheng

2005-01-01

A small-animal x-ray micro computed tomography (micro-CT) system has been constructed to screen laboratory small animals and organs. The micro-CT system consists of dual fiber-optic taper-coupled CCD detectors with a field-of-view of 25x50 mm2, a microfocus x-ray source, a rotational subject holder. For accurate localization of rotation center, coincidence between the axis of rotation and centre of image was studied by calibration with a polymethylmethacrylate cylinder. Feldkamp"s filtered back-projection cone-beam algorithm is adopted for three-dimensional reconstruction on account of the effective corn-beam angle is 5.67° of the micro-CT system. 200x1024x1024 matrix data of micro-CT is obtained with the magnification of 1.77 and pixel size of 31x31μm2. In our reconstruction software, output image size of micro-CT slices data, magnification factor and rotation sample degree can be modified in the condition of different computational efficiency and reconstruction region. The reconstructed image matrix data is processed and visualization by Visualization Toolkit (VTK). Data parallelism of VTK is performed in surface rendering of reconstructed data in order to improve computing speed. Computing time of processing a 512x512x512 matrix datasets is about 1/20 compared with serial program when 30 CPU is used. The voxel size is 54x54x108 μm3. The reconstruction and 3-D visualization images of laboratory rat ear are presented.

Efficient iterative image reconstruction algorithm for dedicated breast CT

NASA Astrophysics Data System (ADS)

Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

2016-03-01

Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

Directional sinogram interpolation for motion weighted 4D cone-beam CT reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Hua; Kruis, Matthijs; Sonke, Jan-Jakob

2017-03-01

The image quality of respiratory sorted four-dimensional (4D) cone-beam (CB) computed tomography (CT) is often limited by streak artifacts due to insufficient projections. A motion weighted reconstruction (MWR) method is proposed to decrease streak artifacts and improve image quality. Firstly, respiratory correlated CBCT projections were interpolated by directional sinogram interpolation (DSI) to generate additional CB projections for each phase and subsequently reconstructed. Secondly, local motion was estimated by deformable image registration of the interpolated 4D CBCT. Thirdly, a regular 3D FDK CBCT was reconstructed from the non-interpolated projections. Finally, weights were assigned to each voxel, based on the local motion, and then were used to combine the 3D FDK CBCT and interpolated 4D CBCT to generate the final 4D image. MWR method was compared with regular 4D CBCT scans as well as McKinnon and Bates (MKB) based reconstructions. Comparisons were made in terms of (1) comparing the steepness of an extracted profile from the boundary of the region-of-interest (ROI), (2) contrast-to-noise ratio (CNR) inside certain ROIs, and (3) the root-mean-square-error (RMSE) between the planning CT and CBCT inside a homogeneous moving region. Comparisons were made for both a phantom and four patient scans. In a 4D phantom, RMSE were reduced by 24.7% and 38.7% for MKB and MWR respectively, compared to conventional 4D CBCT. Meanwhile, interpolation induced blur was minimal in static regions for MWR based reconstructions. In regions with considerable respiratory motion, image blur using MWR is less than the MKB and 3D Feldkamp (FDK) methods. In the lung cancer patients, average CNRs of MKB, DSI and MWR improved by a factor 1.7, 2.8 and 3.5 respectively relative to 4D FDK. MWR effectively reduces RMSE in 4D cone-beam CT and improves the image quality in both the static and respiratory moving regions compared to 4D FDK and MKB methods.

Directional sinogram interpolation for motion weighted 4D cone-beam CT reconstruction.

PubMed

Zhang, Hua; Kruis, Matthijs; Sonke, Jan-Jakob

2017-03-21

The image quality of respiratory sorted four-dimensional (4D) cone-beam (CB) computed tomography (CT) is often limited by streak artifacts due to insufficient projections. A motion weighted reconstruction (MWR) method is proposed to decrease streak artifacts and improve image quality. Firstly, respiratory correlated CBCT projections were interpolated by directional sinogram interpolation (DSI) to generate additional CB projections for each phase and subsequently reconstructed. Secondly, local motion was estimated by deformable image registration of the interpolated 4D CBCT. Thirdly, a regular 3D FDK CBCT was reconstructed from the non-interpolated projections. Finally, weights were assigned to each voxel, based on the local motion, and then were used to combine the 3D FDK CBCT and interpolated 4D CBCT to generate the final 4D image. MWR method was compared with regular 4D CBCT scans as well as McKinnon and Bates (MKB) based reconstructions. Comparisons were made in terms of (1) comparing the steepness of an extracted profile from the boundary of the region-of-interest (ROI), (2) contrast-to-noise ratio (CNR) inside certain ROIs, and (3) the root-mean-square-error (RMSE) between the planning CT and CBCT inside a homogeneous moving region. Comparisons were made for both a phantom and four patient scans. In a 4D phantom, RMSE were reduced by 24.7% and 38.7% for MKB and MWR respectively, compared to conventional 4D CBCT. Meanwhile, interpolation induced blur was minimal in static regions for MWR based reconstructions. In regions with considerable respiratory motion, image blur using MWR is less than the MKB and 3D Feldkamp (FDK) methods. In the lung cancer patients, average CNRs of MKB, DSI and MWR improved by a factor 1.7, 2.8 and 3.5 respectively relative to 4D FDK. MWR effectively reduces RMSE in 4D cone-beam CT and improves the image quality in both the static and respiratory moving regions compared to 4D FDK and MKB methods.

Image reconstruction for PET/CT scanners: past achievements and future challenges

PubMed Central

Tong, Shan; Alessio, Adam M; Kinahan, Paul E

2011-01-01

PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. PMID:21339831

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

PubMed

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

2015-10-01

To investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR. 27 consecutive patients (mean body mass index: 23.55 kg m(-2) underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded. At the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19-49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP. Abdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. This study represents the first clinical research experiment to use ASIR-V, the newest version of

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eck, Brendan L.; Fahmi, Rachid; Miao, Jun

2015-10-15

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated usingmore » a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade

Accuracy assessment of 3D bone reconstructions using CT: an intro comparison.

PubMed

Lalone, Emily A; Willing, Ryan T; Shannon, Hannah L; King, Graham J W; Johnson, James A

2015-08-01

Computed tomography provides high contrast imaging of the joint anatomy and is used routinely to reconstruct 3D models of the osseous and cartilage geometry (CT arthrography) for use in the design of orthopedic implants, for computer assisted surgeries and computational dynamic and structural analysis. The objective of this study was to assess the accuracy of bone and cartilage surface model reconstructions by comparing reconstructed geometries with bone digitizations obtained using an optical tracking system. Bone surface digitizations obtained in this study determined the ground truth measure for the underlying geometry. We evaluated the use of a commercially available reconstruction technique using clinical CT scanning protocols using the elbow joint as an example of a surface with complex geometry. To assess the accuracies of the reconstructed models (8 fresh frozen cadaveric specimens) against the ground truth bony digitization-as defined by this study-proximity mapping was used to calculate residual error. The overall mean error was less than 0.4 mm in the cortical region and 0.3 mm in the subchondral region of the bone. Similarly creating 3D cartilage surface models from CT scans using air contrast had a mean error of less than 0.3 mm. Results from this study indicate that clinical CT scanning protocols and commonly used and commercially available reconstruction algorithms can create models which accurately represent the true geometry. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, P; Mao, T; Gong, S

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 optimizationmore » 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

Technical Note: FreeCT_ICD: An Open Source Implementation of a Model-Based Iterative Reconstruction Method using Coordinate Descent Optimization for CT Imaging Investigations.

PubMed

Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael

2018-06-01

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric

GPU-accelerated regularized iterative reconstruction for few-view cone beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca; Després, Philippe, E-mail: philippe.despres@phy.ulaval.ca

2015-04-15

Purpose: The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. Methods: The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it ismore » implemented on a graphics processing unit, using parallelization to accelerate computations. Results: The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1–2 min and are compatible with the typical clinical workflow for nonreal-time applications. Conclusions: Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.« less

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Ultralow dose computed tomography attenuation correction for pediatric PET CT using adaptive statistical iterative reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brady, Samuel L., E-mail: samuel.brady@stjude.org; Shulkin, Barry L.

2015-02-15

Purpose: To develop ultralow dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET imagesmore » were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUV{sub bw}) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV{sub bw}, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake.« less

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

PubMed Central

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

2015-01-01

Objective: To investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR. Methods: 27 consecutive patients (mean body mass index: 23.55 kg m−2 underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded. Results: At the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19–49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP. Conclusion: Abdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. Advances in knowledge: This study represents the first

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu

2014-05-15

one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hofmann, Christian; Sawall, Stefan; Knaup, Michael

2014-06-15

contrast 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.« less

Estimating Glenoid Width for Instability-Related Bone Loss: A CT Evaluation of an MRI Formula.

PubMed

Giles, Joshua W; Owens, Brett D; Athwal, George S

2015-07-01

Determining the magnitude of glenoid bone loss in cases of shoulder instability is an important step in selecting the optimal reconstructive procedure. Recently, a formula has been proposed that estimates native glenoid width based on magnetic resonance imaging (MRI) measurements of height (1/3 × glenoid height + 15 mm). This technique, however, has not been validated for use with computed tomography (CT), which is often the preferred imaging modality to assess bone deficiencies. The purpose of this project was 2-fold: (1) to determine if the MRI-based formula that predicts glenoid width from height is valid with CT and (2) to determine if a more accurate regression can be resolved for use specifically with CT data. Descriptive laboratory study. Ninety normal shoulder CT scans with preserved osseous anatomy were drawn from an existing database and analyzed. Measurements of glenoid height and width were performed by 2 observers on reconstructed 3-dimensional models. After assessment of reliability, the data were correlated, and regression models were created for male and female shoulders. The accuracy of the MRI-based model's predictions was then compared with that of the CT-based models. Intra- and interrater reliabilities were good to excellent for height and width, with intraclass correlation coefficients of 0.765 to 0.992. The height and width values had a strong correlation of 0.900 (P < .001). Regression analyses for male and female shoulders produced CT-specific formulas: for men, glenoid width = 2/3 × glenoid height + 5 mm; for women, glenoid width = 2/3 × glenoid height + 3 mm. Comparison of predictions from the MRI- and CT-specific formulas demonstrated good agreement (intraclass correlation coefficient = 0.818). The CT-specific formulas produced a root mean squared error of 1.2 mm, whereas application of the MRI-specific formula to CT images resulted in a root mean squared error of 1.5 mm. Use of the MRI-based formula on CT scans to predict glenoid

Superiorization-based multi-energy CT image reconstruction

PubMed Central

Yang, Q; Cong, W; Wang, G

2017-01-01

The recently-developed superiorization approach is efficient and robust for solving various constrained optimization problems. This methodology can be applied to multi-energy CT image reconstruction with the regularization in terms of the prior rank, intensity and sparsity model (PRISM). In this paper, we propose a superiorized version of the simultaneous algebraic reconstruction technique (SART) based on the PRISM model. Then, we compare the proposed superiorized algorithm with the Split-Bregman algorithm in numerical experiments. The results show that both the Superiorized-SART and the Split-Bregman algorithms generate good results with weak noise and reduced artefacts. PMID:28983142

List-mode reconstruction for the Biograph mCT with physics modeling and event-by-event motion correction

NASA Astrophysics Data System (ADS)

Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E.; Liu, Chi; Carson, Richard E.

2013-08-01

Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion

Tight-frame based iterative image reconstruction for spectral breast CT

PubMed Central

Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

2013-01-01

Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

Accurate low-dose iterative CT reconstruction from few projections by Generalized Anisotropic Total Variation minimization for industrial CT.

PubMed

Debatin, Maurice; Hesser, Jürgen

2015-01-01

Reducing the amount of time for data acquisition and reconstruction in industrial CT decreases the operation time of the X-ray machine and therefore increases the sales. This can be achieved by reducing both, the dose and the pulse length of the CT system and the number of projections for the reconstruction, respectively. In this paper, a novel generalized Anisotropic Total Variation regularization for under-sampled, low-dose iterative CT reconstruction is discussed and compared to the standard methods, Total Variation, Adaptive weighted Total Variation and Filtered Backprojection. The novel regularization function uses a priori information about the Gradient Magnitude Distribution of the scanned object for the reconstruction. We provide a general parameterization scheme and evaluate the efficiency of our new algorithm for different noise levels and different number of projection views. When noise is not present, error-free reconstructions are achievable for AwTV and GATV from 40 projections. In cases where noise is simulated, our strategy achieves a Relative Root Mean Square Error that is up to 11 times lower than Total Variation-based and up to 4 times lower than AwTV-based iterative statistical reconstruction (e.g. for a SNR of 223 and 40 projections). To obtain the same reconstruction quality as achieved by Total Variation, the projection number and the pulse length, and the acquisition time and the dose respectively can be reduced by a factor of approximately 3.5, when AwTV is used and a factor of approximately 6.7, when our proposed algorithm is used.

Image reconstruction from few-view CT data by gradient-domain dictionary learning.

PubMed

Hu, Zhanli; Liu, Qiegen; Zhang, Na; Zhang, Yunwan; Peng, Xi; Wu, Peter Z; Zheng, Hairong; Liang, Dong

2016-05-21

Decreasing the number of projections is an effective way to reduce the radiation dose exposed to patients in medical computed tomography (CT) imaging. However, incomplete projection data for CT reconstruction will result in artifacts and distortions. In this paper, a novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction. Specifically, the dictionaries are trained from the horizontal and vertical gradient images, respectively and the desired image is reconstructed subsequently from the sparse representations of both gradients by solving the least-square method. Since the gradient images are sparser than the image itself, the proposed approach could lead to sparser representations than conventional DL methods in the image-domain, and thus a better reconstruction quality is achieved. To evaluate the proposed Grad-DL algorithm, both qualitative and quantitative studies were employed through computer simulations as well as real data experiments on fan-beam and cone-beam geometry. The results show that the proposed algorithm can yield better images than the existing algorithms.

SYRMEP Tomo Project: a graphical user interface for customizing CT reconstruction workflows.

PubMed

Brun, Francesco; Massimi, Lorenzo; Fratini, Michela; Dreossi, Diego; Billé, Fulvio; Accardo, Agostino; Pugliese, Roberto; Cedola, Alessia

2017-01-01

When considering the acquisition of experimental synchrotron radiation (SR) X-ray CT data, the reconstruction workflow cannot be limited to the essential computational steps of flat fielding and filtered back projection (FBP). More refined image processing is often required, usually to compensate artifacts and enhance the quality of the reconstructed images. In principle, it would be desirable to optimize the reconstruction workflow at the facility during the experiment (beamtime). However, several practical factors affect the image reconstruction part of the experiment and users are likely to conclude the beamtime with sub-optimal reconstructed images. Through an example of application, this article presents SYRMEP Tomo Project (STP), an open-source software tool conceived to let users design custom CT reconstruction workflows. STP has been designed for post-beamtime (off-line use) and for a new reconstruction of past archived data at user's home institution where simple computing resources are available. Releases of the software can be downloaded at the Elettra Scientific Computing group GitHub repository https://github.com/ElettraSciComp/STP-Gui.

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, H; Xing, L; Liang, Z

Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern formore » each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation

Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

2000-01-01

This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

Analytic image reconstruction from partial data for a single-scan cone-beam CT with scatter correction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Min, Jonghwan; Pua, Rizza; Cho, Seungryong, E-mail: scho@kaist.ac.kr

Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in amore » circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that

Deep learning methods to guide CT image reconstruction and reduce metal artifacts

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

2017-03-01

The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

Low dose dynamic myocardial CT perfusion using advanced iterative reconstruction

NASA Astrophysics Data System (ADS)

Eck, Brendan L.; Fahmi, Rachid; Fuqua, Christopher; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2015-03-01

Dynamic myocardial CT perfusion (CTP) can provide quantitative functional information for the assessment of coronary artery disease. However, x-ray dose in dynamic CTP is high, typically from 10mSv to >20mSv. We compared the dose reduction potential of advanced iterative reconstruction, Iterative Model Reconstruction (IMR, Philips Healthcare, Cleveland, Ohio) to hybrid iterative reconstruction (iDose4) and filtered back projection (FBP). Dynamic CTP scans were obtained using a porcine model with balloon-induced ischemia in the left anterior descending coronary artery to prescribed fractional flow reserve values. High dose dynamic CTP scans were acquired at 100kVp/100mAs with effective dose of 23mSv. Low dose scans at 75mAs, 50mAs, and 25mAs were simulated by adding x-ray quantum noise and detector electronic noise to the projection space data. Images were reconstructed with FBP, iDose4, and IMR at each dose level. Image quality in static CTP images was assessed by SNR and CNR. Blood flow was obtained using a dynamic CTP analysis pipeline and blood flow image quality was assessed using flow-SNR and flow-CNR. IMR showed highest static image quality according to SNR and CNR. Blood flow in FBP was increasingly over-estimated at reduced dose. Flow was more consistent for iDose4 from 100mAs to 50mAs, but was over-estimated at 25mAs. IMR was most consistent from 100mAs to 25mAs. Static images and flow maps for 100mAs FBP, 50mAs iDose4, and 25mAs IMR showed comparable, clear ischemia, CNR, and flow-CNR values. These results suggest that IMR can enable dynamic CTP at significantly reduced dose, at 5.8mSv or 25% of the comparable 23mSv FBP protocol.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr

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 sinogrammore » 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

Accelerated Compressed Sensing Based CT Image Reconstruction.

PubMed

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

PubMed Central

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. PMID:26167200

SparseCT: interrupted-beam acquisition and sparse reconstruction for radiation dose reduction

NASA Astrophysics Data System (ADS)

Koesters, Thomas; Knoll, Florian; Sodickson, Aaron; Sodickson, Daniel K.; Otazo, Ricardo

2017-03-01

State-of-the-art low-dose CT methods reduce the x-ray tube current and use iterative reconstruction methods to denoise the resulting images. However, due to compromises between denoising and image quality, only moderate dose reductions up to 30-40% are accepted in clinical practice. An alternative approach is to reduce the number of x-ray projections and use compressed sensing to reconstruct the full-tube-current undersampled data. This idea was recognized in the early days of compressed sensing and proposals for CT dose reduction appeared soon afterwards. However, no practical means of undersampling has yet been demonstrated in the challenging environment of a rapidly rotating CT gantry. In this work, we propose a moving multislit collimator as a practical incoherent undersampling scheme for compressed sensing CT and evaluate its application for radiation dose reduction. The proposed collimator is composed of narrow slits and moves linearly along the slice dimension (z), to interrupt the incident beam in different slices for each x-ray tube angle (θ). The reduced projection dataset is then reconstructed using a sparse approach, where 3D image gradients are employed to enforce sparsity. The effects of the collimator slits on the beam profile were measured and represented as a continuous slice profile. SparseCT was tested using retrospective undersampling and compared against commercial current-reduction techniques on phantoms and in vivo studies. Initial results suggest that SparseCT may enable higher performance than current-reduction, particularly for high dose reduction factors.

Assessment of chest CT at CTDIvol less than 1 mGy with iterative reconstruction techniques.

PubMed

Padole, Atul; Digumarthy, Subba; Flores, Efren; Madan, Rachna; Mishra, Shelly; Sharma, Amita; Kalra, Mannudeep K

2017-03-01

To assess the image quality of chest CT reconstructed with image-based iterative reconstruction (SafeCT; MedicVision ® , Tirat Carmel, Israel), adaptive statistical iterative reconstruction (ASIR; GE Healthcare, Waukesha, WI) and model-based iterative reconstruction (MBIR; GE Healthcare, Waukesha, WI) techniques at CT dose index volume (CTDI vol ) <1 mGy. In an institutional review board-approved study, 25 patients gave written informed consent for acquisition of three reduced dose (0.25-, 0.4- and 0.8-mGy) chest CT after standard of care CT (8 mGy) on a 64-channel multidetector CT (MDCT) and reconstructed with SafeCT, ASIR and MBIR. Two board-certified thoracic radiologists evaluated images from the lowest to the highest dose of the reduced dose CT series and subsequently for standard of care CT. Out of the 182 detected lesions, the missed lesions were 35 at 0.25, 24 at 0.4 and 9 at 0.8 mGy with SafeCT, ASIR and MBIR, respectively. The most missed lesions were non-calcified lung nodules (NCLNs) 25/112 (<5 mm) at 0.25, 18/112 (<5 mm) at 0.4 and 3/112 (<4 mm) at 0.8 mGy. There were 78%, 84% and 97% lung nodules detected at 0.25, 0.4 and 0.8 mGy, respectively regardless of iterative reconstruction techniques (IRTs), Most mediastinum structures were not sufficiently seen at 0.25-0.8 mGy. NCLNs can be missed in chest CT at CTDI vol of <1 mGy (0.25, 0.4 and 0.8 mGy) regardless of IRTs. The most lung nodules (97%) were detected at CTDI vol of 0.8 mGy. The most mediastinum structures were not sufficiently seen at 0.25-0.8 mGy. Advances in knowledge: NCLNs can be missed regardless of IRTs in chest CT at CTDI vol of <1 mGy. The performance of ASIR, SafeCT and MBIR was similar for lung nodule detection at 0.25, 0.4 and 0.8 mGy.

Radiation dose reduction in soft tissue neck CT using adaptive statistical iterative reconstruction (ASIR).

PubMed

Vachha, Behroze; Brodoefel, Harald; Wilcox, Carol; Hackney, David B; Moonis, Gul

2013-12-01

To compare objective and subjective image quality in neck CT images acquired at different tube current-time products (275 mAs and 340 mAs) and reconstructed with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR). HIPAA-compliant study with IRB approval and waiver of informed consent. 66 consecutive patients were randomly assigned to undergo contrast-enhanced neck CT at a standard tube-current-time-product (340 mAs; n = 33) or reduced tube-current-time-product (275 mAs, n = 33). Data sets were reconstructed with FBP and 2 levels (30%, 40%) of ASIR-FBP blending at 340 mAs and 275 mAs. Two neuroradiologists assessed subjective image quality in a blinded and randomized manner. Volume CT dose index (CTDIvol), dose-length-product (DLP), effective dose, and objective image noise were recorded. Signal-to-noise ratio (SNR) was computed as mean attenuation in a region of interest in the sternocleidomastoid muscle divided by image noise. Compared with FBP, ASIR resulted in a reduction of image noise at both 340 mAs and 275 mAs. Reduction of tube current from 340 mAs to 275 mAs resulted in an increase in mean objective image noise (p=0.02) and a decrease in SNR (p = 0.03) when images were reconstructed with FBP. However, when the 275 mAs images were reconstructed using ASIR, the mean objective image noise and SNR were similar to those of the standard 340 mAs CT images reconstructed with FBP (p>0.05). Subjective image noise was ranked by both raters as either average or less-than-average irrespective of the tube current and iterative reconstruction technique. Adapting ASIR into neck CT protocols reduced effective dose by 17% without compromising image quality. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Low-dose CT reconstruction with patch based sparsity and similarity constraints

NASA Astrophysics Data System (ADS)

Xu, Qiong; Mou, Xuanqin

2014-03-01

As the rapid growth of CT based medical application, low-dose CT reconstruction becomes more and more important to human health. Compared with other methods, statistical iterative reconstruction (SIR) usually performs better in lowdose case. However, the reconstructed image quality of SIR highly depends on the prior based regularization due to the insufficient of low-dose data. The frequently-used regularization is developed from pixel based prior, such as the smoothness between adjacent pixels. This kind of pixel based constraint cannot distinguish noise and structures effectively. Recently, patch based methods, such as dictionary learning and non-local means filtering, have outperformed the conventional pixel based methods. Patch is a small area of image, which expresses structural information of image. In this paper, we propose to use patch based constraint to improve the image quality of low-dose CT reconstruction. In the SIR framework, both patch based sparsity and similarity are considered in the regularization term. On one hand, patch based sparsity is addressed by sparse representation and dictionary learning methods, on the other hand, patch based similarity is addressed by non-local means filtering method. We conducted a real data experiment to evaluate the proposed method. The experimental results validate this method can lead to better image with less noise and more detail than other methods in low-count and few-views cases.

Edge guided image reconstruction in linear scan CT by weighted alternating direction TV minimization.

PubMed

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

2014-01-01

Linear scan computed tomography (CT) is a promising imaging configuration with high scanning efficiency while the data set is under-sampled and angularly limited for which high quality image reconstruction is challenging. In this work, an edge guided total variation minimization reconstruction (EGTVM) algorithm is developed in dealing with this problem. The proposed method is modeled on the combination of total variation (TV) regularization and iterative edge detection strategy. In the proposed method, the edge weights of intermediate reconstructions are incorporated into the TV objective function. The optimization is efficiently solved by applying alternating direction method of multipliers. A prudential and conservative edge detection strategy proposed in this paper can obtain the true edges while restricting the errors within an acceptable degree. Based on the comparison on both simulation studies and real CT data set reconstructions, EGTVM provides comparable or even better quality compared to the non-edge guided reconstruction and adaptive steepest descent-projection onto convex sets method. With the utilization of weighted alternating direction TV minimization and edge detection, EGTVM achieves fast and robust convergence and reconstructs high quality image when applied in linear scan CT with under-sampled data set.

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

PubMed

Kole, J S; Beekman, F J

2006-02-21

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, C; Chan, S; Lee, F

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 withmore » 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.« less

SART-Type Half-Threshold Filtering Approach for CT Reconstruction

PubMed Central

YU, HENGYONG; WANG, GE

2014-01-01

The ℓ1 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 ℓp norm (0 < p < 1) and solve the ℓp minimization problem. Very recently, Xu et al. developed an analytic solution for the ℓ1∕2 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. PMID:25530928

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

PubMed

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.

CT reconstruction from portal images acquired during volumetric-modulated arc therapy

NASA Astrophysics Data System (ADS)

Poludniowski, G.; Thomas, M. D. R.; Evans, P. M.; Webb, S.

2010-10-01

Volumetric-modulated arc therapy (VMAT), a form of intensity-modulated arc therapy (IMAT), has become a topic of research and clinical activity in recent years. As a form of arc therapy, portal images acquired during the treatment fraction form a (partial) Radon transform of the patient. We show that these portal images, when used in a modified global cone-beam filtered backprojection (FBP) algorithm, allow a surprisingly recognizable CT-volume to be reconstructed. The possibility of distinguishing anatomy in such VMAT-CT reconstructions suggests that this could prove to be a valuable treatment position-verification tool. Further, some potential for local-tomography techniques to improve image quality is shown.

List-mode Reconstruction for the Biograph mCT with Physics Modeling and Event-by-Event Motion Correction

PubMed Central

Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E.; Liu, Chi; Carson, Richard E.

2013-01-01

Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32-bit packets, where averaging of lines of response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic assignment of LOR positions (pLOR) that addresses axial and transaxial LOR grouping in 32-bit data. Second, two simplified approaches for 3D TOF scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + time-of-flight (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32-bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fahimian, Benjamin P.; Zhao Yunzhe; Huang Zhifeng

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). Inmore » 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

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

PubMed

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

PubMed Central

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

2013-01-01

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

Iterative reconstruction for CT perfusion with a prior-image induced hybrid nonlocal means regularization: Phantom studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Bin; Lyu, Qingwen; Ma, Jianhua

2016-04-15

Purpose: In computed tomography perfusion (CTP) imaging, an initial phase CT acquired with a high-dose protocol can be used to improve the image quality of later phase CT acquired with a low-dose protocol. For dynamic regions, signals in the later low-dose CT may not be completely recovered if the initial CT heavily regularizes the iterative reconstruction process. The authors propose a hybrid nonlocal means (hNLM) regularization model for iterative reconstruction of low-dose CTP to overcome the limitation of the conventional prior-image induced penalty. Methods: The hybrid penalty was constructed by combining the NLM of the initial phase high-dose CT inmore » the stationary region and later phase low-dose CT in the dynamic region. The stationary and dynamic regions were determined by the similarity between the initial high-dose scan and later low-dose scan. The similarity was defined as a Gaussian kernel-based distance between the patch-window of the same pixel in the two scans, and its measurement was then used to weigh the influence of the initial high-dose CT. For regions with high similarity (e.g., stationary region), initial high-dose CT played a dominant role for regularizing the solution. For regions with low similarity (e.g., dynamic region), the regularization relied on a low-dose scan itself. This new hNLM penalty was incorporated into the penalized weighted least-squares (PWLS) for CTP reconstruction. Digital and physical phantom studies were performed to evaluate the PWLS-hNLM algorithm. Results: Both phantom studies showed that the PWLS-hNLM algorithm is superior to the conventional prior-image induced penalty term without considering the signal changes within the dynamic region. In the dynamic region of the Catphan phantom, the reconstruction error measured by root mean square error was reduced by 42.9% in PWLS-hNLM reconstructed image. Conclusions: The PWLS-hNLM algorithm can effectively use the initial high-dose CT to reconstruct low-dose CTP in

A biological phantom for evaluation of CT image reconstruction algorithms

NASA Astrophysics Data System (ADS)

Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.

2014-03-01

In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)

NASA Astrophysics Data System (ADS)

Rit, S.; Vila Oliva, M.; Brousmiche, S.; Labarbe, R.; Sarrut, D.; Sharp, G. C.

2014-03-01

We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in partnership with Kitware, the company supporting ITK. Several features are already available: Elekta, Varian and IBA inputs, multi-threaded Feldkamp-David-Kress reconstruction on CPU and GPU, Parker short scan weighting, multi-threaded CPU and GPU forward projectors, etc. Each feature is either accessible through command line tools or C++ classes that can be included in independent software. A MIDAS community has been opened to share CatPhan datasets of several vendors (Elekta, Varian and IBA). RTK will be used in the upcoming cone-beam CT scanner developed by IBA for proton therapy rooms. Many features are under development: new input format support, iterative reconstruction, hybrid Monte Carlo / deterministic CBCT simulation, etc. RTK has been built to freely share tomographic reconstruction developments between researchers and is open for new contributions.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

Extremely low-dose (LD) CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This paper explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air + background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the root mean squared error (RMSE) by roughly two times compared with a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared with a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-LD CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

Investigation of statistical iterative reconstruction for dedicated breast CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Makeev, Andrey; Glick, Stephen J.

2013-08-15

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images weremore » compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue.Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters.Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially

Investigation of statistical iterative reconstruction for dedicated breast CT

PubMed Central

Makeev, Andrey; Glick, Stephen J.

2013-01-01

Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue. Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters. Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved

Comparison of Knowledge-based Iterative Model Reconstruction and Hybrid Reconstruction Techniques for Liver CT Evaluation of Hypervascular Hepatocellular Carcinoma.

PubMed

Park, Hyun Jeong; Lee, Jeong Min; Park, Sung Bin; Lee, Jong Beum; Jeong, Yoong Ki; Yoon, Jeong Hee

The purpose of this work was to evaluate the image quality, lesion conspicuity, and dose reduction provided by knowledge-based iterative model reconstruction (IMR) in computed tomography (CT) of the liver compared with hybrid iterative reconstruction (IR) and filtered back projection (FBP) in patients with hepatocellular carcinoma (HCC). Fifty-six patients with 61 HCCs who underwent multiphasic reduced-dose CT (RDCT; n = 33) or standard-dose CT (SDCT; n = 28) were retrospectively evaluated. Reconstructed images with FBP, hybrid IR (iDose), IMR were evaluated for image quality using CT attenuation and image noise. Objective and subjective image quality of RDCT and SDCT sets were independently assessed by 2 observers in a blinded manner. Image quality and lesion conspicuity were better with IMR for both RDCT and SDCT than either FBP or IR (P < 0.001). Contrast-to-noise ratio of HCCs in IMR-RDCT was significantly higher on delayed phase (DP) (P < 0.001), and comparable on arterial phase, than with IR-SDCT (P = 0.501). Iterative model reconstruction RDCT was significantly superior to FBP-SDCT (P < 0.001). Compared with IR-SDCT, IMR-RDCT was comparable in image sharpness and tumor conspicuity on arterial phase, and superior in image quality, noise, and lesion conspicuity on DP. With the use of IMR, a 27% reduction of effective dose was achieved with RDCT (12.7 ± 0.6 mSv) compared with SDCT (17.4 ± 1.1 mSv) without loss of image quality (P < 0.001). Iterative model reconstruction provides better image quality and tumor conspicuity than FBP and IR with considerable noise reduction. In addition, more than comparable results were achieved with IMR-RDCT to IR-SDCT for the evaluation of HCCs.

Can sinogram-affirmed iterative (SAFIRE) reconstruction improve imaging quality on low-dose lung CT screening compared with traditional filtered back projection (FBP) reconstruction?

PubMed

Yang, Wen Jie; Yan, Fu Hua; Liu, Bo; Pang, Li Fang; Hou, Liang; Zhang, Huan; Pan, Zi Lai; Chen, Ke Min

2013-01-01

To evaluate the performance of sinogram-affirmed iterative (SAFIRE) reconstruction on image quality of low-dose lung computed tomographic (CT) screening compared with filtered back projection (FBP). Three hundred four patients for annual low-dose lung CT screening were examined by a dual-source CT system at 120 kilovolt (peak) with reference tube current of 40 mA·s. Six image serials were reconstructed, including one data set of FBP and 5 data sets of SAFIRE with different reconstruction strengths from 1 to 5. Image noise was recorded; and subjective scores of image noise, images artifacts, and the overall image quality were also assessed by 2 radiologists. The mean ± SD weight for all patients was 66.3 ± 12.8 kg, and the body mass index was 23.4 ± 3.2. The mean ± SD dose-length product was 95.2 ± 30.6 mGy cm, and the mean ± SD effective dose was 1.6 ± 0.5 mSv. The observation agreements for image noise grade, artifact grade, and the overall image quality were 0.785, 0.595 and 0.512, respectively. Among the overall 6 data sets, both the measured mean objective image noise and the subjective image noise of FBP was the highest, and the image noise decreased with the increasing of SAFIRE reconstruction strength. The data sets of S3 obtained the best image quality scores. Sinogram-affirmed iterative reconstruction can significantly improve image quality of low-dose lung CT screening compared with FBP, and SAFIRE with reconstruction strength 3 was a pertinent choice for low-dose lung CT.

A new SPECT/CT reconstruction algorithm: reliability and accuracy in clinical routine for non-oncologic bone diseases.

PubMed

Delcroix, Olivier; Robin, Philippe; Gouillou, Maelenn; Le Duc-Pennec, Alexandra; Alavi, Zarrin; Le Roux, Pierre-Yves; Abgral, Ronan; Salaun, Pierre-Yves; Bourhis, David; Querellou, Solène

2018-02-12

xSPECT Bone® (xB) is a new reconstruction algorithm developed by Siemens® in bone hybrid imaging (SPECT/CT). A CT-based tissue segmentation is incorporated into SPECT reconstruction to provide SPECT images with bone anatomy appearance. The objectives of this study were to assess xB/CT reconstruction diagnostic reliability and accuracy in comparison with Flash 3D® (F3D)/CT in clinical routine. Two hundred thirteen consecutive patients referred to the Brest Nuclear Medicine Department for non-oncological bone diseases were evaluated retrospectively. Two hundred seven SPECT/CT were included. All SPECT/CT were independently interpreted by two nuclear medicine physicians (a junior and a senior expert) with xB/CT then with F3D/CT three months later. Inter-observer agreement (IOA) and diagnostic confidence were determined using McNemar test, and unweighted Kappa coefficient. The study objectives were then re-assessed for validation through > 18 months of clinical and paraclinical follow-up. No statistically significant differences between IOA xB and IOA F3D were found (p = 0.532). Agreement for xB after categorical classification of the diagnoses was high (κ xB = 0.89 [95% CI 0.84 -0.93]) but without statistically significant difference F3D (κ F3D = 0.90 [95% CI 0.86 - 0.94]). Thirty-one (14.9%) inter-reconstruction diagnostic discrepancies were observed of which 21 (10.1%) were classified as major. The follow-up confirmed the diagnosis of F3D in 10 cases, xB in 6 cases and was non-contributory in 5 cases. xB reconstruction algorithm was found reliable, providing high interobserver agreement and similar diagnostic confidence to F3D reconstruction in clinical routine.

Texture-preserved penalized weighted least-squares reconstruction of low-dose CT image via image segmentation and high-order MRF modeling

NASA Astrophysics Data System (ADS)

Han, Hao; Zhang, Hao; Wei, Xinzhou; Moore, William; Liang, Zhengrong

2016-03-01

In this paper, we proposed a low-dose computed tomography (LdCT) image reconstruction method with the help of prior knowledge learning from previous high-quality or normal-dose CT (NdCT) scans. The well-established statistical penalized weighted least squares (PWLS) algorithm was adopted for image reconstruction, where the penalty term was formulated by a texture-based Gaussian Markov random field (gMRF) model. The NdCT scan was firstly segmented into different tissue types by a feature vector quantization (FVQ) approach. Then for each tissue type, a set of tissue-specific coefficients for the gMRF penalty was statistically learnt from the NdCT image via multiple-linear regression analysis. We also proposed a scheme to adaptively select the order of gMRF model for coefficients prediction. The tissue-specific gMRF patterns learnt from the NdCT image were finally used to form an adaptive MRF penalty for the PWLS reconstruction of LdCT image. The proposed texture-adaptive PWLS image reconstruction algorithm was shown to be more effective to preserve image textures than the conventional PWLS image reconstruction algorithm, and we further demonstrated the gain of high-order MRF modeling for texture-preserved LdCT PWLS image reconstruction.

4D-CT motion estimation using deformable image registration and 5D respiratory motion modeling.

PubMed

Yang, Deshan; Lu, Wei; Low, Daniel A; Deasy, Joseph O; Hope, Andrew J; El Naqa, Issam

2008-10-01

Four-dimensional computed tomography (4D-CT) imaging technology has been developed for radiation therapy to provide tumor and organ images at the different breathing phases. In this work, a procedure is proposed for estimating and modeling the respiratory motion field from acquired 4D-CT imaging data and predicting tissue motion at the different breathing phases. The 4D-CT image data consist of series of multislice CT volume segments acquired in ciné mode. A modified optical flow deformable image registration algorithm is used to compute the image motion from the CT segments to a common full volume 3D-CT reference. This reference volume is reconstructed using the acquired 4D-CT data at the end-of-exhalation phase. The segments are optimally aligned to the reference volume according to a proposed a priori alignment procedure. The registration is applied using a multigrid approach and a feature-preserving image downsampling maxfilter to achieve better computational speed and higher registration accuracy. The registration accuracy is about 1.1 +/- 0.8 mm for the lung region according to our verification using manually selected landmarks and artificially deformed CT volumes. The estimated motion fields are fitted to two 5D (spatial 3D+tidal volume+airflow rate) motion models: forward model and inverse model. The forward model predicts tissue movements and the inverse model predicts CT density changes as a function of tidal volume and airflow rate. A leave-one-out procedure is used to validate these motion models. The estimated modeling prediction errors are about 0.3 mm for the forward model and 0.4 mm for the inverse model.

Spectral CT Reconstruction with Image Sparsity and Spectral Mean

PubMed Central

Zhang, Yi; Xi, Yan; Yang, Qingsong; Cong, Wenxiang; Zhou, Jiliu

2017-01-01

Photon-counting detectors can acquire x-ray intensity data in different energy bins. The signal to noise ratio of resultant raw data in each energy bin is generally low due to the narrow bin width and quantum noise. To address this problem, here we propose an image reconstruction approach for spectral CT to simultaneously reconstructs x-ray attenuation coefficients in all the energy bins. Because the measured spectral data are highly correlated among the x-ray energy bins, the intra-image sparsity and inter-image similarity are important prior acknowledge for image reconstruction. Inspired by this observation, the total variation (TV) and spectral mean (SM) measures are combined to improve the quality of reconstructed images. For this purpose, a linear mapping function is used to minimalize image differences between energy bins. The split Bregman technique is applied to perform image reconstruction. Our numerical and experimental results show that the proposed algorithms outperform competing iterative algorithms in this context. PMID:29034267

WE-EF-207-07: Dual Energy CT with One Full Scan and a Second Sparse-View Scan Using Structure Preserving Iterative Reconstruction (SPIR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, T; Zhu, L

Purpose: Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full-size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse-view scan by utilizing redundant structural information of the same object acquired at two different energies. Methods: We first reconstruct a full-scan CT image using filtered-backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CTmore » scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms. Results: On the Catphan600 phantom, SPIR-based DECT method with a second 10-view scan reduces the noise standard deviation of a full-scan FBP CT reconstruction by a factor of 4 with well-maintained spatial resolution, while iterative reconstruction using total-variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two-full-scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue. Conclusion: We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR-based DECT using one full scan and a second 10-view scan

Convex-hull mass estimates of the dodo (Raphus cucullatus): application of a CT-based mass estimation technique

PubMed Central

O’Mahoney, Thomas G.; Kitchener, Andrew C.; Manning, Phillip L.; Sellers, William I.

2016-01-01

The external appearance of the dodo (Raphus cucullatus, Linnaeus, 1758) has been a source of considerable intrigue, as contemporaneous accounts or depictions are rare. The body mass of the dodo has been particularly contentious, with the flightless pigeon alternatively reconstructed as slim or fat depending upon the skeletal metric used as the basis for mass prediction. Resolving this dichotomy and obtaining a reliable estimate for mass is essential before future analyses regarding dodo life history, physiology or biomechanics can be conducted. Previous mass estimates of the dodo have relied upon predictive equations based upon hind limb dimensions of extant pigeons. Yet the hind limb proportions of dodo have been found to differ considerably from those of their modern relatives, particularly with regards to midshaft diameter. Therefore, application of predictive equations to unusually robust fossil skeletal elements may bias mass estimates. We present a whole-body computed tomography (CT) -based mass estimation technique for application to the dodo. We generate 3D volumetric renders of the articulated skeletons of 20 species of extant pigeons, and wrap minimum-fit ‘convex hulls’ around their bony extremities. Convex hull volume is subsequently regressed against mass to generate predictive models based upon whole skeletons. Our best-performing predictive model is characterized by high correlation coefficients and low mean squared error (a = − 2.31, b = 0.90, r2 = 0.97, MSE = 0.0046). When applied to articulated composite skeletons of the dodo (National Museums Scotland, NMS.Z.1993.13; Natural History Museum, NHMUK A.9040 and S/1988.50.1), we estimate eviscerated body masses of 8–10.8 kg. When accounting for missing soft tissues, this may equate to live masses of 10.6–14.3 kg. Mass predictions presented here overlap at the lower end of those previously published, and support recent suggestions of a relatively slim dodo. CT-based reconstructions provide a

Dual-resolution image reconstruction for region-of-interest CT scan

NASA Astrophysics Data System (ADS)

Jin, S. O.; Shin, K. Y.; Yoo, S. K.; Kim, J. G.; Kim, K. H.; Huh, Y.; Lee, S. Y.; Kwon, O.-K.

2014-07-01

In ordinary CT scan, so called full field-of-view (FFOV) scan, in which the x-ray beam span covers the whole section of the body, a large number of projections are necessary to reconstruct high resolution images. However, excessive x-ray dose is a great concern in FFOV scan. Region-of-interest (ROI) scan is a method to visualize the ROI in high resolution while reducing the x-ray dose. But, ROI scan suffers from bright-band artifacts which may hamper CT-number accuracy. In this study, we propose an image reconstruction method to eliminate the band artifacts in the ROI scan. In addition to the ROI scan with high sampling rate in the view direction, we get FFOV projection data with much lower sampling rate. Then, we reconstruct images in the compressed sensing (CS) framework with dual resolutions, that is, high resolution in the ROI and low resolution outside the ROI. For the dual-resolution image reconstruction, we implemented the dual-CS reconstruction algorithm in which data fidelity and total variation (TV) terms were enforced twice in the framework of adaptive steepest descent projection onto convex sets (ASD-POCS). The proposed method has remarkably reduced the bright-band artifacts at around the ROI boundary, and it has also effectively suppressed the streak artifacts over the entire image. We expect the proposed method can be greatly used for dual-resolution imaging with reducing the radiation dose, artifacts and scan time.

Full dose reduction potential of statistical iterative reconstruction for head CT protocols in a predominantly pediatric population

PubMed Central

Mirro, Amy E.; Brady, Samuel L.; Kaufman, Robert. A.

2016-01-01

Purpose To implement the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population. Methods Select head examinations (brain, orbits, sinus, maxilla and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction (ASiR) were compared for image quality with the original filtered back projection (FBP) reconstructed protocols in phantom using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio (CNR), and spatial resolution. Dose reduction estimates were based on computed tomography dose index (CTDIvol) values. Patient CTDIvol and image noise magnitude were assessed in 737 pre and post dose reduced examinations. Results Image noise texture was acceptable up to 60% ASiR for Soft reconstruction kernel (at both 100 and 120 kVp), and up to 40% ASiR for Standard reconstruction kernel. Implementation of 40% and 60% ASiR led to an average reduction in CTDIvol of 43% for brain, 41% for orbits, 30% maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years, while maintaining an average noise magnitude difference of 0.1% (range: −3% to 5%), improving CNR of low contrast soft tissue targets, and improving spatial resolution of high contrast bony anatomy, as compared to FBP. Conclusion The methodology in this study demonstrates a methodology for maximizing patient dose reduction and maintaining image quality using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examination. PMID:27056425

Accuracy of lung nodule volumetry in low-dose CT with iterative reconstruction: an anthropomorphic thoracic phantom study.

PubMed

Doo, K W; Kang, E-Y; Yong, H S; Woo, O H; Lee, K Y; Oh, Y-W

2014-09-01

The purpose of this study was to assess accuracy of lung nodule volumetry in low-dose CT with application of iterative reconstruction (IR) according to nodule size, nodule density and CT tube currents, using artificial lung nodules within an anthropomorphic thoracic phantom. Eight artificial nodules (four diameters: 5, 8, 10 and 12 mm; two CT densities: -630 HU that represents ground-glass nodule and +100 HU that represents solid nodule) were randomly placed inside a thoracic phantom. Scans were performed with tube current-time product to 10, 20, 30 and 50 mAs. Images were reconstructed with IR and filtered back projection (FBP). We compared volume estimates to a reference standard and calculated the absolute percentage error (APE). The APE of all nodules was significantly lower when IR was used than with FBP (7.5 ± 4.7% compared with 9.0 ±6.9%; p < 0.001). The effect of IR was more pronounced for smaller nodules (p < 0.001). IR showed a significantly lower APE than FBP in ground-glass nodules (p < 0.0001), and the difference was more pronounced at the lowest tube current (11.8 ± 5.9% compared with 21.3 ± 6.1%; p < 0.0001). The effect of IR was most pronounced for ground-glass nodules in the lowest CT tube current. Lung nodule volumetry in low-dose CT by application of IR showed reliable accuracy in a phantom study. Lung nodule volumetry can be reliably applicable to all lung nodules including small, ground-glass nodules even in ultra-low-dose CT with application of IR. IR significantly improved the accuracy of lung nodule volumetry compared with FBP particularly for ground-glass (-630 HU) nodules. Volumetry in low-dose CT can be utilized in patient with lung nodule work-up, and IR has benefit for small, ground-glass lung nodules in low-dose CT.

Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra

NASA Astrophysics Data System (ADS)

Xu, S.; Uneri, A.; Khanna, A. Jay; Siewerdsen, J. H.; Stayman, J. W.

2017-04-01

Metal artifacts can cause substantial image quality issues in computed tomography. This is particularly true in interventional imaging where surgical tools or metal implants are in the field-of-view. Moreover, the region-of-interest is often near such devices which is exactly where image quality degradations are largest. Previous work on known-component reconstruction (KCR) has shown the incorporation of a physical model (e.g. shape, material composition, etc) of the metal component into the reconstruction algorithm can significantly reduce artifacts even near the edge of a metal component. However, for such approaches to be effective, they must have an accurate model of the component that include energy-dependent properties of both the metal device and the CT scanner, placing a burden on system characterization and component material knowledge. In this work, we propose a modified KCR approach that adopts a mixed forward model with a polyenergetic model for the component and a monoenergetic model for the background anatomy. This new approach called Poly-KCR jointly estimates a spectral transfer function associated with known components in addition to the background attenuation values. Thus, this approach eliminates both the need to know component material composition a prior as well as the requirement for an energy-dependent characterization of the CT scanner. We demonstrate the efficacy of this novel approach and illustrate its improved performance over traditional and model-based iterative reconstruction methods in both simulation studies and in physical data including an implanted cadaver sample.

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

PubMed

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

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

PubMed Central

Meng, Bowen; Pratx, Guillem; Xing, Lei

2011-01-01

Purpose: 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. Methods: 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. Results: 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

4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

NASA Astrophysics Data System (ADS)

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-02-01

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp-Davis-Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations.

4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling.

PubMed

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-02-07

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp-Davis-Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations.

4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

PubMed Central

Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

2016-01-01

A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp–Davis–Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations. PMID:26758496

Estimating Patient Dose from X-ray Tube Output Metrics: Automated Measurement of Patient Size from CT Images Enables Large-scale Size-specific Dose Estimates

PubMed Central

Ikuta, Ichiro; Warden, Graham I.; Andriole, Katherine P.; Khorasani, Ramin

2014-01-01

Purpose To test the hypothesis that patient size can be accurately calculated from axial computed tomographic (CT) images, including correction for the effects of anatomy truncation that occur in routine clinical CT image reconstruction. Materials and Methods Institutional review board approval was obtained for this HIPAA-compliant study, with waiver of informed consent. Water-equivalent diameter (DW) was computed from the attenuation-area product of each image within 50 adult CT scans of the thorax and of the abdomen and pelvis and was also measured for maximal field of view (FOV) reconstructions. Linear regression models were created to compare DW with the effective diameter (Deff) used to select size-specific volume CT dose index (CTDIvol) conversion factors as defined in report 204 of the American Association of Physicists in Medicine. Linear regression models relating reductions in measured DW to a metric of anatomy truncation were used to compensate for the effects of clinical image truncation. Results In the thorax, DW versus Deff had an R2 of 0.51 (n = 200, 50 patients at four anatomic locations); in the abdomen and pelvis, R2 was 0.90 (n = 150, 50 patients at three anatomic locations). By correcting for image truncation, the proportion of clinically reconstructed images with an extracted DW within ±5% of the maximal FOV DW increased from 54% to 90% in the thorax (n = 3602 images) and from 95% to 100% in the abdomen and pelvis (6181 images). Conclusion The DW extracted from axial CT images is a reliable measure of patient size, and varying degrees of clinical image truncation can be readily corrected. Automated measurement of patient size combined with CT radiation exposure metrics may enable patient-specific dose estimation on a large scale. © RSNA, 2013 PMID:24086075

Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.

Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan wasmore » performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and

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

PubMed

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

2018-04-18

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

Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177Lu images.

PubMed

Rydén, T; Heydorn Lagerlöf, J; Hemmingsson, J; Marin, I; Svensson, J; Båth, M; Gjertsson, P; Bernhardt, P

2018-01-04

Full Monte Carlo (MC)-based SPECT reconstructions have a strong potential for correcting for image degrading factors, but the reconstruction times are long. The objective of this study was to develop a highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images. The MC code was written in the Compute Unified Device Architecture language for a computer with four graphics processing units (GPUs) (GeForce GTX Titan X, Nvidia, USA). This enabled simulations of parallel photon emissions from the voxels matrix (128 3 or 256 3 ). Each computed tomography (CT) number was converted to attenuation coefficients for photo absorption, coherent scattering, and incoherent scattering. For photon scattering, the deflection angle was determined by the differential scattering cross sections. An angular response function was developed and used to model the accepted angles for photon interaction with the crystal, and a detector scattering kernel was used for modeling the photon scattering in the detector. Predefined energy and spatial resolution kernels for the crystal were used. The MC code was implemented in the OSEM reconstruction of clinical and phantom 177 Lu SPECT/CT images. The Jaszczak image quality phantom was used to evaluate the performance of the MC reconstruction in comparison with attenuated corrected (AC) OSEM reconstructions and attenuated corrected OSEM reconstructions with resolution recovery corrections (RRC). The performance of the MC code was 3200 million photons/s. The required number of photons emitted per voxel to obtain a sufficiently low noise level in the simulated image was 200 for a 128 3 voxel matrix. With this number of emitted photons/voxel, the MC-based OSEM reconstruction with ten subsets was performed within 20 s/iteration. The images converged after around six iterations. Therefore, the reconstruction time was around 3 min. The activity recovery for the spheres in the Jaszczak phantom was

Reconstruction artifacts in VRX CT scanner images

NASA Astrophysics Data System (ADS)

Rendon, David A.; DiBianca, Frank A.; Keyes, Gary S.

2008-03-01

Variable Resolution X-ray (VRX) CT scanners allow imaging of different sized anatomy at the same level of detail using the same device. This is achieved by tilting the x-ray detectors so that the projected size of the detecting elements is varied to produce reconstructions of smaller fields of view with higher spatial resolution. As with regular CT scanners, the images obtained with VRX scanners are affected by different kinds of artifacts of various origins. This work studies some of these artifacts and the impact that the VRX effect has on them. For this, computational models of single-arm single-slice VRX scanners are used to produce images with artifacts commonly found in routine use. These images and artifacts are produced using our VRX CT scanner simulator, which allows us to isolate the system parameters that have a greater effect on the artifacts. A study of the behavior of the artifacts at varying VRX opening angles is presented for scanners implemented using two different detectors. The results show that, although varying the VRX angle will have an effect on the severity of each of the artifacts studied, for some of these artifacts the effect of other factors (such as the distribution of the detector cells and the position of the phantom in the reconstruction grid) is overwhelmingly more significant. This is shown to be the case for streak artifacts produced by thin metallic objects. For some artifacts related to beam hardening, their severity was found to decrease along with the VRX angle. These observations allow us to infer that in regular use the effect of the VRX angle artifacts similar to the ones studied here will not be noticeable as it will be overshadowed by parameters that cannot be easily controlled outside of a computational model.

[Preoperative CT angiography for planning free perforator flaps in breast reconstruction].

PubMed

Kuekrek, H; Müller, D; Paepke, S; Dobritz, M; Machens, H-G; Giunta, R E

2011-04-01

Preoperative Doppler ultrasonography for planning free perforator flaps is widely established to identify preoperatively perforators. The method allows one to localise the penetrating point of the perforator through the abdominal fascia. By this means it is not possible to see the intramuscular course or the position of the perforator in relation to the inferior epigastric artery. Lately the technique of computed tomographic angiography provides an opportunity for visualising the course of perforator vessels in these tissues. This paper summarises our experience with the preoperative CT angiography in our breast centre. Since spring 2009 we have reconstructed the breasts of 44 female patients by using free flaps from the lower abdominal wall. 6 of these were bilateral. In a total number of 50 breast reconstructions we used 23 deep inferior epigastric perforator (DIEP) flaps and 27 muscle-sparing transverse rectus abdominis muscle (TRAM) flaps. In addition to the preoperative ultrasonography, a CT angiography of the lower abdomen was conducted in 29 patients. On average they showed at least 2 perforators on the left as well as right abdominal sides, which could be used as flap vessels based on their signal intensity. Based on their estimated microsurgical dissection complexity, the perforator vessels could be classified into 3 groups: 1) direct perforators of category A with short intramuscular course (39%), 2) perforators with long intramuscular course of category B (50%) and 3) "turn around" perforators of category C, which pass medially around the rectus abdominis (11%). The technique of CT angiography permits a reliable preoperative visualisation of perforators in their entire course and facilitates the selection of the supplying perforator as well as the intraoperative procedure for the surgeon. The suggested classification of perforators into 3 groups simplifies the preoperative assessment of the microsurgical dissection effort. Compared to the commonly used

CT Imaging Findings after Craniosynostosis Reconstructive Surgery.

PubMed

Ginat, Daniel Thomas; Lam, Daniel; Kuhn, Andrew Scott; Reid, Russell

2018-06-06

Several surgical options are available for treating the different types of craniosynostosis, including fronto-orbital advancement and remodeling, total or subtotal cranial vault remodeling, barrel stave osteotomy with cranial remodeling, endoscopic suturectomy, monobloc advancement and cranioplasty, and revision cranioplasty. High-resolution, low-dose CT with 3D reconstructed images and volumetric analysis can be useful for evaluating the craniofacial skeleton following surgery. The various types of craniosynostosis surgery and corresponding imaging findings are reviewed in this article. © 2018 S. Karger AG, Basel.

Spatial and contrast resolution of ultralow dose dentomaxillofacial CT imaging using iterative reconstruction technology

PubMed Central

Bischel, Alexander; Stratis, Andreas; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben

2017-01-01

Objectives: The objective of this study was to determine how iterative reconstruction technology (IRT) influences contrast and spatial resolution in ultralow-dose dentomaxillofacial CT imaging. Methods: A polymethyl methacrylate phantom with various inserts was scanned using a reference protocol (RP) at CT dose index volume 36.56 mGy, a sinus protocol at 18.28 mGy and ultralow-dose protocols (LD) at 4.17 mGy, 2.36 mGy, 0.99 mGy and 0.53 mGy. All data sets were reconstructed using filtered back projection (FBP) and the following IRTs: adaptive statistical iterative reconstructions (ASIRs) (ASIR-50, ASIR-100) and model-based iterative reconstruction (MBIR). Inserts containing line-pair patterns and contrast detail patterns for three different materials were scored by three observers. Observer agreement was analyzed using Cohen's kappa and difference in performance between the protocols and reconstruction was analyzed with Dunn's test at α = 0.05. Results: Interobserver agreement was acceptable with a mean kappa value of 0.59. Compared with the RP using FBP, similar scores were achieved at 2.36 mGy using MBIR. MIBR reconstructions showed the highest noise suppression as well as good contrast even at the lowest doses. Overall, ASIR reconstructions did not outperform FBP. Conclusions: LD and MBIR at a dose reduction of >90% may show no significant differences in spatial and contrast resolution compared with an RP and FBP. Ultralow-dose CT and IRT should be further explored in clinical studies. PMID:28059562

Ultra-Low-Dose Fetal CT With Model-Based Iterative Reconstruction: A Prospective Pilot Study.

PubMed

Imai, Rumi; Miyazaki, Osamu; Horiuchi, Tetsuya; Asano, Keisuke; Nishimura, Gen; Sago, Haruhiko; Nosaka, Shunsuke

2017-06-01

Prenatal diagnosis of skeletal dysplasia by means of 3D skeletal CT examination is highly accurate. However, it carries a risk of fetal exposure to radiation. Model-based iterative reconstruction (MBIR) technology can reduce radiation exposure; however, to our knowledge, the lower limit of an optimal dose is currently unknown. The objectives of this study are to establish ultra-low-dose fetal CT as a method for prenatal diagnosis of skeletal dysplasia and to evaluate the appropriate radiation dose for ultra-low-dose fetal CT. Relationships between tube current and image noise in adaptive statistical iterative reconstruction and MBIR were examined using a 32-cm CT dose index (CTDI) phantom. On the basis of the results of this examination and the recommended methods for the MBIR option and the known relationship between noise and tube current for filtered back projection, as represented by the expression SD = (milliamperes) -0.5 , the lower limit of the optimal dose in ultra-low-dose fetal CT with MBIR was set. The diagnostic power of the CT images obtained using the aforementioned scanning conditions was evaluated, and the radiation exposure associated with ultra-low-dose fetal CT was compared with that noted in previous reports. Noise increased in nearly inverse proportion to the square root of the dose in adaptive statistical iterative reconstruction and in inverse proportion to the fourth root of the dose in MBIR. Ultra-low-dose fetal CT was found to have a volume CTDI of 0.5 mGy. Prenatal diagnosis was accurately performed on the basis of ultra-low-dose fetal CT images that were obtained using this protocol. The level of fetal exposure to radiation was 0.7 mSv. The use of ultra-low-dose fetal CT with MBIR led to a substantial reduction in radiation exposure, compared with the CT imaging method currently used at our institution, but it still enabled diagnosis of skeletal dysplasia without reducing diagnostic power.

Intra-individual diagnostic image quality and organ-specific-radiation dose comparison between spiral cCT with iterative image reconstruction and z-axis automated tube current modulation and sequential cCT.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Gawlitza, Joshua; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Groden, Christoph; Henzler, Thomas

2016-01-01

To prospectively evaluate image quality and organ-specific-radiation dose of spiral cranial CT (cCT) combined with automated tube current modulation (ATCM) and iterative image reconstruction (IR) in comparison to sequential tilted cCT reconstructed with filtered back projection (FBP) without ATCM. 31 patients with a previous performed tilted non-contrast enhanced sequential cCT aquisition on a 4-slice CT system with only FBP reconstruction and no ATCM were prospectively enrolled in this study for a clinical indicated cCT scan. All spiral cCT examinations were performed on a 3rd generation dual-source CT system using ATCM in z-axis direction. Images were reconstructed using both, FBP and IR (level 1-5). A Monte-Carlo-simulation-based analysis was used to compare organ-specific-radiation dose. Subjective image quality for various anatomic structures was evaluated using a 4-point Likert-scale and objective image quality was evaluated by comparing signal-to-noise ratios (SNR). Spiral cCT led to a significantly lower (p < 0.05) organ-specific-radiation dose in all targets including eye lense. Subjective image quality of spiral cCT datasets with an IR reconstruction level 5 was rated significantly higher compared to the sequential cCT acquisitions (p < 0.0001). Consecutive mean SNR was significantly higher in all spiral datasets (FBP, IR 1-5) when compared to sequential cCT with a mean SNR improvement of 44.77% (p < 0.0001). Spiral cCT combined with ATCM and IR allows for significant-radiation dose reduction including a reduce eye lens organ-dose when compared to a tilted sequential cCT while improving subjective and objective image quality.

Feasibility of a low-dose orbital CT protocol with a knowledge-based iterative model reconstruction algorithm for evaluating Graves' orbitopathy.

PubMed

Lee, Ho-Joon; Kim, Jinna; Kim, Ki Wook; Lee, Seung-Koo; Yoon, Jin Sook

2018-06-23

To evaluate the clinical feasibility of low-dose orbital CT with a knowledge-based iterative model reconstruction (IMR) algorithm for evaluating Graves' orbitopathy. Low-dose orbital CT was performed with a CTDI vol of 4.4 mGy. In 12 patients for whom prior or subsequent non-low-dose orbital CT data obtained within 12 months were available, background noise, SNR, and CNR were compared for images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose 4 ), and IMR and non-low-dose CT images. Comparison of clinically relevant measurements for Graves' orbitopathy, such as rectus muscle thickness and retrobulbar fat area, was performed in a subset of 6 patients who underwent CT for causes other than Graves' orbitopathy, by using the Wilcoxon signed-rank test. The lens dose estimated from skin dosimetry on a phantom was 4.13 mGy, which was on average 59.34% lower than that of the non-low-dose protocols. Image quality in terms of background noise, SNR, and CNR was the best for IMR, followed by non-low-dose CT, iDose 4 , and FBP, in descending order. A comparison of clinically relevant measurements revealed no significant difference in the retrobulbar fat area and the inferior and medial rectus muscle thicknesses between the low-dose and non-low-dose CT images. Low-dose CT with IMR may be performed without significantly affecting the measurement of prognostic parameters for Graves' orbitopathy while lowering the lens dose and image noise. Copyright © 2018 Elsevier Inc. All rights reserved.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niemkiewicz, J; Palmiotti, A; Miner, M

2014-06-01

Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU valuesmore » 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

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

PubMed

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.

TU-A-12A-07: CT-Based Biomarkers to Characterize Lung Lesion: Effects of CT Dose, Slice Thickness and Reconstruction Algorithm Based Upon a Phantom Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, B; Tan, Y; Tsai, W

2014-06-15

Purpose: Radiogenomics promises the ability to study cancer tumor genotype from the phenotype obtained through radiographic imaging. However, little attention has been paid to the sensitivity of image features, the image-based biomarkers, to imaging acquisition techniques. This study explores the impact of CT dose, slice thickness and reconstruction algorithm on measuring image features using a thorax phantom. Methods: Twentyfour phantom lesions of known volume (1 and 2mm), shape (spherical, elliptical, lobular and spicular) and density (-630, -10 and +100 HU) were scanned on a GE VCT at four doses (25, 50, 100, and 200 mAs). For each scan, six imagemore » series were reconstructed at three slice thicknesses of 5, 2.5 and 1.25mm with continuous intervals, using the lung and standard reconstruction algorithms. The lesions were segmented with an in-house 3D algorithm. Fifty (50) image features representing lesion size, shape, edge, and density distribution/texture were computed. Regression method was employed to analyze the effect of CT dose, slice of thickness and reconstruction algorithm on these features adjusting 3 confounding factors (size, density and shape of phantom lesions). Results: The coefficients of CT dose, slice thickness and reconstruction algorithm are presented in Table 1 in the supplementary material. No significant difference was found between the image features calculated on low dose CT scans (25mAs and 50mAs). About 50% texture features were found statistically different between low doses and high doses (100 and 200mAs). Significant differences were found for almost all features when calculated on 1.25mm, 2.5mm, and 5mm slice thickness images. Reconstruction algorithms significantly affected all density-based image features, but not morphological features. Conclusions: There is a great need to standardize the CT imaging protocols for radiogenomics study because CT dose, slice thickness and reconstruction algorithm impact quantitative image

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

PubMed

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. • 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.

SU-E-I-33: Initial Evaluation of Model-Based Iterative CT Reconstruction Using Standard Image Quality Phantoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gingold, E; Dave, J

2014-06-01

Purpose: The purpose of this study was to compare a new model-based iterative reconstruction with existing reconstruction methods (filtered backprojection and basic iterative reconstruction) using quantitative analysis of standard image quality phantom images. Methods: An ACR accreditation phantom (Gammex 464) and a CATPHAN600 phantom were scanned using 3 routine clinical acquisition protocols (adult axial brain, adult abdomen, and pediatric abdomen) on a Philips iCT system. Each scan was acquired using default conditions and 75%, 50% and 25% dose levels. Images were reconstructed using standard filtered backprojection (FBP), conventional iterative reconstruction (iDose4) and a prototype model-based iterative reconstruction (IMR). Phantom measurementsmore » included CT number accuracy, contrast to noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD), and noise power spectrum (NPS). Results: The choice of reconstruction method had no effect on CT number accuracy, or MTF (p<0.01). The CNR of a 6 HU contrast target was improved by 1–67% with iDose4 relative to FBP, while IMR improved CNR by 145–367% across all protocols and dose levels. Within each scan protocol, the CNR improvement from IMR vs FBP showed a general trend of greater improvement at lower dose levels. NPS magnitude was greatest for FBP and lowest for IMR. The NPS of the IMR reconstruction showed a pronounced decrease with increasing spatial frequency, consistent with the unusual noise texture seen in IMR images. Conclusion: Iterative Model Reconstruction reduces noise and improves contrast-to-noise ratio without sacrificing spatial resolution in CT phantom images. This offers the possibility of radiation dose reduction and improved low contrast detectability compared with filtered backprojection or conventional iterative reconstruction.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haga, A; Magome, T; Nakano, M

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 volumemore » 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).« less

Accuracy of lung nodule volumetry in low-dose CT with iterative reconstruction: an anthropomorphic thoracic phantom study

PubMed Central

Doo, K W; Yong, H S; Woo, O H; Lee, K Y; Oh, Y-W

2014-01-01

Objective: The purpose of this study was to assess accuracy of lung nodule volumetry in low-dose CT with application of iterative reconstruction (IR) according to nodule size, nodule density and CT tube currents, using artificial lung nodules within an anthropomorphic thoracic phantom. Methods: Eight artificial nodules (four diameters: 5, 8, 10 and 12 mm; two CT densities: −630 HU that represents ground-glass nodule and +100 HU that represents solid nodule) were randomly placed inside a thoracic phantom. Scans were performed with tube current–time product to 10, 20, 30 and 50 mAs. Images were reconstructed with IR and filtered back projection (FBP). We compared volume estimates to a reference standard and calculated the absolute percentage error (APE). Results: The APE of all nodules was significantly lower when IR was used than with FBP (7.5 ± 4.7% compared with 9.0 ±6.9%; p < 0.001). The effect of IR was more pronounced for smaller nodules (p < 0.001). IR showed a significantly lower APE than FBP in ground-glass nodules (p < 0.0001), and the difference was more pronounced at the lowest tube current (11.8 ± 5.9% compared with 21.3 ± 6.1%; p < 0.0001). The effect of IR was most pronounced for ground-glass nodules in the lowest CT tube current. Conclusion: Lung nodule volumetry in low-dose CT by application of IR showed reliable accuracy in a phantom study. Lung nodule volumetry can be reliably applicable to all lung nodules including small, ground-glass nodules even in ultra-low-dose CT with application of IR. Advances in knowledge: IR significantly improved the accuracy of lung nodule volumetry compared with FBP particularly for ground-glass (−630 HU) nodules. Volumetry in low-dose CT can be utilized in patient with lung nodule work-up, and IR has benefit for small, ground-glass lung nodules in low-dose CT. PMID:25026866

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

PubMed

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

2016-01-01

To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

Image quality of multiplanar reconstruction of pulmonary CT scans using adaptive statistical iterative reconstruction.

PubMed

Honda, O; Yanagawa, M; Inoue, A; Kikuyama, A; Yoshida, S; Sumikawa, H; Tobino, K; Koyama, M; Tomiyama, N

2011-04-01

We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). Inflated and fixed lungs were scanned with a garnet detector CT in high-resolution mode (HR mode) or non-high-resolution (HR) mode, and MPR images were then reconstructed. Observers compared 15 MPR images of ASIR (40%) and ASIR (80%) with those of ASIR (0%), and assessed image quality using a visual five-point scale (1, definitely inferior; 5, definitely superior), with particular emphasis on normal pulmonary structures, artefacts, noise and overall image quality. The mean overall image quality scores in HR mode were 3.67 with ASIR (40%) and 4.97 with ASIR (80%). Those in non-HR mode were 3.27 with ASIR (40%) and 3.90 with ASIR (80%). The mean artefact scores in HR mode were 3.13 with ASIR (40%) and 3.63 with ASIR (80%), but those in non-HR mode were 2.87 with ASIR (40%) and 2.53 with ASIR (80%). The mean scores of the other parameters were greater than 3, whereas those in HR mode were higher than those in non-HR mode. There were significant differences between ASIR (40%) and ASIR (80%) in overall image quality (p<0.01). Contrast medium in the injection syringe was scanned to analyse image quality; ASIR did not suppress the severe artefacts of contrast medium. In general, MPR image quality with ASIR (80%) was superior to that with ASIR (40%). However, there was an increased incidence of artefacts by ASIR when CT images were obtained in non-HR mode.

WE-AB-207A-04: Random Undersampled Cone Beam CT: Theoretical Analysis and a Novel Reconstruction Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, C; Chen, L; Jia, X

2016-06-15

Purpose: Reducing x-ray exposure and speeding up data acquisition motived studies on projection data undersampling. It is an important question that for a given undersampling ratio, what the optimal undersampling approach is. In this study, we propose a new undersampling scheme: random-ray undersampling. We will mathematically analyze its projection matrix properties and demonstrate its advantages. We will also propose a new reconstruction method that simultaneously performs CT image reconstruction and projection domain data restoration. Methods: By representing projection operator under the basis of singular vectors of full projection operator, matrix representations for an undersampling case can be generated and numericalmore » singular value decomposition can be performed. We compared properties of matrices among three undersampling approaches: regular-view undersampling, regular-ray undersampling, and the proposed random-ray undersampling. To accomplish CT reconstruction for random undersampling, we developed a novel method that iteratively performs CT reconstruction and missing projection data restoration via regularization approaches. Results: For a given undersampling ratio, random-ray undersampling preserved mathematical properties of full projection operator better than the other two approaches. This translates to advantages of reconstructing CT images at lower errors. Different types of image artifacts were observed depending on undersampling strategies, which were ascribed to the unique singular vectors of the sampling operators in the image domain. We tested the proposed reconstruction algorithm on a Forbid phantom with only 30% of the projection data randomly acquired. Reconstructed image error was reduced from 9.4% in a TV method to 7.6% in the proposed method. Conclusion: The proposed random-ray undersampling is mathematically advantageous over other typical undersampling approaches. It may permit better image reconstruction at the same

Diagnostic Accuracy of CT Enterography for Active Inflammatory Terminal Ileal Crohn Disease: Comparison of Full-Dose and Half-Dose Images Reconstructed with FBP and Half-Dose Images with SAFIRE.

PubMed

Gandhi, Namita S; Baker, Mark E; Goenka, Ajit H; Bullen, Jennifer A; Obuchowski, Nancy A; Remer, Erick M; Coppa, Christopher P; Einstein, David; Feldman, Myra K; Kanmaniraja, Devaraju; Purysko, Andrei S; Vahdat, Noushin; Primak, Andrew N; Karim, Wadih; Herts, Brian R

2016-08-01

Purpose To compare the diagnostic accuracy and image quality of computed tomographic (CT) enterographic images obtained at half dose and reconstructed with filtered back projection (FBP) and sinogram-affirmed iterative reconstruction (SAFIRE) with those of full-dose CT enterographic images reconstructed with FBP for active inflammatory terminal or neoterminal ileal Crohn disease. Materials and Methods This retrospective study was compliant with HIPAA and approved by the institutional review board. The requirement to obtain informed consent was waived. Ninety subjects (45 with active terminal ileal Crohn disease and 45 without Crohn disease) underwent CT enterography with a dual-source CT unit. The reference standard for confirmation of active Crohn disease was active terminal ileal Crohn disease based on ileocolonoscopy or established Crohn disease and imaging features of active terminal ileal Crohn disease. Data from both tubes were reconstructed with FBP (100% exposure); data from the primary tube (50% exposure) were reconstructed with FBP and SAFIRE strengths 3 and 4, yielding four datasets per CT enterographic examination. The mean volume CT dose index (CTDIvol) and size-specific dose estimate (SSDE) at full dose were 13.1 mGy (median, 7.36 mGy) and 15.9 mGy (median, 13.06 mGy), respectively, and those at half dose were 6.55 mGy (median, 3.68 mGy) and 7.95 mGy (median, 6.5 mGy). Images were subjectively evaluated by eight radiologists for quality and diagnostic confidence for Crohn disease. Areas under the receiver operating characteristic curves (AUCs) were estimated, and the multireader, multicase analysis of variance method was used to compare reconstruction methods on the basis of a noninferiority margin of 0.05. Results The mean AUCs with half-dose scans (FBP, 0.908; SAFIRE 3, 0.935; SAFIRE 4, 0.924) were noninferior to the mean AUC with full-dose FBP scans (0.908; P < .003). The proportion of images with inferior quality was significantly higher with all

Radiation dose reduction in CT with adaptive statistical iterative reconstruction (ASIR) for patients with bronchial carcinoma and intrapulmonary metastases.

PubMed

Schäfer, M-L; Lüdemann, L; Böning, G; Kahn, J; Fuchs, S; Hamm, B; Streitparth, F

2016-05-01

To compare the radiation dose and image quality of 64-row chest computed tomography (CT) in patients with bronchial carcinoma or intrapulmonary metastases using full-dose CT reconstructed with filtered back projection (FBP) at baseline and reduced dose with 40% adaptive statistical iterative reconstruction (ASIR) at follow-up. The chest CT images of patients who underwent FBP and ASIR studies were reviewed. Dose-length products (DLP), effective dose, and size-specific dose estimates (SSDEs) were obtained. Image quality was analysed quantitatively by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurement. In addition, image quality was assessed by two blinded radiologists evaluating images for noise, contrast, artefacts, visibility of small structures, and diagnostic acceptability using a five-point scale. The ASIR studies showed 36% reduction in effective dose compared with the FBP studies. The qualitative and quantitative image quality was good to excellent in both protocols, without significant differences. There were also no significant differences for SNR except for the SNR of lung surrounding the tumour (FBP: 35±17, ASIR: 39±22). A protocol with 40% ASIR can provide approximately 36% dose reduction in chest CT of patients with bronchial carcinoma or intrapulmonary metastases while maintaining excellent image quality. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

A fast CT reconstruction scheme for a general multi-core PC.

PubMed

Zeng, Kai; Bai, Erwei; Wang, Ge

2007-01-01

Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.

A Fast CT Reconstruction Scheme for a General Multi-Core PC

PubMed Central

Zeng, Kai; Bai, Erwei; Wang, Ge

2007-01-01

Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors. PMID:18256731

Use of quantitative SPECT/CT reconstruction in 99mTc-sestamibi imaging of patients with renal masses.

PubMed

Jones, Krystyna M; Solnes, Lilja B; Rowe, Steven P; Gorin, Michael A; Sheikhbahaei, Sara; Fung, George; Frey, Eric C; Allaf, Mohamad E; Du, Yong; Javadi, Mehrbod S

2018-02-01

Technetium-99m ( 99m Tc)-sestamibi single-photon emission computed tomography/computed tomography (SPECT/CT) has previously been shown to allow for the accurate differentiation of benign renal oncocytomas and hybrid oncocytic/chromophobe tumors (HOCTs) apart from other malignant renal tumor histologies, with oncocytomas/HOCTs showing high uptake and renal cell carcinoma (RCC) showing low uptake based on uptake ratios from non-quantitative single-photon emission computed tomography (SPECT) reconstructions. However, in this study, several tumors fell close to the uptake ratio cutoff, likely due to limitations in conventional SPECT/CT reconstruction methods. We hypothesized that application of quantitative SPECT/CT (QSPECT) reconstruction methods developed by our group would provide more robust separation of hot and cold lesions, serving as an imaging framework on which quantitative biomarkers can be validated for evaluation of renal masses with 99m Tc-sestamibi. Single-photon emission computed tomography data were reconstructed using the clinical Flash 3D reconstruction and QSPECT methods. Two blinded readers then characterized each tumor as hot or cold. Semi-quantitative uptake ratios were calculated by dividing lesion activity by background renal activity for both Flash 3D and QSPECT reconstructions. The difference between median (mean) hot and cold tumor uptake ratios measured 0.655 (0.73) with the QSPECT method and 0.624 (0.67) with the conventional method, resulting in increased separation between hot and cold tumors. Sub-analysis of 7 lesions near the separation point showed a higher absolute difference (0.16) between QPSECT and Flash 3D mean uptake ratios compared to the remaining lesions. Our finding of improved separation between uptake ratios of hot and cold lesions using QSPECT reconstruction lays the foundation for additional quantitative SPECT techniques such as SPECT-UV in the setting of renal 99m Tc-sestamibi and other SPECT/CT exams. With robust

Effect of low-dose CT and iterative reconstruction on trabecular bone microstructure assessment

NASA Astrophysics Data System (ADS)

Kopp, Felix K.; Baum, Thomas; Nasirudin, Radin A.; Mei, Kai; Garcia, Eduardo G.; Burgkart, Rainer; Rummeny, Ernst J.; Bauer, Jan S.; Noël, Peter B.

2016-03-01

The trabecular bone microstructure is an important factor in the development of osteoporosis. It is well known that its deterioration is one effect when osteoporosis occurs. Previous research showed that the analysis of trabecular bone microstructure enables more precise diagnoses of osteoporosis compared to a sole measurement of the mineral density. Microstructure parameters are assessed on volumetric images of the bone acquired either with high-resolution magnetic resonance imaging, high-resolution peripheral quantitative computed tomography or high-resolution computed tomography (CT), with only CT being applicable to the spine, which is one of clinically most relevant fracture sites. However, due to the high radiation exposure for imaging the whole spine these measurements are not applicable in current clinical routine. In this work, twelve vertebrae from three different donors were scanned with standard and low radiation dose. Trabecular bone microstructure parameters were assessed for CT images reconstructed with statistical iterative reconstruction (SIR) and analytical filtered backprojection (FBP). The resulting structure parameters were correlated to the biomechanically determined fracture load of each vertebra. Microstructure parameters assessed for low-dose data reconstructed with SIR significantly correlated with fracture loads as well as parameters assessed for standard-dose data reconstructed with FBP. Ideal results were achieved with low to zero regularization strength yielding microstructure parameters not significantly different from those assessed for standard-dose FPB data. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

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.

PubMed

Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth; Vardhanabhuti, Varut; Stuckey, Colin; Gutteridge, Catherine; Hyde, Christopher; Roobottom, Carl

2017-10-01

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. • MBIR allows reduced CT dose with similar diagnostic accuracy • MBIR outperforms ASIR when used for the reconstruction of reduced-dose scans • MBIR can be used to accurately assess stones 3 mm and above.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solomon, Justin, E-mail: justin.solomon@duke.edu; Samei, Ehsan

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 onmore » 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

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

PubMed

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

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging.

PubMed

Lauzier, Pascal Theriault; Tang, Jie; Speidel, Michael A; Chen, Guang-Hong

2012-07-01

To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lauzier, Pascal Theriault; Tang Jie; Speidel, Michael A.

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise andmore » streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

PubMed Central

Lauzier, Pascal Thériault; Tang, Jie; Speidel, Michael A.; Chen, Guang-Hong

2012-01-01

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution

Technical note: RabbitCT--an open platform for benchmarking 3D cone-beam reconstruction algorithms.

PubMed

Rohkohl, C; Keck, B; Hofmann, H G; Hornegger, J

2009-09-01

Fast 3D cone beam reconstruction is mandatory for many clinical workflows. For that reason, researchers and industry work hard on hardware-optimized 3D reconstruction. Backprojection is a major component of many reconstruction algorithms that require a projection of each voxel onto the projection data, including data interpolation, before updating the voxel value. This step is the bottleneck of most reconstruction algorithms and the focus of optimization in recent publications. A crucial limitation, however, of these publications is that the presented results are not comparable to each other. This is mainly due to variations in data acquisitions, preprocessing, and chosen geometries and the lack of a common publicly available test dataset. The authors provide such a standardized dataset that allows for substantial comparison of hardware accelerated backprojection methods. They developed an open platform RabbitCT (www.rabbitCT.com) for worldwide comparison in backprojection performance and ranking on different architectures using a specific high resolution C-arm CT dataset of a rabbit. This includes a sophisticated benchmark interface, a prototype implementation in C++, and image quality measures. At the time of writing, six backprojection implementations are already listed on the website. Optimizations include multithreading using Intel threading building blocks and OpenMP, vectorization using SSE, and computation on the GPU using CUDA 2.0. There is a need for objectively comparing backprojection implementations for reconstruction algorithms. RabbitCT aims to provide a solution to this problem by offering an open platform with fair chances for all participants. The authors are looking forward to a growing community and await feedback regarding future evaluations of novel software- and hardware-based acceleration schemes.

Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction

PubMed Central

Yu, Lifeng; Li, Zhoubo; Manduca, Armando; Blezek, Daniel J.; Hough, David M.; Venkatesh, Sudhakar K.; Brickner, Gregory C.; Cernigliaro, Joseph C.; Hara, Amy K.; Fidler, Jeff L.; Lake, David S.; Shiung, Maria; Lewis, David; Leng, Shuai; Augustine, Kurt E.; Carter, Rickey E.; Holmes, David R.; McCollough, Cynthia H.

2015-01-01

Purpose To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). Materials and Methods This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per–malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than −0.10. Results Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: −0.041 [95% CI: −0.090, 0.009] and −0.003 [95% CI: −0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: −0.077, 0.106]), whereas lower-dose FBP images were not (difference −0.049 [95% CI: �

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

PubMed

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 < .01). CNR values were also significantly higher at ASIR levels of ≥40% (P < .01). Blinded qualitative review demonstrated significant improvements in perceived image noise, artifacts, and GM-WM differentiation at ASIR levels ≥60% (P < .01). These results demonstrate that the use of ASIR in adult head CT scans reduces image noise and increases low-contrast resolution, while allowing lower radiation doses without affecting spatial resolution.

Normalization of CT scans reconstructed with different kernels to reduce variability in emphysema measurements

NASA Astrophysics Data System (ADS)

Gallardo Estrella, L.; van Ginneken, B.; van Rikxoort, E. M.

2013-03-01

Chronic Obstructive Pulmonary Disease (COPD) is a lung disease characterized by progressive air flow limitation caused by emphysema and chronic bronchitis. Emphysema is quantified from chest computed tomography (CT) scans as the percentage of attentuation values below a fixed threshold. The emphysema quantification varies substantially between scans reconstructed with different kernels, limiting the possibilities to compare emphysema quantifications obtained from scans with different reconstruction parameters. In this paper we propose a method to normalize scans reconstructed with different kernels to have the same characteristics as scans reconstructed with a reference kernel and investigate if this normalization reduces the variability in emphysema quantification. The proposed normalization splits a CT scan into different frequency bands based on hierarchical unsharp masking. Normalization is performed by changing the energy in each frequency band to the average energy in each band in the reference kernel. A database of 15 subjects with COPD was constructed for this study. All subjects were scanned at total lung capacity and the scans were reconstructed with four different reconstruction kernels. The normalization was applied to all scans. Emphysema quantification was performed before and after normalization. It is shown that the emphysema score varies substantially before normalization but the variation diminishes after normalization.

Image quality of multiplanar reconstruction of pulmonary CT scans using adaptive statistical iterative reconstruction

PubMed Central

Honda, O; Yanagawa, M; Inoue, A; Kikuyama, A; Yoshida, S; Sumikawa, H; Tobino, K; Koyama, M; Tomiyama, N

2011-01-01

Objective We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). Methods Inflated and fixed lungs were scanned with a garnet detector CT in high-resolution mode (HR mode) or non-high-resolution (HR) mode, and MPR images were then reconstructed. Observers compared 15 MPR images of ASIR (40%) and ASIR (80%) with those of ASIR (0%), and assessed image quality using a visual five-point scale (1, definitely inferior; 5, definitely superior), with particular emphasis on normal pulmonary structures, artefacts, noise and overall image quality. Results The mean overall image quality scores in HR mode were 3.67 with ASIR (40%) and 4.97 with ASIR (80%). Those in non-HR mode were 3.27 with ASIR (40%) and 3.90 with ASIR (80%). The mean artefact scores in HR mode were 3.13 with ASIR (40%) and 3.63 with ASIR (80%), but those in non-HR mode were 2.87 with ASIR (40%) and 2.53 with ASIR (80%). The mean scores of the other parameters were greater than 3, whereas those in HR mode were higher than those in non-HR mode. There were significant differences between ASIR (40%) and ASIR (80%) in overall image quality (p<0.01). Contrast medium in the injection syringe was scanned to analyse image quality; ASIR did not suppress the severe artefacts of contrast medium. Conclusion In general, MPR image quality with ASIR (80%) was superior to that with ASIR (40%). However, there was an increased incidence of artefacts by ASIR when CT images were obtained in non-HR mode. PMID:21081572

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Reconstruction for proton computed tomography by tracing proton trajectories: A Monte Carlo study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Tianfang; Liang Zhengrong; Singanallur, Jayalakshmi V.

Proton computed tomography (pCT) has been explored in the past decades because of its unique imaging characteristics, low radiation dose, and its possible use for treatment planning and on-line target localization in proton therapy. However, reconstruction of pCT images is challenging because the proton path within the object to be imaged is statistically affected by multiple Coulomb scattering. In this paper, we employ GEANT4-based Monte Carlo simulations of the two-dimensional pCT reconstruction of an elliptical phantom to investigate the possible use of the algebraic reconstruction technique (ART) with three different path-estimation methods for pCT reconstruction. The first method assumes amore » straight-line path (SLP) connecting the proton entry and exit positions, the second method adapts the most-likely path (MLP) theoretically determined for a uniform medium, and the third method employs a cubic spline path (CSP). The ART reconstructions showed progressive improvement of spatial resolution when going from the SLP [2 line pairs (lp) cm{sup -1}] to the curved CSP and MLP path estimates (5 lp cm{sup -1}). The MLP-based ART algorithm had the fastest convergence and smallest residual error of all three estimates. This work demonstrates the advantage of tracking curved proton paths in conjunction with the ART algorithm and curved path estimates.« less

Appearance of bony lesions on 3-D CT reconstructions: a case study in variable renderings

NASA Astrophysics Data System (ADS)

Mankovich, Nicholas J.; White, Stuart C.

1992-05-01

This paper discusses conventional 3-D reconstruction for bone visualization and presents a case study to demonstrate the dangers of performing 3-D reconstructions without careful selection of the bone threshold. The visualization of midface bone lesions directly from axial CT images is difficult because of the complex anatomic relationships. Three-dimensional reconstructions made from the CT to provide graphic images showing lesions in relation to adjacent facial bones. Most commercially available 3-D image reconstruction requires that the radiologist or technologist identify a threshold image intensity value that can be used to distinguish bone from other tissues. Much has been made of the many disadvantages of this technique, but it continues as the predominant method in producing 3-D pictures for clinical use. This paper is intended to provide a clear demonstration for the physician of the caveats that should accompany 3-D reconstructions. We present a case of recurrent odontogenic keratocyst in the anterior maxilla where the 3-D reconstructions, made with different bone thresholds (windows), are compared to the resected specimen. A DMI 3200 computer was used to convert the scan data from a GE 9800 CT into a 3-D shaded surface image. Threshold values were assigned to (1) generate the most clinically pleasing image, (2) produce maximum theoretical fidelity (using the midpoint image intensity between average cortical bone and average soft tissue), and (3) cover stepped threshold intensities between these two methods. We compared the computer lesions with the resected specimen and noted measurement errors of up to 44 percent introduced by inappropriate bone threshold levels. We suggest clinically applicable standardization techniques in the 3-D reconstruction as well as cautionary language that should accompany the 3-D images.

Estimation of skull table thickness with clinical CT and validation with microCT.

PubMed

Lillie, Elizabeth M; Urban, Jillian E; Weaver, Ashley A; Powers, Alexander K; Stitzel, Joel D

2015-01-01

Brain injuries resulting from motor vehicle crashes (MVC) are extremely common yet the details of the mechanism of injury remain to be well characterized. Skull deformation is believed to be a contributing factor to some types of traumatic brain injury (TBI). Understanding biomechanical contributors to skull deformation would provide further insight into the mechanism of head injury resulting from blunt trauma. In particular, skull thickness is thought be a very important factor governing deformation of the skull and its propensity for fracture. Current computed tomography (CT) technology is limited in its ability to accurately measure cortical thickness using standard techniques. A method to evaluate cortical thickness using cortical density measured from CT data has been developed previously. This effort validates this technique for measurement of skull table thickness in clinical head CT scans using two postmortem human specimens. Bone samples were harvested from the skulls of two cadavers and scanned with microCT to evaluate the accuracy of the estimated cortical thickness measured from clinical CT. Clinical scans were collected at 0.488 and 0.625 mm in plane resolution with 0.625 mm thickness. The overall cortical thickness error was determined to be 0.078 ± 0.58 mm for cortical samples thinner than 4 mm. It was determined that 91.3% of these differences fell within the scanner resolution. Color maps of clinical CT thickness estimations are comparable to color maps of microCT thickness measurements, indicating good quantitative agreement. These data confirm that the cortical density algorithm successfully estimates skull table thickness from clinical CT scans. The application of this technique to clinical CT scans enables evaluation of cortical thickness in population-based studies. © 2014 Anatomical Society.

Influence of Ultra-Low-Dose and Iterative Reconstructions on the Visualization of Orbital Soft Tissues on Maxillofacial CT.

PubMed

Widmann, G; Juranek, D; Waldenberger, F; Schullian, P; Dennhardt, A; Hoermann, R; Steurer, M; Gassner, E-M; Puelacher, W

2017-08-01

Dose reduction on CT scans for surgical planning and postoperative evaluation of midface and orbital fractures is an important concern. The purpose of this study was to evaluate the variability of various low-dose and iterative reconstruction techniques on the visualization of orbital soft tissues. Contrast-to-noise ratios of the optic nerve and inferior rectus muscle and subjective scores of a human cadaver were calculated from CT with a reference dose protocol (CT dose index volume = 36.69 mGy) and a subsequent series of low-dose protocols (LDPs I-4: CT dose index volume = 4.18, 2.64, 0.99, and 0.53 mGy) with filtered back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR)-50, ASIR-100, and model-based iterative reconstruction. The Dunn Multiple Comparison Test was used to compare each combination of protocols (α = .05). Compared with the reference dose protocol with FBP, the following statistically significant differences in contrast-to-noise ratios were shown (all, P ≤ .012) for the following: 1) optic nerve: LDP-I with FBP; LDP-II with FBP and ASIR-50; LDP-III with FBP, ASIR-50, and ASIR-100; and LDP-IV with FBP, ASIR-50, and ASIR-100; and 2) inferior rectus muscle: LDP-II with FBP, LDP-III with FBP and ASIR-50, and LDP-IV with FBP, ASIR-50, and ASIR-100. Model-based iterative reconstruction showed the best contrast-to-noise ratio in all images and provided similar subjective scores for LDP-II. ASIR-50 had no remarkable effect, and ASIR-100, a small effect on subjective scores. Compared with a reference dose protocol with FBP, model-based iterative reconstruction may show similar diagnostic visibility of orbital soft tissues at a CT dose index volume of 2.64 mGy. Low-dose technology and iterative reconstruction technology may redefine current reference dose levels in maxillofacial CT. © 2017 by American Journal of Neuroradiology.

Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, Zhye, E-mail: yin@ge.com; De Man, Bruno; Yao, Yangyang

Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies tomore » achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.« less

Direct reconstruction in CT-analogous pharmacokinetic diffuse fluorescence tomography: two-dimensional simulative and experimental validations

NASA Astrophysics Data System (ADS)

Wang, Xin; Zhang, Yanqi; Zhang, Limin; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng

2016-04-01

We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.

The Detection of Focal Liver Lesions Using Abdominal CT: A Comparison of Image Quality Between Adaptive Statistical Iterative Reconstruction V and Adaptive Statistical Iterative Reconstruction.

PubMed

Lee, Sangyun; Kwon, Heejin; Cho, Jihan

2016-12-01

To investigate image quality characteristics of abdominal computed tomography (CT) scans reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) vs currently using applied adaptive statistical iterative reconstruction (ASIR). This institutional review board-approved study included 35 consecutive patients who underwent CT of the abdomen. Among these 35 patients, 27 with focal liver lesions underwent abdomen CT with a 128-slice multidetector unit using the following parameters: fixed noise index of 30, 1.25 mm slice thickness, 120 kVp, and a gantry rotation time of 0.5 seconds. CT images were analyzed depending on the method of reconstruction: ASIR (30%, 50%, and 70%) vs ASIR-V (30%, 50%, and 70%). Three radiologists independently assessed randomized images in a blinded manner. Imaging sets were compared to focal lesion detection numbers, overall image quality, and objective noise with a paired sample t test. Interobserver agreement was assessed with the intraclass correlation coefficient. The detection of small focal liver lesions (<10 mm) was significantly higher when ASIR-V was used when compared to ASIR (P <0.001). Subjective image noise, artifact, and objective image noise in liver were generally significantly better for ASIR-V compared to ASIR, especially in 50% ASIR-V. Image sharpness and diagnostic acceptability were significantly worse in 70% ASIR-V compared to various levels of ASIR. Images analyzed using 50% ASIR-V were significantly better than three different series of ASIR or other ASIR-V conditions at providing diagnostically acceptable CT scans without compromising image quality and in the detection of focal liver lesions. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Impact of joint statistical dual-energy CT reconstruction of proton stopping power images: Comparison to image- and sinogram-domain material decomposition approaches.

PubMed

Zhang, Shuangyue; Han, Dong; Politte, David G; Williamson, Jeffrey F; O'Sullivan, Joseph A

2018-05-01

The purpose of this study was to assess the performance of a novel dual-energy CT (DECT) approach for proton stopping power ratio (SPR) mapping that integrates image reconstruction and material characterization using a joint statistical image reconstruction (JSIR) method based on a linear basis vector model (BVM). A systematic comparison between the JSIR-BVM method and previously described DECT image- and sinogram-domain decomposition approaches is also carried out on synthetic data. The JSIR-BVM method was implemented to estimate the electron densities and mean excitation energies (I-values) required by the Bethe equation for SPR mapping. In addition, image- and sinogram-domain DECT methods based on three available SPR models including BVM were implemented for comparison. The intrinsic SPR modeling accuracy of the three models was first validated. Synthetic DECT transmission sinograms of two 330 mm diameter phantoms each containing 17 soft and bony tissues (for a total of 34) of known composition were then generated with spectra of 90 and 140 kVp. The estimation accuracy of the reconstructed SPR images were evaluated for the seven investigated methods. The impact of phantom size and insert location on SPR estimation accuracy was also investigated. All three selected DECT-SPR models predict the SPR of all tissue types with less than 0.2% RMS errors under idealized conditions with no reconstruction uncertainties. When applied to synthetic sinograms, the JSIR-BVM method achieves the best performance with mean and RMS-average errors of less than 0.05% and 0.3%, respectively, for all noise levels, while the image- and sinogram-domain decomposition methods show increasing mean and RMS-average errors with increasing noise level. The JSIR-BVM method also reduces statistical SPR variation by sixfold compared to other methods. A 25% phantom diameter change causes up to 4% SPR differences for the image-domain decomposition approach, while the JSIR-BVM method and sinogram

WE-G-18A-03: Cone Artifacts Correction in Iterative Cone Beam CT Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, H; Folkerts, M; Jiang, S

Purpose: For iterative reconstruction (IR) in cone-beam CT (CBCT) imaging, data truncation along the superior-inferior (SI) direction causes severe cone artifacts in the reconstructed CBCT volume images. Not only does it reduce the effective SI coverage of the reconstructed volume, it also hinders the IR algorithm convergence. This is particular a problem for regularization based IR, where smoothing type regularization operations tend to propagate the artifacts to a large area. It is our purpose to develop a practical cone artifacts correction solution. Methods: We found it is the missing data residing in the truncated cone area that leads to inconsistencymore » between the calculated forward projections and measured projections. We overcome this problem by using FDK type reconstruction to estimate the missing data and design weighting factors to compensate the inconsistency caused by the missing data. We validate the proposed methods in our multi-GPU low-dose CBCT reconstruction system on multiple patients' datasets. Results: Compared to the FDK reconstruction with full datasets, while IR is able to reconstruct CBCT images using a subset of projection data, the severe cone artifacts degrade overall image quality. For head-neck case under a full-fan mode, 13 out of 80 slices are contaminated. It is even more severe in pelvis case under half-fan mode, where 36 out of 80 slices are affected, leading to inferior soft-tissue delineation. By applying the proposed method, the cone artifacts are effectively corrected, with a mean intensity difference decreased from ∼497 HU to ∼39HU for those contaminated slices. Conclusion: A practical and effective solution for cone artifacts correction is proposed and validated in CBCT IR algorithm. This study is supported in part by NIH (1R01CA154747-01)« less

Local reconstruction in computed tomography of diffraction enhanced imaging

NASA Astrophysics Data System (ADS)

Huang, Zhi-Feng; Zhang, Li; Kang, Ke-Jun; Chen, Zhi-Qiang; Zhu, Pei-Ping; Yuan, Qing-Xi; Huang, Wan-Xia

2007-07-01

Computed tomography of diffraction enhanced imaging (DEI-CT) based on synchrotron radiation source has extremely high sensitivity of weakly absorbing low-Z samples in medical and biological fields. The authors propose a modified backprojection filtration(BPF)-type algorithm based on PI-line segments to reconstruct region of interest from truncated refraction-angle projection data in DEI-CT. The distribution of refractive index decrement in the sample can be directly estimated from its reconstruction images, which has been proved by experiments at the Beijing Synchrotron Radiation Facility. The algorithm paves the way for local reconstruction of large-size samples by the use of DEI-CT with small field of view based on synchrotron radiation source.

Combined use of iterative reconstruction and monochromatic imaging in spinal fusion CT images.

PubMed

Wang, Fengdan; Zhang, Yan; Xue, Huadan; Han, Wei; Yang, Xianda; Jin, Zhengyu; Zwar, Richard

2017-01-01

Spinal fusion surgery is an important procedure for treating spinal diseases and computed tomography (CT) is a critical tool for postoperative evaluation. However, CT image quality is considerably impaired by metal artifacts and image noise. To explore whether metal artifacts and image noise can be reduced by combining two technologies, adaptive statistical iterative reconstruction (ASIR) and monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. A total of 51 patients with 318 spinal pedicle screws were prospectively scanned by dual-energy CT using fast kV-switching GSI between 80 and 140 kVp. Monochromatic GSI images at 110 keV were reconstructed either without or with various levels of ASIR (30%, 50%, 70%, and 100%). The quality of five sets of images was objectively and subjectively assessed. With objective image quality assessment, metal artifacts decreased when increasing levels of ASIR were applied (P < 0.001). Moreover, adding ASIR to GSI also decreased image noise (P < 0.001) and improved the signal-to-noise ratio (P < 0.001). The subjective image quality analysis showed good inter-reader concordance, with intra-class correlation coefficients between 0.89 and 0.99. The visualization of peri-implant soft tissue was improved at higher ASIR levels (P < 0.001). Combined use of ASIR and GSI decreased image noise and improved image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels ≥70%. © The Foundation Acta Radiologica 2016.

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

NASA Astrophysics Data System (ADS)

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.

Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose.

PubMed

Aurumskjöld, Marie-Louise; Söderberg, Marcus; Stålhammar, Fredrik; von Steyern, Kristina Vult; Tingberg, Anders; Ydström, Kristina

2018-06-01

Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose 4 ), and images from the low-dose examinations were reconstructed with both iDose 4 and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose 4 and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose 4 images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60-0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose 4 method for evaluating pediatric abdominal CT, even with a 32% dose reduction.

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

NASA Astrophysics Data System (ADS)

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.

Influence of iterative reconstruction on coronary calcium scores at multiple heart rates: a multivendor phantom study on state-of-the-art CT systems.

PubMed

van der Werf, N R; Willemink, M J; Willems, T P; Greuter, M J W; Leiner, T

2017-12-28

The objective of this study was to evaluate the influence of iterative reconstruction on coronary calcium scores (CCS) at different heart rates for four state-of-the-art CT systems. Within an anthropomorphic chest phantom, artificial coronary arteries were translated in a water-filled compartment. The arteries contained three different calcifications with low (38 mg), medium (80 mg) and high (157 mg) mass. Linear velocities were applied, corresponding to heart rates of 0, < 60, 60-75 and > 75 bpm. Data were acquired on four state-of-the-art CT systems (CT1-CT4) with routinely used CCS protocols. Filtered back projection (FBP) and three increasing levels of iterative reconstruction (L1-L3) were used for reconstruction. CCS were quantified as Agatston score and mass score. An iterative reconstruction susceptibility (IRS) index was used to assess susceptibility of Agatston score (IRS AS ) and mass score (IRS MS ) to iterative reconstruction. IRS values were compared between CT systems and between calcification masses. For each heart rate, differences in CCS of iterative reconstructed images were evaluated with CCS of FBP images as reference, and indicated as small (< 5%), medium (5-10%) or large (> 10%). Statistical analysis was performed with repeated measures ANOVA tests. While subtle differences were found for Agatston scores of low mass calcification, medium and high mass calcifications showed increased CCS up to 77% with increasing heart rates. IRS AS of CT1-T4 were 17, 41, 130 and 22% higher than IRS MS . Not only were IRS significantly different between all CT systems, but also between calcification masses. Up to a fourfold increase in IRS was found for the low mass calcification in comparison with the high mass calcification. With increasing iterative reconstruction strength, maximum decreases of 21 and 13% for Agatston and mass score were found. In total, 21 large differences between Agatston scores from FBP and iterative reconstruction were found

Accuracy of iodine quantification in dual-layer spectral CT: Influence of iterative reconstruction, patient habitus and tube parameters.

PubMed

Sauter, Andreas P; Kopp, Felix K; Münzel, Daniela; Dangelmaier, Julia; Renz, Martin; Renger, Bernhard; Braren, Rickmer; Fingerle, Alexander A; Rummeny, Ernst J; Noël, Peter B

2018-05-01

Evaluation of the influence of iterative reconstruction, tube settings and patient habitus on the accuracy of iodine quantification with dual-layer spectral CT (DL-CT). A CT abdomen phantom with different extension rings and four iodine inserts (1, 2, 5 and 10 mg/ml) was scanned on a DL-CT. The phantom was scanned with tube-voltages of 120 and 140 kVp and CTDI vol of 2.5, 5, 10 and 20 mGy. Reconstructions were performed for eight levels of iterative reconstruction (i0-i7). Diagnostic dose levels are classified depending on patient-size and radiation dose. Measurements of iodine concentration showed accurate and reliable results. Taking all CTDI vol -levels into account, the mean absolute percentage difference (MAPD) showed less accuracy for low CTDI vol -levels (2.5 mGy: 34.72%) than for high CTDI vol -levels (20 mGy: 5.89%). At diagnostic dose levels, accurate quantification of iodine was possible (MAPD 3.38%). Level of iterative reconstruction did not significantly influence iodine measurements. Iodine quantification worked more accurately at a tube voltage of 140 kVp. Phantom size had a considerable effect only at low-dose-levels; at diagnostic dose levels the effect of phantom size decreased (MAPD <5% for all phantom sizes). With DL-CT, even low iodine concentrations can be accurately quantified. Accuracies are higher when diagnostic radiation doses are employed. Copyright © 2018 Elsevier B.V. All rights reserved.

Micro CT based truth estimation of nodule volume

NASA Astrophysics Data System (ADS)

Kinnard, L. M.; Gavrielides, M. A.; Myers, K. J.; Zeng, R.; Whiting, B.; Lin-Gibson, S.; Petrick, N.

2010-03-01

With the advent of high-resolution CT, three-dimensional (3D) methods for nodule volumetry have been introduced, with the hope that such methods will be more accurate and consistent than currently used planar measures of size. However, the error associated with volume estimation methods still needs to be quantified. Volume estimation error is multi-faceted in the sense that there is variability associated with the patient, the software tool and the CT system. A primary goal of our current research efforts is to quantify the various sources of measurement error and, when possible, minimize their effects. In order to assess the bias of an estimate, the actual value, or "truth," must be known. In this work we investigate the reliability of micro CT to determine the "true" volume of synthetic nodules. The advantage of micro CT over other truthing methods is that it can provide both absolute volume and shape information in a single measurement. In the current study we compare micro CT volume truth to weight-density truth for spherical, elliptical, spiculated and lobulated nodules with diameters from 5 to 40 mm, and densities of -630 and +100 HU. The percent differences between micro CT and weight-density volume for -630 HU nodules range from [-21.7%, -0.6%] (mean= -11.9%) and the differences for +100 HU nodules range from [-0.9%, 3.0%] (mean=1.7%).

Evaluating the effect of increased pitch, iterative reconstruction and dual source CT on dose reduction and image quality.

PubMed

Gariani, Joanna; Martin, Steve P; Botsikas, Diomidis; Becker, Christoph D; Montet, Xavier

2018-06-14

To compare radiation dose and image quality of thoracoabdominal scans obtained with a high-pitch protocol (pitch 3.2) and iterative reconstruction (Sinogram Affirmed Iterative Reconstruction) in comparison to standard pitch reconstructed with filtered back projection (FBP) using dual source CT. 114 CT scans (Somatom Definition Flash, Siemens Healthineers, Erlangen, Germany), 39 thoracic scans, 54 thoracoabdominal scans and 21 abdominal scans were performed. Analysis of three protocols was undertaken; pitch of 1 reconstructed with FBP, pitch of 3.2 reconstructed with SAFIRE, pitch of 3.2 with stellar detectors reconstructed with SAFIRE. Objective and subjective image analysis were performed. Dose differences of the protocols used were compared. Dose was reduced when comparing scans with a pitch of 1 reconstructed with FBP to high-pitch scans with a pitch of 3.2 reconstructed with SAFIRE with a reduction of volume CT dose index of 75% for thoracic scans, 64% for thoracoabdominal scans and 67% for abdominal scans. There was a further reduction after the implementation of stellar detectors reflected in a reduction of 36% of the dose-length product for thoracic scans. This was not at the detriment of image quality, contrast-to-noise ratio, signal-to-noise ratio and the qualitative image analysis revealed a superior image quality in the high-pitch protocols. The combination of a high pitch protocol with iterative reconstruction allows significant dose reduction in routine chest and abdominal scans whilst maintaining or improving diagnostic image quality, with a further reduction in thoracic scans with stellar detectors. Advances in knowledge: High pitch imaging with iterative reconstruction is a tool that can be used to reduce dose without sacrificing image quality.

Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

NASA Astrophysics Data System (ADS)

Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

2017-03-01

In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

Development of a method to estimate organ doses for pediatric CT examinations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papadakis, Antonios E., E-mail: apapadak@pagni.gr; Perisinakis, Kostas; Damilakis, John

Purpose: To develop a method for estimating doses to primarily exposed organs in pediatric CT by taking into account patient size and automatic tube current modulation (ATCM). Methods: A Monte Carlo CT dosimetry software package, which creates patient-specific voxelized phantoms, accurately simulates CT exposures, and generates dose images depicting the energy imparted on the exposed volume, was used. Routine head, thorax, and abdomen/pelvis CT examinations in 92 pediatric patients, ranging from 1-month to 14-yr-old (49 boys and 43 girls), were simulated on a 64-slice CT scanner. Two sets of simulations were performed in each patient using (i) a fixed tubemore » current (FTC) value over the entire examination length and (ii) the ATCM profile extracted from the DICOM header of the reconstructed images. Normalized to CTDI{sub vol} organ dose was derived for all primary irradiated radiosensitive organs. Normalized dose data were correlated to patient’s water equivalent diameter using log-transformed linear regression analysis. Results: The maximum percent difference in normalized organ dose between FTC and ATCM acquisitions was 10% for eyes in head, 26% for thymus in thorax, and 76% for kidneys in abdomen/pelvis. In most of the organs, the correlation between dose and water equivalent diameter was significantly improved in ATCM compared to FTC acquisitions (P < 0.001). Conclusions: The proposed method employs size specific CTDI{sub vol}-normalized organ dose coefficients for ATCM-activated and FTC acquisitions in pediatric CT. These coefficients are substantially different between ATCM and FTC modes of operation and enable a more accurate assessment of patient-specific organ dose in the clinical setting.« less

Submillisievert Radiation Dose Coronary CT Angiography: Clinical Impact of the Knowledge-Based Iterative Model Reconstruction.

PubMed

Iyama, Yuji; Nakaura, Takeshi; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Sakaino, Naritsugu; Tokuyasu, Shinichi; Osakabe, Hirokazu; Harada, Kazunori; Yamashita, Yasuyuki

2016-11-01

The purpose of this study was to evaluate the noise and image quality of images reconstructed with a knowledge-based iterative model reconstruction (knowledge-based IMR) in ultra-low dose cardiac computed tomography (CT). We performed submillisievert radiation dose coronary CT angiography on 43 patients. We also performed a phantom study to evaluate the influence of object size with the automatic exposure control phantom. We reconstructed clinical and phantom studies with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and knowledge-based IMR. We measured effective dose of patients and compared CT number, image noise, and contrast noise ratio in ascending aorta of each reconstruction technique. We compared the relationship between image noise and body mass index for the clinical study, and object size for phantom study. The mean effective dose was 0.98 ± 0.25 mSv. The image noise of knowledge-based IMR images was significantly lower than those of FBP and hybrid IR images (knowledge-based IMR: 19.4 ± 2.8; FBP: 126.7 ± 35.0; hybrid IR: 48.8 ± 12.8, respectively) (P < .01). The contrast noise ratio of knowledge-based IMR images was significantly higher than those of FBP and hybrid IR images (knowledge-based IMR: 29.1 ± 5.4; FBP: 4.6 ± 1.3; hybrid IR: 13.1 ± 3.5, respectively) (P < .01). There were moderate correlations between image noise and body mass index in FBP (r = 0.57, P < .01) and hybrid IR techniques (r = 0.42, P < .01); however, these correlations were weak in knowledge-based IMR (r = 0.27, P < .01). Compared to FBP and hybrid IR, the knowledge-based IMR offers significant noise reduction and improvement in image quality in submillisievert radiation dose cardiac CT. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR)

NASA Astrophysics Data System (ADS)

Wang, Tonghe; Zhu, Lei

2016-09-01

Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an

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

PubMed

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Hao; Folkerts, Michael; Jiang, Steve B., E-mail: xun.jia@utsouthwestern.edu, E-mail: steve.jiang@UTSouthwestern.edu

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 inventedmore » 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

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, C; Qi, H; Chen, Z

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using meanmore » filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.« less

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

PubMed

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.

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

PubMed

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

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

PubMed

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.

Performance analysis of model based iterative reconstruction with dictionary learning in transportation security CT

NASA Astrophysics Data System (ADS)

Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno

2016-05-01

In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.

A high-resolution photon-counting breast CT system with tensor-framelet based iterative image reconstruction for radiation dose reduction

NASA Astrophysics Data System (ADS)

Ding, Huanjun; Gao, Hao; Zhao, Bo; Cho, Hyo-Min; Molloi, Sabee

2014-10-01

Both computer simulations and experimental phantom studies were carried out to investigate the radiation dose reduction with tensor framelet based iterative image reconstruction (TFIR) for a dedicated high-resolution spectral breast computed tomography (CT) based on a silicon strip photon-counting detector. The simulation was performed with a 10 cm-diameter water phantom including three contrast materials (polyethylene, 8 mg ml-1 iodine and B-100 bone-equivalent plastic). In the experimental study, the data were acquired with a 1.3 cm-diameter polymethylmethacrylate (PMMA) phantom containing iodine in three concentrations (8, 16 and 32 mg ml-1) at various radiation doses (1.2, 2.4 and 3.6 mGy) and then CT images were reconstructed using the filtered-back-projection (FBP) technique and the TFIR technique, respectively. The image quality between these two techniques was evaluated by the quantitative analysis on contrast-to-noise ratio (CNR) and spatial resolution that was evaluated using the task-based modulation transfer function (MTF). Both the simulation and experimental results indicated that the task-based MTF obtained from TFIR reconstruction with one-third of the radiation dose was comparable to that from the FBP reconstruction for low contrast target. For high contrast target, the TFIR was substantially superior to the FBP reconstruction in terms of spatial resolution. In addition, TFIR was able to achieve a factor of 1.6-1.8 increase in CNR, depending on the target contrast level. This study demonstrates that the TFIR can reduce the required radiation dose by a factor of two-thirds for a CT image reconstruction compared to the FBP technique. It achieves much better CNR and spatial resolution for high contrast target in addition to retaining similar spatial resolution for low contrast target. This TFIR technique has been implemented with a graphic processing unit system and it takes approximately 10 s to reconstruct a single-slice CT image

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

PubMed

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.

Autocalibration method for non-stationary CT bias correction.

PubMed

Vegas-Sánchez-Ferrero, Gonzalo; Ledesma-Carbayo, Maria J; Washko, George R; Estépar, Raúl San José

2018-02-01

Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases. Copyright © 2017 Elsevier B.V. All rights reserved.

Estimation of radiation cancer risk in CT-KUB

NASA Astrophysics Data System (ADS)

Karim, M. K. A.; Hashim, S.; Bakar, K. A.; Bradley, D. A.; Ang, W. C.; Bahrudin, N. A.; Mhareb, M. H. A.

2017-08-01

The increased demand for computed tomography (CT) in radiological scanning examinations raises the question of a potential health impact from the associated radiation exposures. Focusing on CT kidney-ureter-bladder (CT-KUB) procedures, this work was aimed at determining organ equivalent dose using a commercial CT dose calculator and providing an estimate of cancer risks. The study, which included 64 patients (32 males and 32 females, mean age 55.5 years and age range 30-80 years), involved use of a calibrated CT scanner (Siemens-Somatom Emotion 16-slice). The CT exposures parameter including tube potential, pitch factor, tube current, volume CT dose index (CTDIvol) and dose-length product (DLP) were recorded and analyzed using CT-EXPO (Version 2.3.1, Germany). Patient organ doses, including for stomach, liver, colon, bladder, red bone marrow, prostate and ovaries were calculated and converted into cancer risks using age- and sex-specific data published in the Biological Effects of Ionizing Radiation (BEIR) VII report. With a median value scan range of 36.1 cm, the CTDIvol, DLP, and effective dose were found to be 10.7 mGy, 390.3 mGy cm and 6.2 mSv, respectively. The mean cancer risks for males and females were estimated to be respectively 25 and 46 out of 100,000 procedures with effective doses between 4.2 mSv and 10.1 mSv. Given the increased cancer risks from current CT-KUB procedures compared to conventional examinations, we propose that the low dose protocols for unenhanced CT procedures be taken into consideration before establishing imaging protocols for CT-KUB.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: experimental assessment of noise performance.

PubMed

Li, Ke; Tang, Jie; Chen, Guang-Hong

2014-04-01

To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo(®), GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a "redder" NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose)(-β) with the component β ≈ 0.25, which violated the classical σ ∝ (dose)(-0.5) power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial uniformity when compared with FBP. (6) A composite image

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

PubMed

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

2007-10-07

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.

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

PubMed Central

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

2010-01-01

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. PMID:20376330

Compressive Sampling Based Interior Reconstruction for Dynamic Carbon Nanotube Micro-CT

PubMed Central

Yu, Hengyong; Cao, Guohua; Burk, Laurel; Lee, Yueh; Lu, Jianping; Santago, Pete; Zhou, Otto; Wang, Ge

2010-01-01

In the computed tomography (CT) field, one recent invention is the so-called carbon nanotube (CNT) based field emission x-ray technology. On the other hand, compressive sampling (CS) based interior tomography is a new innovation. Combining the strengths of these two novel subjects, we apply the interior tomography technique to local mouse cardiac imaging using respiration and cardiac gating with a CNT based micro-CT scanner. The major features of our method are: (1) it does not need exact prior knowledge inside an ROI; and (2) two orthogonal scout projections are employed to regularize the reconstruction. Both numerical simulations and in vivo mouse studies are performed to demonstrate the feasibility of our methodology. PMID:19923686

The role of advanced reconstruction algorithms in cardiac CT

PubMed Central

Halliburton, Sandra S.; Tanabe, Yuki; Partovi, Sasan

2017-01-01

Non-linear iterative reconstruction (IR) algorithms have been increasingly incorporated into clinical cardiac CT protocols at institutions around the world. Multiple IR algorithms are available commercially from various vendors. IR algorithms decrease image noise and are primarily used to enable lower radiation dose protocols. IR can also be used to improve image quality for imaging of obese patients, coronary atherosclerotic plaques, coronary stents, and myocardial perfusion. In this article, we will review the various applications of IR algorithms in cardiac imaging and evaluate how they have changed practice. PMID:29255694

WE-G-207-04: Non-Local Total-Variation (NLTV) Combined with Reweighted L1-Norm for Compressed Sensing Based CT Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, H; Chen, J; Pouliot, J

2015-06-15

Purpose: Compressed sensing (CS) has been used for CT (4DCT/CBCT) reconstruction with few projections to reduce dose of radiation. Total-variation (TV) in L1-minimization (min.) with local information is the prevalent technique in CS, while it can be prone to noise. To address the problem, this work proposes to apply a new image processing technique, called non-local TV (NLTV), to CS based CT reconstruction, and incorporate reweighted L1-norm into it for more precise reconstruction. Methods: TV minimizes intensity variations by considering two local neighboring voxels, which can be prone to noise, possibly damaging the reconstructed CT image. NLTV, contrarily, utilizes moremore » global information by computing a weight function of current voxel relative to surrounding search area. In fact, it might be challenging to obtain an optimal solution due to difficulty in defining the weight function with appropriate parameters. Introducing reweighted L1-min., designed for approximation to ideal L0-min., can reduce the dependence on defining the weight function, therefore improving accuracy of the solution. This work implemented the NLTV combined with reweighted L1-min. by Split Bregman Iterative method. For evaluation, a noisy digital phantom and a pelvic CT images are employed to compare the quality of images reconstructed by TV, NLTV and reweighted NLTV. Results: In both cases, conventional and reweighted NLTV outperform TV min. in signal-to-noise ratio (SNR) and root-mean squared errors of the reconstructed images. Relative to conventional NLTV, NLTV with reweighted L1-norm was able to slightly improve SNR, while greatly increasing the contrast between tissues due to additional iterative reweighting process. Conclusion: NLTV min. can provide more precise compressed sensing based CT image reconstruction by incorporating the reweighted L1-norm, while maintaining greater robustness to the noise effect than TV min.« less

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

NASA Astrophysics Data System (ADS)

Benson, T. M.; Gregor, J.

2006-09-01

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.

DART: a practical reconstruction algorithm for discrete tomography.

PubMed

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.

4D Cone-beam CT reconstruction using a motion model based on principal component analysis

PubMed Central

Staub, David; Docef, Alen; Brock, Robert S.; Vaman, Constantin; Murphy, Martin J.

2011-01-01

Purpose: To provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm. Methods: The algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT. The motion model uses a basis of eigenvectors that are generated via principal component analysis (PCA) of a training set of displacement vector fields (DVFs) that approximate patient motion. The eigenvectors are weighted by a parameterized function of the patient breathing trace recorded during 4DCBCT. The algorithm is demonstrated and tested via numerical simulation. Results: The algorithm is shown to produce accurate reconstruction results for the most complicated simulated motion, in which voxels move with a pseudo-periodic pattern and relative phase shifts exist between voxels. The tests show that principal component eigenvectors trained on DVFs from a novel 2D/3D registration method give substantially better results than eigenvectors trained on DVFs obtained by conventionally registering 4DCBCT phases reconstructed via filtered backprojection. Conclusions: Proof of concept testing has validated the 4DCBCT reconstruction approach for the types of simulated data considered. In addition, the authors found the 2D/3D registration approach to be our best choice for generating the DVF training set, and the Nelder-Mead simplex algorithm the most robust optimization routine. PMID:22149852

Advanced CT acquisition protocol with a third-generation dual-source CT scanner and iterative reconstruction technique for comprehensive prosthetic heart valve assessment.

PubMed

Faure, Marguerite E; Swart, Laurens E; Dijkshoorn, Marcel L; Bekkers, Jos A; van Straten, Marcel; Nieman, Koen; Parizel, Paul M; Krestin, Gabriel P; Budde, Ricardo P J

2018-05-01

Multidetector CT (MDCT) is a valuable tool for functional prosthetic heart valve (PHV) assessment. However, radiation exposure remains a concern. We assessed a novel CT-acquisition protocol for comprehensive PHV evaluation at limited dose. Patients with a PHV were scanned using a third-generation dual-source CT scanner (DSCT) and iterative reconstruction technique (IR). Three acquisitions were obtained: a non-enhanced scan; a contrast-enhanced, ECG-triggered, arterial CT angiography (CTA) scan with reconstructions at each 5 % of the R-R interval; and a delayed high-pitch CTA of the entire chest. Image quality was scored on a five-point scale. Radiation dose was obtained from the reported CT dose index (CTDI) and dose length product (DLP). We analysed 43 CT examinations. Mean image quality score was 4.1±1.4, 4.7±0.5 and 4.2±0.6 for the non-contrast-enhanced, arterial and delayed acquisitions, respectively, with a total mean image quality of 4.3±0.7. Mean image quality for leaflet motion was 3.9±1.4. Mean DLP was 28.2±17.1, 457.3±168.6 and 68.5±47.2 mGy.cm for the non-contrast-enhanced (n=40), arterial (n=43) and delayed acquisition (n=43), respectively. The mean total DLP was 569±208 mGy.cm and mean total radiation dose was 8.3±3.0 mSv (n=43). Comprehensive assessment of PHVs is possible using DSCT and IR at moderate radiation dose. • Prosthetic heart valve dysfunction is a potentially life-threatening condition. • Dual-source CT can adequately assess valve leaflet motion and anatomy. • We assessed a comprehensive protocol with three acquisitions for PHV evaluation. • This protocol is associated with good image quality and limited dose.

SU-E-I-04: Improving CT Quality for Radiation Therapy of Patients with High Body Mass Index Using Iterative Reconstruction Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noid, G; Tai, A; Li, X

2015-06-15

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. The CT IQ for patients with a high Body Mass Index (BMI) can suffer from increased noise due to photon starvation. The purpose of this study is to investigate and to quantify the IQ enhancement for high BMI patients through the application of IR algorithms. Methods: CT raw data collected for 6 radiotherapy (RT) patients with BMI, greater than or equal to 30 were retrospectively analyzed. All CT data were acquired using a CT scanner (Somaton Definition ASmore » Open, Siemens) installed in a linac room (CT-on-rails) using standard imaging protocols. The CT data were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared and correlated with patient depth and BMI. The patient depth was defined as the largest distance from anterior to posterior along the bilateral symmetry axis. Results: IR techniques are demonstrated to preserve contrast and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is roughly doubled by adopting the highest SAFIRE strength. A significant correlation was observed between patient depth and IR noise reduction through Pearson’s correlation test (R = 0.9429/P = 0.0167). The mean patient depth was 30.4 cm and the average relative noise reduction for the strongest iterative reconstruction was 55%. Conclusion: The IR techniques produce a measureable enhancement to CT IQ by reducing the noise. Dramatic noise reduction is evident for the high BMI patients. The improved CT IQ enables more accurate delineation of tumors and organs at risk and more accuarte dose calculations for RT planning and delivery guidance. Supported by Siemens.« less

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, S; Zhang, Y; Ma, J

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinctmore » from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.« less

Comparing performance of many-core CPUs and GPUs for static and motion compensated reconstruction of C-arm CT data.

PubMed

Hofmann, Hannes G; Keck, Benjamin; Rohkohl, Christopher; Hornegger, Joachim

2011-01-01

Interventional reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. Hardware optimization is not an option but mandatory for interventional image processing and, in particular, for image reconstruction due to the high demands on performance. Several groups have published fast analytical 3-D reconstruction on highly parallel hardware such as GPUs to mitigate this issue. The authors show that the performance of modern CPU-based systems is in the same order as current GPUs for static 3-D reconstruction and outperforms them for a recent motion compensated (3-D+time) image reconstruction algorithm. This work investigates two algorithms: Static 3-D reconstruction as well as a recent motion compensated algorithm. The evaluation was performed using a standardized reconstruction benchmark, RABBITCT, to get comparable results and two additional clinical data sets. The authors demonstrate for a parametric B-spline motion estimation scheme that the derivative computation, which requires many write operations to memory, performs poorly on the GPU and can highly benefit from modern CPU architectures with large caches. Moreover, on a 32-core Intel Xeon server system, the authors achieve linear scaling with the number of cores used and reconstruction times almost in the same range as current GPUs. Algorithmic innovations in the field of motion compensated image reconstruction may lead to a shift back to CPUs in the future. For analytical 3-D reconstruction, the authors show that the gap between GPUs and CPUs became smaller. It can be performed in less than 20 s (on-the-fly) using a 32-core server.

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values.

PubMed

McMillan, Kyle; Bostani, Maryam; Cagnon, Christopher H; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H; McNitt-Gray, Michael F

2017-08-01

The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose. Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating

Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

PubMed

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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 amore » 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

Reducing the number of reconstructions needed for estimating channelized observer performance

NASA Astrophysics Data System (ADS)

Pineda, Angel R.; Miedema, Hope; Brenner, Melissa; Altaf, Sana

2018-03-01

A challenge for task-based optimization is the time required for each reconstructed image in applications where reconstructions are time consuming. Our goal is to reduce the number of reconstructions needed to estimate the area under the receiver operating characteristic curve (AUC) of the infinitely-trained optimal channelized linear observer. We explore the use of classifiers which either do not invert the channel covariance matrix or do feature selection. We also study the assumption that multiple low contrast signals in the same image of a non-linear reconstruction do not significantly change the estimate of the AUC. We compared the AUC of several classifiers (Hotelling, logistic regression, logistic regression using Firth bias reduction and the least absolute shrinkage and selection operator (LASSO)) with a small number of observations both for normal simulated data and images from a total variation reconstruction in magnetic resonance imaging (MRI). We used 10 Laguerre-Gauss channels and the Mann-Whitney estimator for AUC. For this data, our results show that at small sample sizes feature selection using the LASSO technique can decrease bias of the AUC estimation with increased variance and that for large sample sizes the difference between these classifiers is small. We also compared the use of multiple signals in a single reconstructed image to reduce the number of reconstructions in a total variation reconstruction for accelerated imaging in MRI. We found that AUC estimation using multiple low contrast signals in the same image resulted in similar AUC estimates as doing a single reconstruction per signal leading to a 13x reduction in the number of reconstructions needed.

Performance Characteristics of a New LSO PET/CT Scanner With Extended Axial Field-of-View and PSF Reconstruction

NASA Astrophysics Data System (ADS)

Jakoby, Bjoern W.; Bercier, Yanic; Watson, Charles C.; Bendriem, Bernard; Townsend, David W.

2009-06-01

A new combined lutetium oxyorthosilicate (LSO) PET/CT scanner with an extended axial field-of-view (FOV) of 21.8 cm has been developed (Biograph TruePoint PET/CT with TrueV; Siemens Molecular Imaging) and introduced into clinical practice. The scanner includes the recently announced point spread function (PSF) reconstruction algorithm. The PET components incorporate four rings of 48 detector blocks, 5.4 cm times 5.4 cm in cross-section. Each block comprises a 13 times 13 matrix of 4 times 4 times 20 mm3 elements. Data are acquired with a 4.5 ns coincidence time window and an energy window of 425-650 keV. The physical performance of the new scanner has been evaluated according to the recently revised National Electrical Manufacturers Association (NEMA) NU 2-2007 standard and the results have been compared with a previous PET/CT design that incorporates three rings of block detectors with an axial coverage of 16.2 cm (Biograph TruePoint PET/CT; Siemens Molecular Imaging). In addition to the phantom measurements, patient Noise Equivalent Count Rates (NECRs) have been estimated for a range of patients with different body weights (42-154 kg). The average spatial resolution is the same for both scanners: 4.4 mm (FWHM) and 5.0 mm (FWHM) at 1 cm and 10 cm respectively from the center of the transverse FOV. The scatter fractions of the Biograph TruePoint and Biograph TruePoint TrueV are comparable at 32%. Compared to the three ring design, the system sensitivity and peak NECR with smoothed randoms correction (1R) increase by 82% and 73%, respectively. The increase in sensitivity from the extended axial coverage of the Biograph TruePoint PET/CT with TrueV should allow a decrease in either scan time or injected dose without compromising diagnostic image quality. The contrast improvement with the PSF reconstruction potentially offers enhanced detectability for small lesions.

Comparison of extended field-of-view reconstructions in C-arm flat-detector CT using patient size, shape or attenuation information.

PubMed

Kolditz, Daniel; Meyer, Michael; Kyriakou, Yiannis; Kalender, Willi A

2011-01-07

In C-arm-based flat-detector computed tomography (FDCT) it frequently happens that the patient exceeds the scan field of view (SFOV) in the transaxial direction because of the limited detector size. This results in data truncation and CT image artefacts. In this work three truncation correction approaches for extended field-of-view (EFOV) reconstructions have been implemented and evaluated. An FDCT-based method estimates the patient size and shape from the truncated projections by fitting an elliptical model to the raw data in order to apply an extrapolation. In a camera-based approach the patient is sampled with an optical tracking system and this information is used to apply an extrapolation. In a CT-based method the projections are completed by artificial projection data obtained from the CT data acquired in an earlier exam. For all methods the extended projections are filtered and backprojected with a standard Feldkamp-type algorithm. Quantitative evaluations have been performed by simulations of voxelized phantoms on the basis of the root mean square deviation and a quality factor Q (Q = 1 represents the ideal correction). Measurements with a C-arm FDCT system have been used to validate the simulations and to investigate the practical applicability using anthropomorphic phantoms which caused truncation in all projections. The proposed approaches enlarged the FOV to cover wider patient cross-sections. Thus, image quality inside and outside the SFOV has been improved. Best results have been obtained using the CT-based method, followed by the camera-based and the FDCT-based truncation correction. For simulations, quality factors up to 0.98 have been achieved. Truncation-induced cupping artefacts have been reduced, e.g., from 218% to less than 1% for the measurements. The proposed truncation correction approaches for EFOV reconstructions are an effective way to ensure accurate CT values inside the SFOV and to recover peripheral information outside the SFOV.

Optimization of hybrid iterative reconstruction level in pediatric body CT.

PubMed

Karmazyn, Boaz; Liang, Yun; Ai, Huisi; Eckert, George J; Cohen, Mervyn D; Wanner, Matthew R; Jennings, S Gregory

2014-02-01

The objective of our study was to attempt to optimize the level of hybrid iterative reconstruction (HIR) in pediatric body CT. One hundred consecutive chest or abdominal CT examinations were selected. For each examination, six series were obtained: one filtered back projection (FBP) and five HIR series (iDose(4)) levels 2-6. Two pediatric radiologists, blinded to noise measurements, independently chose the optimal HIR level and then rated series quality. We measured CT number (mean in Hounsfield units) and noise (SD in Hounsfield units) changes by placing regions of interest in the liver, muscles, subcutaneous fat, and aorta. A mixed-model analysis-of-variance test was used to analyze correlation of noise reduction with the optimal HIR level compared with baseline FBP noise. One hundred CT examinations were performed of 88 patients (52 females and 36 males) with a mean age of 8.5 years (range, 19 days-18 years); 12 patients had both chest and abdominal CT studies. Radiologists agreed to within one level of HIR in 92 of 100 studies. The mean quality rating was significantly higher for HIR than FBP (3.6 vs 3.3, respectively; p < 0.01). HIR caused minimal (0-0.2%) change in CT numbers. Noise reduction varied among structures and patients. Liver noise reduction positively correlated with baseline noise when the optimal HIR level was used (p < 0.01). HIR levels were significantly correlated with body weight and effective diameter of the upper abdomen (p < 0.01). HIR, such as iDose(4), improves the quality of body CT scans of pediatric patients by decreasing noise; HIR level 3 or 4 is optimal for most studies. The optimal HIR level was less effective in reducing liver noise in children with lower baseline noise.

A comparison of linear interpolation models for iterative CT reconstruction.

PubMed

Hahn, Katharina; Schöndube, Harald; Stierstorfer, Karl; Hornegger, Joachim; Noo, Frédéric

2016-12-01

Recent reports indicate that model-based iterative reconstruction methods may improve image quality in computed tomography (CT). One difficulty with these methods is the number of options available to implement them, including the selection of the forward projection model and the penalty term. Currently, the literature is fairly scarce in terms of guidance regarding this selection step, whereas these options impact image quality. Here, the authors investigate the merits of three forward projection models that rely on linear interpolation: the distance-driven method, Joseph's method, and the bilinear method. The authors' selection is motivated by three factors: (1) in CT, linear interpolation is often seen as a suitable trade-off between discretization errors and computational cost, (2) the first two methods are popular with manufacturers, and (3) the third method enables assessing the importance of a key assumption in the other methods. One approach to evaluate forward projection models is to inspect their effect on discretized images, as well as the effect of their transpose on data sets, but significance of such studies is unclear since the matrix and its transpose are always jointly used in iterative reconstruction. Another approach is to investigate the models in the context they are used, i.e., together with statistical weights and a penalty term. Unfortunately, this approach requires the selection of a preferred objective function and does not provide clear information on features that are intrinsic to the model. The authors adopted the following two-stage methodology. First, the authors analyze images that progressively include components of the singular value decomposition of the model in a reconstructed image without statistical weights and penalty term. Next, the authors examine the impact of weights and penalty on observed differences. Image quality metrics were investigated for 16 different fan-beam imaging scenarios that enabled probing various aspects

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

NASA Astrophysics Data System (ADS)

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.

A resource for the assessment of lung nodule size estimation methods: database of thoracic CT scans of an anthropomorphic phantom◊

PubMed Central

Gavrielides, Marios A.; Kinnard, Lisa M.; Myers, Kyle J.; Peregoy, Jennifer; Pritchard, William F.; Zeng, Rongping; Esparza, Juan; Karanian, John; Petrick, Nicholas

2010-01-01

A number of interrelated factors can affect the precision and accuracy of lung nodule size estimation. To quantify the effect of these factors, we have been conducting phantom CT studies using an anthropomorphic thoracic phantom containing a vasculature insert to which synthetic nodules were inserted or attached. Ten repeat scans were acquired on different multi-detector scanners, using several sets of acquisition and reconstruction protocols and various nodule characteristics (size, shape, density, location). This study design enables both bias and variance analysis for the nodule size estimation task. The resulting database is in the process of becoming publicly available as a resource to facilitate the assessment of lung nodule size estimation methodologies and to enable comparisons between different methods regarding measurement error. This resource complements public databases of clinical data and will contribute towards the development of procedures that will maximize the utility of CT imaging for lung cancer screening and tumor therapy evaluation. PMID:20640011

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ke; Tang, Jie; Chen, Guang-Hong, E-mail: gchen7@wisc.edu

Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD,more » GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial

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

PubMed

Noël, Peter B; Renger, Bernhard; Fiebich, Martin; Münzel, Daniela; Fingerle, Alexander A; Rummeny, Ernst J; Dobritz, Martin

2013-01-01

Evaluation of 15,000 computed tomography (CT) examinations to investigate if iterative reconstruction (IR) reduces sustainably radiation exposure. 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. 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). The dose aspect remains a priority in CT research. Iterative reconstruction algorithms reduce sustainably and significantly radiation dose in the clinical routine. Our results illustrate that not only in studies with a limited

MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Q; Stanford University School of Medicine, Stanford, CA; Liu, H

Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channelmore » and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low

Comparison of computational to human observer detection for evaluation of CT low dose iterative reconstruction

NASA Astrophysics Data System (ADS)

Eck, Brendan; Fahmi, Rachid; Brown, Kevin M.; Raihani, Nilgoun; Wilson, David L.

2014-03-01

Model observers were created and compared to human observers for the detection of low contrast targets in computed tomography (CT) images reconstructed with an advanced, knowledge-based, iterative image reconstruction method for low x-ray dose imaging. A 5-channel Laguerre-Gauss Hotelling Observer (CHO) was used with internal noise added to the decision variable (DV) and/or channel outputs (CO). Models were defined by parameters: (k1) DV-noise with standard deviation (std) proportional to DV std; (k2) DV-noise with constant std; (k3) CO-noise with constant std across channels; and (k4) CO-noise in each channel with std proportional to CO variance. Four-alternative forced choice (4AFC) human observer studies were performed on sub-images extracted from phantom images with and without a "pin" target. Model parameters were estimated using maximum likelihood comparison to human probability correct (PC) data. PC in human and all model observers increased with dose, contrast, and size, and was much higher for advanced iterative reconstruction (IMR) as compared to filtered back projection (FBP). Detection in IMR was better than FPB at 1/3 dose, suggesting significant dose savings. Model(k1,k2,k3,k4) gave the best overall fit to humans across independent variables (dose, size, contrast, and reconstruction) at fixed display window. However Model(k1) performed better when considering model complexity using the Akaike information criterion. Model(k1) fit the extraordinary detectability difference between IMR and FBP, despite the different noise quality. It is anticipated that the model observer will predict results from iterative reconstruction methods having similar noise characteristics, enabling rapid comparison of methods.

Quantitative CT: technique dependence of volume estimation on pulmonary nodules

NASA Astrophysics Data System (ADS)

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Colsher, James; Amurao, Maxwell; Samei, Ehsan

2012-03-01

Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.

The Effects of Metal on Size Specific Dose Estimation (SSDE) in CT: A Phantom Study

NASA Astrophysics Data System (ADS)

Alsanea, Maram M.

Over the past number of years there has been a significant increase in the awareness of radiation dose from use of computed tomography (CT). Efforts have been made to reduce radiation dose from CT and to better quantify dose being delivered. However, unfortunately, these dose metrics such as CTDI vol are not a specific patient dose. In 2011, the size-specific dose estimation (SSDE) was introduced by AAPM TG-204 which accounts for the physical size of the patient. However, the approach presented in TG-204 ignores the importance of the attenuation differences in the body. In 2014, a newer methodology that accounted for tissue attenuation was introduced by the AAPM TG-220 based on the concept of water equivalent diameter, Dw. One of the limitation of TG-220 is that there is no estimation of the dose while highly attenuating objects such as metal is present in the body. The purpose of this research is to evaluate the accuracy of size-specific dose estimates in CT in the presence of simulated metal prostheses using a conventional PMMA CTDI phantom at different phantom diameter (body and head) and beam energy. Titanium, Cobalt- chromium and stainless steel alloys rods were used in the study. Two approaches were used as introduced by AAPM TG-204 and 220 utilizing the effective diameter and the Dw calculations. From these calculations, conversion factors have been derived that could be applied to the measured CTDIvol to convert it to specific patient dose, or size specific dose estimate, (SSDE). Radiation dose in tissue (f-factor = 0.94) was measured at various chamber positions with the presence of metal. Following, an average weighted tissue dose (AWTD) was calculated in a manner similar to the weighted CTDI (CTDIw). In general, for the 32 cm body phantom SSDE220 provided more accurate estimates of AWTD than did SSDE204. For smaller patient size, represented by the 16 cm head phantom, the SSDE204 was a more accurate estimate of AWTD that that of SSDE220. However, as the

Reducing Radiation Dose in Adult Head CT using Iterative Reconstruction - A Clinical Study in 177 Patients.

PubMed

Kaul, D; Kahn, J; Huizing, L; Wiener, E; Grupp, U; Böning, G; Ghadjar, P; Renz, D M; Streitparth, F

2016-02-01

To assess how ASIR (adaptive statistical iterative reconstruction) contributes to dose reduction and affects image quality of non-contrast cranial computed tomography (cCT). Non-contrast emergency CT scans of the head acquired in 177 patients were evaluated. The scans were acquired and processed using four different protocols: Group A (control): 120 kV, FBP (filtered back projection) n = 71; group B1: 120 kV, scan and reconstruction performed with 20 % ASIR (blending of 20 % ASIR and 80 % FBP), n = 86; group B2: raw data from group B1 reconstructed using a blending of 40 % ASIR and 60 % FBP, n = 74; group C1: 120 kV, scan and reconstruction performed with 30 % ASIR, n = 20; group C2: raw data from group C1 reconstructed using a blending of 50 % ASIR and 50 % FBP, n = 20. The effective dose was calculated. Image quality was assessed quantitatively and qualitatively. Compared to group A, groups B1/2 and C1/2 showed a significantly reduced effective dose of 40.4 % and 73.3 % (p < 0.0001), respectively. Group B1 and group C1/2 also showed significantly reduced quantitative and qualitative image quality parameters. In group B2, quantitative measures were comparable to group A, and qualitative scores were lower compared to group A but higher compared to group B1. Diagnostic confidence grading showed groups B1/2 to be adequate for everyday clinical practice. Group C2 was considered acceptable for follow-up imaging of severe acute events such as bleeding or subacute stroke. Use of ASIR makes it possible to reduce radiation significantly while maintaining adequate image quality in non-contrast head CT, which may be particularly useful for younger patients in an emergency setting and in follow-up. ASIR may reduce radiation significantly while maintaining adequate image quality. cCT protocol with 20 % ASIR and 40 %ASIR/60 %FBP blending is adequate for everyday clinical use. cCT protocol with 30 % ASIR and 50�

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

NASA Astrophysics Data System (ADS)

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 model for filtered backprojection reconstruction artifacts due to time-varying attenuation values in perfusion C-arm CT.

PubMed

Fieselmann, Andreas; Dennerlein, Frank; Deuerling-Zheng, Yu; Boese, Jan; Fahrig, Rebecca; Hornegger, Joachim

2011-06-21

Filtered backprojection is the basis for many CT reconstruction tasks. It assumes constant attenuation values of the object during the acquisition of the projection data. Reconstruction artifacts can arise if this assumption is violated. For example, contrast flow in perfusion imaging with C-arm CT systems, which have acquisition times of several seconds per C-arm rotation, can cause this violation. In this paper, we derived and validated a novel spatio-temporal model to describe these kinds of artifacts. The model separates the temporal dynamics due to contrast flow from the scan and reconstruction parameters. We introduced derivative-weighted point spread functions to describe the spatial spread of the artifacts. The model allows prediction of reconstruction artifacts for given temporal dynamics of the attenuation values. Furthermore, it can be used to systematically investigate the influence of different reconstruction parameters on the artifacts. We have shown that with optimized redundancy weighting function parameters the spatial spread of the artifacts around a typical arterial vessel can be reduced by about 70%. Finally, an inversion of our model could be used as the basis for novel dynamic reconstruction algorithms that further minimize these artifacts.

Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registration.

PubMed

Wolthaus, J W H; Sonke, J J; van Herk, M; Damen, E M F

2008-09-01

.g., tumor and diaphragm). The shape of the tumor, with respect to that of the BH CT scan, was better represented by the MidP reconstructions than any of the 4D CT frames (including MidV; reduction of "shape differences" was 66%). The MidP scans contained about one-third the noise of individual 4D CT scan frames. We implemented an accurate method to estimate the motion of structures in a 4D CT scan. Subsequently, a novel method to create a midposition CT scan (time-weighted average of the anatomy) for treatment planning with reduced noise and artifacts was introduced. Tumor shape and position in the MidP CT scan represents that of the BH CT scan better than MidV CT scan and, therefore, was found to be appropriate for treatment planning.

Y-90 SPECT ML image reconstruction with a new model for tissue-dependent bremsstrahlung production using CT information: a proof-of-concept study

NASA Astrophysics Data System (ADS)

Lim, Hongki; Fessler, Jeffrey A.; Wilderman, Scott J.; Brooks, Allen F.; Dewaraja, Yuni K.

2018-06-01

While the yield of positrons used in Y-90 PET is independent of tissue media, Y-90 SPECT imaging is complicated by the tissue dependence of bremsstrahlung photon generation. The probability of bremsstrahlung production is proportional to the square of the atomic number of the medium. Hence, the same amount of activity in different tissue regions of the body will produce different numbers of bremsstrahlung photons. Existing reconstruction methods disregard this tissue-dependency, potentially impacting both qualitative and quantitative imaging of heterogeneous regions of the body such as bone with marrow cavities. In this proof-of-concept study, we propose a new maximum-likelihood method that incorporates bremsstrahlung generation probabilities into the system matrix, enabling images of the desired Y-90 distribution to be reconstructed instead of the ‘bremsstrahlung distribution’ that is obtained with existing methods. The tissue-dependent probabilities are generated by Monte Carlo simulation while bone volume fractions for each SPECT voxel are obtained from co-registered CT. First, we demonstrate the tissue dependency in a SPECT/CT imaging experiment with Y-90 in bone equivalent solution and water. Visually, the proposed reconstruction approach better matched the true image and the Y-90 PET image than the standard bremsstrahlung reconstruction approach. An XCAT phantom simulation including bone and marrow regions also demonstrated better agreement with the true image using the proposed reconstruction method. Quantitatively, compared with the standard reconstruction, the new method improved estimation of the liquid bone:water activity concentration ratio by 40% in the SPECT measurement and the cortical bone:marrow activity concentration ratio by 58% in the XCAT simulation.

An angle-dependent estimation of CT x-ray spectrum from rotational transmission measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Yuan, E-mail: yuan.lin@duke.edu; Samei, Ehsan; Ramirez-Giraldo, Juan Carlos

2014-06-15

Purpose: Computed tomography (CT) performance as well as dose and image quality is directly affected by the x-ray spectrum. However, the current assessment approaches of the CT x-ray spectrum require costly measurement equipment and complicated operational procedures, and are often limited to the spectrum corresponding to the center of rotation. In order to address these limitations, the authors propose an angle-dependent estimation technique, where the incident spectra across a wide range of angular trajectories can be estimated accurately with only a single phantom and a single axial scan in the absence of the knowledge of the bowtie filter. Methods: Themore » proposed technique uses a uniform cylindrical phantom, made of ultra-high-molecular-weight polyethylene and positioned in an off-centered geometry. The projection data acquired with an axial scan have a twofold purpose. First, they serve as a reflection of the transmission measurements across different angular trajectories. Second, they are used to reconstruct the cross sectional image of the phantom, which is then utilized to compute the intersection length of each transmission measurement. With each CT detector element recording a range of transmission measurements for a single angular trajectory, the spectrum is estimated for that trajectory. A data conditioning procedure is used to combine information from hundreds of collected transmission measurements to accelerate the estimation speed, to reduce noise, and to improve estimation stability. The proposed spectral estimation technique was validated experimentally using a clinical scanner (Somatom Definition Flash, Siemens Healthcare, Germany) with spectra provided by the manufacturer serving as the comparison standard. Results obtained with the proposed technique were compared against those obtained from a second conventional transmission measurement technique with two materials (i.e., Cu and Al). After validation, the proposed technique was applied to

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method.

PubMed

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-05-16

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

PubMed Central

Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Soleimani, Manuchehr; Mueller-Lisse, Ullrich; Moeller, Knut

2016-01-01

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications. PMID:27181695

WE-AB-204-09: Respiratory Motion Correction in 4D-PET by Simultaneous Motion Estimation and Image Reconstruction (SMEIR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kalantari, F; Wang, J; Li, T

2015-06-15

Purpose: In conventional 4D-PET, images from different frames are reconstructed individually and aligned by registration methods. Two issues with these approaches are: 1) Reconstruction algorithms do not make full use of all projections statistics; and 2) Image registration between noisy images can Result in poor alignment. In this study we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) method for cone beam CT for motion estimation/correction in 4D-PET. Methods: Modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM- TV) is used to obtain a primary motion-compensated PET (pmc-PET) from all projection data using Demons derivedmore » deformation vector fields (DVFs) as initial. Motion model update is done to obtain an optimal set of DVFs between the pmc-PET and other phases by matching the forward projection of the deformed pmc-PET and measured projections of other phases. Using updated DVFs, OSEM- TV image reconstruction is repeated and new DVFs are estimated based on updated images. 4D XCAT phantom with typical FDG biodistribution and a 10mm diameter tumor was used to evaluate the performance of the SMEIR algorithm. Results: Image quality of 4D-PET is greatly improved by the SMEIR algorithm. When all projections are used to reconstruct a 3D-PET, motion blurring artifacts are present, leading to a more than 5 times overestimation of the tumor size and 54% tumor to lung contrast ratio underestimation. This error reduced to 37% and 20% for post reconstruction registration methods and SMEIR respectively. Conclusion: SMEIR method can be used for motion estimation/correction in 4D-PET. The statistics is greatly improved since all projection data are combined together to update the image. The performance of the SMEIR algorithm for 4D-PET is sensitive to smoothness control parameters in the DVF estimation step.« less

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

PubMed

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

Estimating Radiation Dose Metrics for Patients Undergoing Tube Current Modulation CT Scans

NASA Astrophysics Data System (ADS)

McMillan, Kyle Lorin

Computed tomography (CT) has long been a powerful tool in the diagnosis of disease, identification of tumors and guidance of interventional procedures. With CT examinations comes the concern of radiation exposure and the associated risks. In order to properly understand those risks on a patient-specific level, organ dose must be quantified for each CT scan. Some of the most widely used organ dose estimates are derived from fixed tube current (FTC) scans of a standard sized idealized patient model. However, in current clinical practice, patient size varies from neonates weighing just a few kg to morbidly obese patients weighing over 200 kg, and nearly all CT exams are performed with tube current modulation (TCM), a scanning technique that adjusts scanner output according to changes in patient attenuation. Methods to account for TCM in CT organ dose estimates have been previously demonstrated, but these methods are limited in scope and/or restricted to idealized TCM profiles that are not based on physical observations and not scanner specific (e.g. don't account for tube limits, scanner-specific effects, etc.). The goal of this work was to develop methods to estimate organ doses to patients undergoing CT scans that take into account both the patient size as well as the effects of TCM. This work started with the development and validation of methods to estimate scanner-specific TCM schemes for any voxelized patient model. An approach was developed to generate estimated TCM schemes that match actual TCM schemes that would have been acquired on the scanner for any patient model. Using this approach, TCM schemes were then generated for a variety of body CT protocols for a set of reference voxelized phantoms for which TCM information does not currently exist. These are whole body patient models representing a variety of sizes, ages and genders that have all radiosensitive organs identified. TCM schemes for these models facilitated Monte Carlo-based estimates of fully

Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia.

PubMed

Sun, Jihang; Yu, Tong; Liu, Jinrong; Duan, Xiaomin; Hu, Di; Liu, Yong; Peng, Yun

2017-03-16

Model-based iterative reconstruction (MBIR) is a promising reconstruction method which could improve CT image quality with low radiation dose. The purpose of this study was to demonstrate the advantage of using MBIR for noise reduction and image quality improvement in low dose chest CT for children with necrotizing pneumonia, over the adaptive statistical iterative reconstruction (ASIR) and conventional filtered back-projection (FBP) technique. Twenty-six children with necrotizing pneumonia (aged 2 months to 11 years) who underwent standard of care low dose CT scans were included. Thinner-slice (0.625 mm) images were retrospectively reconstructed using MBIR, ASIR and conventional FBP techniques. Image noise and signal-to-noise ratio (SNR) for these thin-slice images were measured and statistically analyzed using ANOVA. Two radiologists independently analyzed the image quality for detecting necrotic lesions, and results were compared using a Friedman's test. Radiation dose for the overall patient population was 0.59 mSv. There was a significant improvement in the high-density and low-contrast resolution of the MBIR reconstruction resulting in more detection and better identification of necrotic lesions (38 lesions in 0.625 mm MBIR images vs. 29 lesions in 0.625 mm FBP images). The subjective display scores (mean ± standard deviation) for the detection of necrotic lesions were 5.0 ± 0.0, 2.8 ± 0.4 and 2.5 ± 0.5 with MBIR, ASIR and FBP reconstruction, respectively, and the respective objective image noise was 13.9 ± 4.0HU, 24.9 ± 6.6HU and 33.8 ± 8.7HU. The image noise decreased by 58.9 and 26.3% in MBIR images as compared to FBP and ASIR images. Additionally, the SNR of MBIR images was significantly higher than FBP images and ASIR images. The quality of chest CT images obtained by MBIR in children with necrotizing pneumonia was significantly improved by the MBIR technique as compared to the ASIR and FBP reconstruction, to

Improved quantitation and reproducibility in multi-PET/CT lung studies by combining CT information.

PubMed

Holman, Beverley F; Cuplov, Vesna; Millner, Lynn; Endozo, Raymond; Maher, Toby M; Groves, Ashley M; Hutton, Brian F; Thielemans, Kris

2018-06-05

Matched attenuation maps are vital for obtaining accurate and reproducible kinetic and static parameter estimates from PET data. With increased interest in PET/CT imaging of diffuse lung diseases for assessing disease progression and treatment effectiveness, understanding the extent of the effect of respiratory motion and establishing methods for correction are becoming more important. In a previous study, we have shown that using the wrong attenuation map leads to large errors due to density mismatches in the lung, especially in dynamic PET scans. Here, we extend this work to the case where the study is sub-divided into several scans, e.g. for patient comfort, each with its own CT (cine-CT and 'snap shot' CT). A method to combine multi-CT information into a combined-CT has then been developed, which averages the CT information from each study section to produce composite CT images with the lung density more representative of that in the PET data. This combined-CT was applied to nine patients with idiopathic pulmonary fibrosis, imaged with dynamic 18 F-FDG PET/CT to determine the improvement in the precision of the parameter estimates. Using XCAT simulations, errors in the influx rate constant were found to be as high as 60% in multi-PET/CT studies. Analysis of patient data identified displacements between study sections in the time activity curves, which led to an average standard error in the estimates of the influx rate constant of 53% with conventional methods. This reduced to within 5% after use of combined-CTs for attenuation correction of the study sections. Use of combined-CTs to reconstruct the sections of a multi-PET/CT study, as opposed to using the individually acquired CTs at each study stage, produces more precise parameter estimates and may improve discrimination between diseased and normal lung.

Correlation between differential renal function estimation using CT-based functional renal parenchymal volume and (99m)Tc - DTPA renal scan.

PubMed

Sarma, Debanga; Barua, Sasanka K; Rajeev, T P; Baruah, Saumar J

2012-10-01

Nuclear renal scan is currently the gold standard imaging study to determine differential renal function. We propose helical CT as single modality for both the anatomical and functional evaluation of kidney with impaired function. In the present study renal parenchymal volume is measured and percent total renal volume is used as a surrogate marker for differential renal function. The objective of this study is to correlate between differential renal function estimation using CT-based renal parenchymal volume measurement with differential renal function estimation using (99m)TC - DTPA renal scan. Twenty-one patients with unilateral obstructive uropathy were enrolled in this prospective comparative study. They were subjected to (99m)Tc - DTPA renal scan and 64 slice helical CT scan which estimates the renal volume depending on the reconstruction of arterial phase images followed by volume rendering and percent renal volume was calculated. Percent renal volume was correlated with percent renal function, as determined by nuclear renal scan using Pearson coefficient. RESULTS AND OBSERVATION: A strong correlation is observed between percent renal volume and percent renal function in obstructed units (r = 0.828, P < 0.001) as well as in nonobstructed units (r = 0.827, P < 0.001). There is a strong correlation between percent renal volume determined by CT scan and percent renal function determined by (99m)TC - DTPA renal scan both in obstructed and in normal units. CT-based percent renal volume can be used as a single radiological tests for both functional and anatomical assessment of impaired renal units.

1975 Memorial Award Paper. Image generation and display techniques for CT scan data. Thin transverse and reconstructed coronal and sagittal planes.

PubMed

Glenn, W V; Johnston, R J; Morton, P E; Dwyer, S J

1975-01-01

The various limitations to computerized axial tomographic (CT) interpretation are due in part to the 8-13 mm standard tissue plane thickness and in part to the absence of alternative planes of view, such as coronal or sagittal images. This paper describes a method for gathering multiple overlapped 8 mm transverse sections, subjecting these data to a deconvolution process, and then displaying thin (1 mm) transverse as well as reconstructed coronal and sagittal CT images. Verification of the deconvolution technique with phantom experiments is described. Application of the phantom results to human post mortem CT scan data illustrates this method's faithful reconstruction of coronal and sagittal tissue densities when correlated with actual specimen photographs of a sectioned brain. A special CT procedure, limited basal overlap scanning, is proposed for use on current first generation CT scanners without hardware modification.

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

PubMed

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maier, Joscha, E-mail: joscha.maier@dkfz.de; Sawall, Stefan; Kachelrieß, Marc

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 levelsmore » 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

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

NASA Astrophysics Data System (ADS)

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.

SU-F-18C-13: Low-Dose X-Ray CT Reconstruction Using a Hybrid First-Order Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, L; Lin, W; Jin, M

2014-06-15

Purpose: To develop a novel reconstruction method for X-ray CT that can lead to accurate reconstruction at significantly reduced dose levels combining low X-ray incident intensity and few views of projection data. Methods: The noise nature of the projection data at low X-ray incident intensity was modeled and accounted by the weighted least-squares (WLS) criterion. The total variation (TV) penalty was used to mitigate artifacts caused by few views of data. The first order primal-dual (FOPD) algorithm was used to minimize TV in image domain, which avoided the difficulty of the non-smooth objective function. The TV penalized WLS reconstruction wasmore » achieved by alternated FOPD TV minimization and projection onto convex sets (POCS) for data fidelity constraints. The proposed FOPD-POCS method was evaluated using the FORBILD jaw phantom and the real cadaver head CT data. Results: The quantitative measures, root mean square error (RMSE) and contrast-to-noise ratio (CNR), demonstrate the superior denoising capability of WLS over LS-based TV iterative reconstruction. The improvement of RMSE (WLS vs. LS) is 15%∼21% and that of CNR is 17%∼72% when the incident counts per ray are ranged from 1×10{sup 5} to 1×10{sup 3}. In addition, the TV regularization can accurately reconstruct images from about 50 views of the jaw phantom. The FOPD-POCS reconstruction reveals more structural details and suffers fewer artifacts in both the phantom and real head images. The FOPD-POCS method also shows fast convergence at low X-ray incident intensity. Conclusion: The new hybrid FOPD-POCS method, based on TV penalized WLS, yields excellent image quality when the incident X-ray intensity is low and the projection views are limited. The reconstruction is computationally efficient since the FOPD minimization of TV is applied only in the image domain. The characteristics of FOPD-POCS can be exploited to significantly reduce radiation dose of X-ray CT without compromising accuracy for

Acceleration of fluoro-CT reconstruction for a mobile C-Arm on GPU and FPGA hardware: a simulation study

NASA Astrophysics Data System (ADS)

Xue, Xinwei; Cheryauka, Arvi; Tubbs, David

2006-03-01

CT imaging in interventional and minimally-invasive surgery requires high-performance computing solutions that meet operational room demands, healthcare business requirements, and the constraints of a mobile C-arm system. The computational requirements of clinical procedures using CT-like data are increasing rapidly, mainly due to the need for rapid access to medical imagery during critical surgical procedures. The highly parallel nature of Radon transform and CT algorithms enables embedded computing solutions utilizing a parallel processing architecture to realize a significant gain of computational intensity with comparable hardware and program coding/testing expenses. In this paper, using a sample 2D and 3D CT problem, we explore the programming challenges and the potential benefits of embedded computing using commodity hardware components. The accuracy and performance results obtained on three computational platforms: a single CPU, a single GPU, and a solution based on FPGA technology have been analyzed. We have shown that hardware-accelerated CT image reconstruction can be achieved with similar levels of noise and clarity of feature when compared to program execution on a CPU, but gaining a performance increase at one or more orders of magnitude faster. 3D cone-beam or helical CT reconstruction and a variety of volumetric image processing applications will benefit from similar accelerations.

Radiation dose and image quality in pediatric chest CT: effects of iterative reconstruction in normal weight and overweight children.

PubMed

Yoon, Haesung; Kim, Myung-Joon; Yoon, Choon-Sik; Choi, Jiin; Shin, Hyun Joo; Kim, Hyun Gi; Lee, Mi-Jung

2015-03-01

New CT reconstruction techniques may help reduce the burden of ionizing radiation. To quantify radiation dose reduction when performing pediatric chest CT using a low-dose protocol and 50% adaptive statistical iterative reconstruction (ASIR) compared with age/gender-matched chest CT using a conventional dose protocol and reconstructed with filtered back projection (control group) and to determine its effect on image quality in normal weight and overweight children. We retrospectively reviewed 40 pediatric chest CT (M:F = 21:19; range: 0.1-17 years) in both groups. Radiation dose was compared between the two groups using paired Student's t-test. Image quality including noise, sharpness, artifacts and diagnostic acceptability was subjectively assessed by three pediatric radiologists using a four-point scale (superior, average, suboptimal, unacceptable). Eight children in the ASIR group and seven in the control group were overweight. All radiation dose parameters were significantly lower in the ASIR group (P < 0.01) with a greater than 57% dose reduction in overweight children. Image noise was higher in the ASIR group in both normal weight and overweight children. Only one scan in the ASIR group (1/40, 2.5%) was rated as diagnostically suboptimal and there was no unacceptable study. In both normal weight and overweight children, the ASIR technique is associated with a greater than 57% mean dose reduction, without significantly impacting diagnostic image quality in pediatric chest CT examinations. However, CT scans in overweight children may have a greater noise level, even when using the ASIR technique.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noid, G; Chen, G; Tai, A

2014-06-01

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 ASmore » 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.« less

Estimating the lifetime risk of cancer associated with multiple CT scans.

PubMed

Ivanov, V K; Kashcheev, V V; Chekin, S Yu; Menyaylo, A N; Pryakhin, E A; Tsyb, A F; Mettler, F A

2014-12-01

Multiple CT scans are often done on the same patient resulting in an increased risk of cancer. Prior publications have estimated risks on a population basis and often using an effective dose. Simply adding up the risks from single scans does not correctly account for the survival function. A methodology for estimating personal radiation risks attributed to multiple CT imaging using organ doses is presented in this article. The estimated magnitude of the attributable risk fraction for the possible development of radiation-induced cancer indicates the necessity for strong clinical justification when ordering multiple CT scans.

Value of 100 kVp scan with sinogram-affirmed iterative reconstruction algorithm on a single-source CT system during whole-body CT for radiation and contrast medium dose reduction: an intra-individual feasibility study.

PubMed

Nagayama, Y; Nakaura, T; Oda, S; Tsuji, A; Urata, J; Furusawa, M; Tanoue, S; Utsunomiya, D; Yamashita, Y

2018-02-01

To perform an intra-individual investigation of the usefulness of a contrast medium (CM) and radiation dose-reduction protocol using single-source computed tomography (CT) combined with 100 kVp and sinogram-affirmed iterative reconstruction (SAFIRE) for whole-body CT (WBCT; chest-abdomen-pelvis CT) in oncology patients. Forty-three oncology patients who had undergone WBCT under both 120 and 100 kVp protocols at different time points (mean interscan intervals: 98 days) were included retrospectively. The CM doses for the 120 and 100 kVp protocols were 600 and 480 mg iodine/kg, respectively; 120 kVp images were reconstructed with filtered back-projection (FBP), whereas 100 kVp images were reconstructed with FBP (100 kVp-F) and the SAFIRE (100 kVp-S). The size-specific dose estimate (SSDE), iodine load and image quality of each protocol were compared. The SSDE and iodine load of 100 kVp protocol were 34% and 21%, respectively, lower than of 120 kVp protocol (SSDE: 10.6±1.1 versus 16.1±1.8 mGy; iodine load: 24.8±4versus 31.5±5.5 g iodine, p<0.01). Contrast enhancement, objective image noise, contrast-to-noise-ratio, and visual score of 100 kVp-S were similar to or better than of 120 kVp protocol. Compared with the 120 kVp protocol, the combined use of 100 kVp and SAFIRE in WBCT for oncology assessment with an SSCT facilitated substantial reduction in the CM and radiation dose while maintaining image quality. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Does Iterative Reconstruction Lower CT Radiation Dose: Evaluation of 15,000 Examinations

PubMed Central

Noël, Peter B.; Renger, Bernhard; Fiebich, Martin; Münzel, Daniela; Fingerle, Alexander A.; Rummeny, Ernst J.; Dobritz, Martin

2013-01-01

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. Our results

Renal Cyst Pseudoenhancement: Intraindividual Comparison Between Virtual Monochromatic Spectral Images and Conventional Polychromatic 120-kVp Images Obtained During the Same CT Examination and Comparisons Among Images Reconstructed Using Filtered Back Projection, Adaptive Statistical Iterative Reconstruction, and Model-Based Iterative Reconstruction

PubMed Central

Yamada, Yoshitake; Yamada, Minoru; Sugisawa, Koichi; Akita, Hirotaka; Shiomi, Eisuke; Abe, Takayuki; Okuda, Shigeo; Jinzaki, Masahiro

2015-01-01

Abstract The purpose of this study was to compare renal cyst pseudoenhancement between virtual monochromatic spectral (VMS) and conventional polychromatic 120-kVp images obtained during the same abdominal computed tomography (CT) examination and among images reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Our institutional review board approved this prospective study; each participant provided written informed consent. Thirty-one patients (19 men, 12 women; age range, 59–85 years; mean age, 73.2 ± 5.5 years) with renal cysts underwent unenhanced 120-kVp CT followed by sequential fast kVp-switching dual-energy (80/140 kVp) and 120-kVp abdominal enhanced CT in the nephrographic phase over a 10-cm scan length with a random acquisition order and 4.5-second intervals. Fifty-one renal cysts (maximal diameter, 18.0 ± 14.7 mm [range, 4–61 mm]) were identified. The CT attenuation values of the cysts as well as of the kidneys were measured on the unenhanced images, enhanced VMS images (at 70 keV) reconstructed using FBP and ASIR from dual-energy data, and enhanced 120-kVp images reconstructed using FBP, ASIR, and MBIR. The results were analyzed using the mixed-effects model and paired t test with Bonferroni correction. The attenuation increases (pseudoenhancement) of the renal cysts on the VMS images reconstructed using FBP/ASIR (least square mean, 5.0/6.0 Hounsfield units [HU]; 95% confidence interval, 2.6–7.4/3.6–8.4 HU) were significantly lower than those on the conventional 120-kVp images reconstructed using FBP/ASIR/MBIR (least square mean, 12.1/12.8/11.8 HU; 95% confidence interval, 9.8–14.5/10.4–15.1/9.4–14.2 HU) (all P < .001); on the other hand, the CT attenuation values of the kidneys on the VMS images were comparable to those on the 120-kVp images. Regardless of the reconstruction algorithm, 70-keV VMS images showed

Motion compensation for cone-beam CT using Fourier consistency conditions

NASA Astrophysics Data System (ADS)

Berger, M.; Xia, Y.; Aichinger, W.; Mentl, K.; Unberath, M.; Aichert, A.; Riess, C.; Hornegger, J.; Fahrig, R.; Maier, A.

2017-09-01

In cone-beam CT, involuntary patient motion and inaccurate or irreproducible scanner motion substantially degrades image quality. To avoid artifacts this motion needs to be estimated and compensated during image reconstruction. In previous work we showed that Fourier consistency conditions (FCC) can be used in fan-beam CT to estimate motion in the sinogram domain. This work extends the FCC to 3\\text{D} cone-beam CT. We derive an efficient cost function to compensate for 3\\text{D} motion using 2\\text{D} detector translations. The extended FCC method have been tested with five translational motion patterns, using a challenging numerical phantom. We evaluated the root-mean-square-error and the structural-similarity-index between motion corrected and motion-free reconstructions. Additionally, we computed the mean-absolute-difference (MAD) between the estimated and the ground-truth motion. The practical applicability of the method is demonstrated by application to respiratory motion estimation in rotational angiography, but also to motion correction for weight-bearing imaging of knees. Where the latter makes use of a specifically modified FCC version which is robust to axial truncation. The results show a great reduction of motion artifacts. Accurate estimation results were achieved with a maximum MAD value of 708 μm and 1184 μm for motion along the vertical and horizontal detector direction, respectively. The image quality of reconstructions obtained with the proposed method is close to that of motion corrected reconstructions based on the ground-truth motion. Simulations using noise-free and noisy data demonstrate that FCC are robust to noise. Even high-frequency motion was accurately estimated leading to a considerable reduction of streaking artifacts. The method is purely image-based and therefore independent of any auxiliary data.

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

PubMed

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.

A Model of Regularization Parameter Determination in Low-Dose X-Ray CT Reconstruction Based on Dictionary Learning

PubMed Central

Zhang, Cheng; Zhang, Tao; Li, Ming; Lu, Yanfei; You, Jiali; Guan, Yihui

2015-01-01

In recent years, X-ray computed tomography (CT) is becoming widely used to reveal patient's anatomical information. However, the side effect of radiation, relating to genetic or cancerous diseases, has caused great public concern. The problem is how to minimize radiation dose significantly while maintaining image quality. As a practical application of compressed sensing theory, one category of methods takes total variation (TV) minimization as the sparse constraint, which makes it possible and effective to get a reconstruction image of high quality in the undersampling situation. On the other hand, a preliminary attempt of low-dose CT reconstruction based on dictionary learning seems to be another effective choice. But some critical parameters, such as the regularization parameter, cannot be determined by detecting datasets. In this paper, we propose a reweighted objective function that contributes to a numerical calculation model of the regularization parameter. A number of experiments demonstrate that this strategy performs well with better reconstruction images and saving of a large amount of time. PMID:26550024

A Model of Regularization Parameter Determination in Low-Dose X-Ray CT Reconstruction Based on Dictionary Learning.

PubMed

Zhang, Cheng; Zhang, Tao; Zheng, Jian; Li, Ming; Lu, Yanfei; You, Jiali; Guan, Yihui

2015-01-01

In recent years, X-ray computed tomography (CT) is becoming widely used to reveal patient's anatomical information. However, the side effect of radiation, relating to genetic or cancerous diseases, has caused great public concern. The problem is how to minimize radiation dose significantly while maintaining image quality. As a practical application of compressed sensing theory, one category of methods takes total variation (TV) minimization as the sparse constraint, which makes it possible and effective to get a reconstruction image of high quality in the undersampling situation. On the other hand, a preliminary attempt of low-dose CT reconstruction based on dictionary learning seems to be another effective choice. But some critical parameters, such as the regularization parameter, cannot be determined by detecting datasets. In this paper, we propose a reweighted objective function that contributes to a numerical calculation model of the regularization parameter. A number of experiments demonstrate that this strategy performs well with better reconstruction images and saving of a large amount of time.

Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: a review

PubMed Central

Zhang, Hao; Zeng, Dong; Zhang, Hua; Wang, Jing; Liang, Zhengrong

2017-01-01

Low-dose X-ray computed tomography (LDCT) imaging is highly recommended for use in the clinic because of growing concerns over excessive radiation exposure. However, the CT images reconstructed by the conventional filtered back-projection (FBP) method from low-dose acquisitions may be severely degraded with noise and streak artifacts due to excessive X-ray quantum noise, or with view-aliasing artifacts due to insufficient angular sampling. In 2005, the nonlocal means (NLM) algorithm was introduced as a non-iterative edge-preserving filter to denoise natural images corrupted by additive Gaussian noise, and showed superior performance. It has since been adapted and applied to many other image types and various inverse problems. This paper specifically reviews the applications of the NLM algorithm in LDCT image processing and reconstruction, and explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose acquisitions. The effectiveness of these applications on LDCT and their relative performance are described in detail. PMID:28303644

Radiation dose reduction with the adaptive statistical iterative reconstruction (ASIR) technique for chest CT in children: an intra-individual comparison.

PubMed

Lee, Seung Hyun; Kim, Myung-Joon; Yoon, Choon-Sik; Lee, Mi-Jung

2012-09-01

To retrospectively compare radiation dose and image quality of pediatric chest CT using a routine dose protocol reconstructed with filtered back projection (FBP) (the Routine study) and a low-dose protocol with 50% adaptive statistical iterative reconstruction (ASIR) (the ASIR study). We retrospectively reviewed chest CT performed in pediatric patients who underwent both the Routine study and the ASIR study on different days between January 2010 and August 2011. Volume CT dose indices (CTDIvol), dose length products (DLP), and effective doses were obtained to estimate radiation dose. The image quality was evaluated objectively as noise measured in the descending aorta and paraspinal muscle, and subjectively by three radiologists for noise, sharpness, artifacts, and diagnostic acceptability using a four-point scale. The paired Student's t-test and the Wilcoxon signed-rank test were used for statistical analysis. Twenty-six patients (M:F=13:13, mean age 11.7) were enrolled. The ASIR studies showed 60.3%, 56.2%, and 55.2% reductions in CTDIvol (from 18.73 to 7.43 mGy, P<0.001), DLP (from 307.42 to 134.51 mGy×cm, P<0.001), and effective dose (from 4.12 to 1.84 mSv, P<0.001), respectively, compared with the Routine studies. The objective noise was higher in the paraspinal muscle of the ASIR studies (20.81 vs. 16.67, P=0.004), but was not different in the aorta (18.23 vs. 18.72, P=0.726). The subjective image quality demonstrated no difference between the two studies. A low-dose protocol with 50% ASIR allows radiation dose reduction in pediatric chest CT by more than 55% while maintaining image quality. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, S; Lo, P; Hoffman, J

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 modulesmore » 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

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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.

MO-DE-207A-11: Sparse-View CT Reconstruction Via a Novel Non-Local Means Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Z; Qi, H; Wu, S

2016-06-15

Purpose: Sparse-view computed tomography (CT) reconstruction is an effective strategy to reduce the radiation dose delivered to patients. Due to its insufficiency of measurements, traditional non-local means (NLM) based reconstruction methods often lead to over-smoothness in image edges. To address this problem, an adaptive NLM reconstruction method based on rotational invariance (RIANLM) is proposed. Methods: The method consists of four steps: 1) Initializing parameters; 2) Algebraic reconstruction technique (ART) reconstruction using raw projection data; 3) Positivity constraint of the image reconstructed by ART; 4) Update reconstructed image by using RIANLM filtering. In RIANLM, a novel similarity metric that is rotationalmore » invariance is proposed and used to calculate the distance between two patches. In this way, any patch with similar structure but different orientation to the reference patch would win a relatively large weight to avoid over-smoothed image. Moreover, the parameter h in RIANLM which controls the decay of the weights is adaptive to avoid over-smoothness, while it in NLM is not adaptive during the whole reconstruction process. The proposed method is named as ART-RIANLM and validated on Shepp-Logan phantom and clinical projection data. Results: In our experiments, the searching neighborhood size is set to 15 by 15 and the similarity window is set to 3 by 3. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, the ART-RIANLM produces higher SNR (35.38dB<24.00dB) and lower MAE (0.0006<0.0023) reconstructed image than ART-NLM. The visual inspection demonstrated that the proposed method could suppress artifacts or noises more effectively and preserve image edges better. Similar results were found for clinical data case. Conclusion: A novel ART-RIANLM method for sparse-view CT reconstruction is presented with superior image. Compared to the conventional ART-NLM method, the SNR and MAE from ART-RIANLM increases 47% and

Very low-dose (0.15 mGy) chest CT protocols using the COPDGene 2 test object and a third-generation dual-source CT scanner with corresponding third-generation iterative reconstruction software.

PubMed

Newell, John D; Fuld, Matthew K; Allmendinger, Thomas; Sieren, Jered P; Chan, Kung-Sik; Guo, Junfeng; Hoffman, Eric A

2015-01-01

The purpose of this study was to evaluate the impact of ultralow radiation dose single-energy computed tomographic (CT) acquisitions with Sn prefiltration and third-generation iterative reconstruction on density-based quantitative measures of growing interest in phenotyping pulmonary disease. The effects of both decreasing dose and different body habitus on the accuracy of the mean CT attenuation measurements and the level of image noise (SD) were evaluated using the COPDGene 2 test object, containing 8 different materials of interest ranging from air to acrylic and including various density foams. A third-generation dual-source multidetector CT scanner (Siemens SOMATOM FORCE; Siemens Healthcare AG, Erlangen, Germany) running advanced modeled iterative reconstruction (ADMIRE) software (Siemens Healthcare AG) was used.We used normal and very large body habitus rings at dose levels varying from 1.5 to 0.15 mGy using a spectral-shaped (0.6-mm Sn) tube output of 100 kV(p). Three CT scans were obtained at each dose level using both rings. Regions of interest for each material in the test object scans were automatically extracted. The Hounsfield unit values of each material using weighted filtered back projection (WFBP) at 1.5 mGy was used as the reference value to evaluate shifts in CT attenuation at lower dose levels using either WFBP or ADMIRE. Statistical analysis included basic statistics, Welch t tests, multivariable covariant model using the F test to assess the significance of the explanatory (independent) variables on the response (dependent) variable, and CT mean attenuation, in the multivariable covariant model including reconstruction method. Multivariable regression analysis of the mean CT attenuation values showed a significant difference with decreasing dose between ADMIRE and WFBP. The ADMIRE has reduced noise and more stable CT attenuation compared with WFBP. There was a strong effect on the mean CT attenuation values of the scanned materials for ring

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening.

PubMed

Nomura, Yukihiro; Higaki, Toru; Fujita, Masayo; Miki, Soichiro; Awaya, Yoshikazu; Nakanishi, Toshio; Yoshikawa, Takeharu; Hayashi, Naoto; Awai, Kazuo

2017-02-01

This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening. We selected 85 subjects who underwent both a low-dose CT (LD-CT) scan and an additional ULD-CT scan in our lung cancer screening program for high-risk populations. The LD-CT scans were reconstructed with filtered back projection (FBP; LD-FBP). The ULD-CT scans were reconstructed with FBP (ULD-FBP), adaptive iterative dose reduction 3D (AIDR 3D; ULD-AIDR 3D), and forward projected model-based IR solution (FIRST; ULD-FIRST). CAD software for lung nodules was applied to each image dataset, and the performance of the CAD software was compared among the different IR algorithms. The mean volume CT dose indexes were 3.02 mGy (LD-CT) and 0.30 mGy (ULD-CT). For overall nodules, the sensitivities of CAD software at 3.0 false positives per case were 78.7% (LD-FBP), 9.3% (ULD-FBP), 69.4% (ULD-AIDR 3D), and 77.8% (ULD-FIRST). Statistical analysis showed that the sensitivities of ULD-AIDR 3D and ULD-FIRST were significantly higher than that of ULD-FBP (P < .001). The performance of CAD software in ULD-CT was improved by using IR algorithms. In particular, the performance of CAD in ULD-FIRST was almost equivalent to that in LD-FBP. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

SU-F-I-36: In-Utero Dose Measurements Within Postmortem Subjects for Estimating Fetal Doses in Pregnant Patients Examined with Pulmonary Embolism, Trauma, and Appendicitis CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lipnharski, I; Quails, N; Carranza, C

Purpose: The imaging of pregnant patients is medically necessary in certain clinical situations. The purpose of this work was to directly measure uterine doses in a cadaver scanned with CT protocols commonly performed on pregnant patients in order to estimate fetal dose and assess potential risk. Method: One postmortem subject was scanned on a 320-slice CT scanner with standard pulmonary embolism, trauma, and appendicitis protocols. All protocols were performed with the scan parameters and ranges currently used in clinical practice. Exams were performed both with and without iterative reconstruction to highlight the dose savings potential. Optically stimulated luminescent dosimeters (OSLDs)more » were inserted into the uterus in order to approximate fetal doses. Results: In the pulmonary embolism CT protocol, the uterus is outside of the primary beam, and the dose to the uterus was under 1 mGy. In the trauma and appendicitis protocols, the uterus is in the primary beam, the fetal dose estimates were 30.5 mGy for the trauma protocol, and 20.6 mGy for the appendicitis protocol. Iterative reconstruction reduced fetal doses by 30%, with uterine doses at 21.3 for the trauma and 14.3 mGy for the appendicitis protocol. Conclusion: Fetal doses were under 1 mGy when exposed to scatter radiation, and under 50 mGy when exposed to primary radiation with the trauma and appendicitis protocols. Consistent with the National Council on Radiation Protection & Measurements (NCRP) and the International Commission on Radiological Protection (ICRP), these doses exhibit a negligible risk to the fetus, with only a small increased risk of cancer. Still, CT scans are not recommended during pregnancy unless the benefits of the exam clearly outweigh the potential risk. Furthermore, when possible, pregnant patients should be examined on CT scanners equipped with iterative reconstruction in order to keep patient doses as low as reasonable achievable.« less

MO-DE-207A-10: One-Step CT Reconstruction for Metal Artifact Reduction by a Modification of Penalized Weighted Least-Squares (PWLS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, H; Chen, J

Purpose: Metal objects create severe artifacts in kilo-voltage (kV) CT image reconstructions due to the high attenuation coefficients of high atomic number objects. Most of the techniques devised to reduce this artifact utilize a two-step approach, which do not reliably yield the qualified reconstructed images. Thus, for accuracy and simplicity, this work presents a one-step reconstruction method based on a modified penalized weighted least-squares (PWLS) technique. Methods: Existing techniques for metal artifact reduction mostly adopt a two-step approach, which conduct additional reconstruction with the modified projection data from the initial reconstruction. This procedure does not consistently perform well due tomore » the uncertainties in manipulating the metal-contaminated projection data by thresholding and linear interpolation. This study proposes a one-step reconstruction process using a new PWLS operation with total-variation (TV) minimization, while not manipulating the projection. The PWLS for CT reconstruction has been investigated using a pre-defined weight, based on the variance of the projection datum at each detector bin. It works well when reconstructing CT images from metal-free projection data, which does not appropriately penalize metal-contaminated projection data. The proposed work defines the weight at each projection element under the assumption of a Poisson random variable. This small modification using element-wise penalization has a large impact in reducing metal artifacts. For evaluation, the proposed technique was assessed with two noisy, metal-contaminated digital phantoms, against the existing PWLS with TV minimization and the two-step approach. Result: The proposed PWLS with TV minimization greatly improved the metal artifact reduction, relative to the other techniques, by watching the results. Numerically, the new approach lowered the normalized root-mean-square error about 30 and 60% for the two cases, respectively, compared to

Image reconstruction and scan configurations enabled by optimization-based algorithms in multispectral CT

NASA Astrophysics Data System (ADS)

Chen, Buxin; Zhang, Zheng; Sidky, Emil Y.; Xia, Dan; Pan, Xiaochuan

2017-11-01

Optimization-based algorithms for image reconstruction in multispectral (or photon-counting) computed tomography (MCT) remains a topic of active research. The challenge of optimization-based image reconstruction in MCT stems from the inherently non-linear data model that can lead to a non-convex optimization program for which no mathematically exact solver seems to exist for achieving globally optimal solutions. In this work, based upon a non-linear data model, we design a non-convex optimization program, derive its first-order-optimality conditions, and propose an algorithm to solve the program for image reconstruction in MCT. In addition to consideration of image reconstruction for the standard scan configuration, the emphasis is on investigating the algorithm’s potential for enabling non-standard scan configurations with no or minimum hardware modification to existing CT systems, which has potential practical implications for lowered hardware cost, enhanced scanning flexibility, and reduced imaging dose/time in MCT. Numerical studies are carried out for verification of the algorithm and its implementation, and for a preliminary demonstration and characterization of the algorithm in reconstructing images and in enabling non-standard configurations with varying scanning angular range and/or x-ray illumination coverage in MCT.

Ultra-low dose quantitative CT myocardial perfusion imaging with sparse-view dynamic acquisition and image reconstruction: A feasibility study.

PubMed

Enjilela, Esmaeil; Lee, Ting-Yim; Hsieh, Jiang; Wisenberg, Gerald; Teefy, Patrick; Yadegari, Andrew; Bagur, Rodrigo; Islam, Ali; Branch, Kelley; So, Aaron

2018-03-01

We implemented and validated a compressed sensing (CS) based algorithm for reconstructing dynamic contrast-enhanced (DCE) CT images of the heart from sparsely sampled X-ray projections. DCE CT imaging of the heart was performed on five normal and ischemic pigs after contrast injection. DCE images were reconstructed with filtered backprojection (FBP) and CS from all projections (984-view) and 1/3 of all projections (328-view), and with CS from 1/4 of all projections (246-view). Myocardial perfusion (MP) measurements with each protocol were compared to those with the reference 984-view FBP protocol. Both the 984-view CS and 328-view CS protocols were in good agreements with the reference protocol. The Pearson correlation coefficients of 984-view CS and 328-view CS determined from linear regression analyses were 0.98 and 0.99 respectively. The corresponding mean biases of MP measurement determined from Bland-Altman analyses were 2.7 and 1.2ml/min/100g. When only 328 projections were used for image reconstruction, CS was more accurate than FBP for MP measurement with respect to 984-view FBP. However, CS failed to generate MP maps comparable to those with 984-view FBP when only 246 projections were used for image reconstruction. DCE heart images reconstructed from one-third of a full projection set with CS were minimally affected by aliasing artifacts, leading to accurate MP measurements with the effective dose reduced to just 33% of conventional full-view FBP method. The proposed CS sparse-view image reconstruction method could facilitate the implementation of sparse-view dynamic acquisition for ultra-low dose CT MP imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Beam hardening correction in CT myocardial perfusion measurement

NASA Astrophysics Data System (ADS)

So, Aaron; Hsieh, Jiang; Li, Jian-Ying; Lee, Ting-Yim

2009-05-01

This paper presents a method for correcting beam hardening (BH) in cardiac CT perfusion imaging. The proposed algorithm works with reconstructed images instead of projection data. It applies thresholds to separate low (soft tissue) and high (bone and contrast) attenuating material in a CT image. The BH error in each projection is estimated by a polynomial function of the forward projection of the segmented image. The error image is reconstructed by back-projection of the estimated errors. A BH-corrected image is then obtained by subtracting a scaled error image from the original image. Phantoms were designed to simulate the BH artifacts encountered in cardiac CT perfusion studies of humans and animals that are most commonly used in cardiac research. These phantoms were used to investigate whether BH artifacts can be reduced with our approach and to determine the optimal settings, which depend upon the anatomy of the scanned subject, of the correction algorithm for patient and animal studies. The correction algorithm was also applied to correct BH in a clinical study to further demonstrate the effectiveness of our technique.

Ultralow dose dentomaxillofacial CT imaging and iterative reconstruction techniques: variability of Hounsfield units and contrast-to-noise ratio

PubMed Central

Bischel, Alexander; Stratis, Andreas; Kakar, Apoorv; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben

2016-01-01

Objective: The aim of this study was to evaluate whether application of ultralow dose protocols and iterative reconstruction technology (IRT) influence quantitative Hounsfield units (HUs) and contrast-to-noise ratio (CNR) in dentomaxillofacial CT imaging. Methods: A phantom with inserts of five types of materials was scanned using protocols for (a) a clinical reference for navigated surgery (CT dose index volume 36.58 mGy), (b) low-dose sinus imaging (18.28 mGy) and (c) four ultralow dose imaging (4.14, 2.63, 0.99 and 0.53 mGy). All images were reconstructed using: (i) filtered back projection (FBP); (ii) IRT: adaptive statistical iterative reconstruction-50 (ASIR-50), ASIR-100 and model-based iterative reconstruction (MBIR); and (iii) standard (std) and bone kernel. Mean HU, CNR and average HU error after recalibration were determined. Each combination of protocols was compared using Friedman analysis of variance, followed by Dunn's multiple comparison test. Results: Pearson's sample correlation coefficients were all >0.99. Ultralow dose protocols using FBP showed errors of up to 273 HU. Std kernels had less HU variability than bone kernels. MBIR reduced the error value for the lowest dose protocol to 138 HU and retained the highest relative CNR. ASIR could not demonstrate significant advantages over FBP. Conclusions: Considering a potential dose reduction as low as 1.5% of a std protocol, ultralow dose protocols and IRT should be further tested for clinical dentomaxillofacial CT imaging. Advances in knowledge: HU as a surrogate for bone density may vary significantly in CT ultralow dose imaging. However, use of std kernels and MBIR technology reduce HU error values and may retain the highest CNR. PMID:26859336

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.

PubMed

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Guang-Hong, E-mail: gchen7@wisc.edu; Li, Yinsheng

Purpose: 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. Methods:more » 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

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

PubMed

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 < .001) more accurate for IFS when compared with filtered back projection. In patients, best overall and pelvic organ image quality was found in all reformations with IFS (P < .001). Pelvic abnormalities in 11 of 41 patients (27%) were diagnosed with significantly (P = .002) higher confidence on the basis of IFS images. CT attenuation of bladder (P < .001) and muscle (P = .043) was significantly less variable with IFS compared with filtered back projection and linear interpolation MAR. In comparison with that of FBP and linear interpolation MAR, noise with IFS was similar close to and far from the prosthesis (P = .295). The IFS 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.

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

NASA Astrophysics Data System (ADS)

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

Bragg peak prediction from quantitative proton computed tomography using different path estimates

PubMed Central

Wang, Dongxu; Mackie, T Rockwell

2015-01-01

This paper characterizes the performance of the straight-line path (SLP) and cubic spline path (CSP) as path estimates used in reconstruction of proton computed tomography (pCT). The GEANT4 Monte Carlo simulation toolkit is employed to simulate the imaging phantom and proton projections. SLP, CSP and the most-probable path (MPP) are constructed based on the entrance and exit information of each proton. The physical deviations of SLP, CSP and MPP from the real path are calculated. Using a conditional proton path probability map, the relative probability of SLP, CSP and MPP are calculated and compared. The depth dose and Bragg peak are predicted on the pCT images reconstructed using SLP, CSP, and MPP and compared with the simulation result. The root-mean-square physical deviations and the cumulative distribution of the physical deviations show that the performance of CSP is comparable to MPP while SLP is slightly inferior. About 90% of the SLP pixels and 99% of the CSP pixels lie in the 99% relative probability envelope of the MPP. Even at an imaging dose of ~0.1 mGy the proton Bragg peak for a given incoming energy can be predicted on the pCT image reconstructed using SLP, CSP, or MPP with 1 mm accuracy. This study shows that SLP and CSP, like MPP, are adequate path estimates for pCT reconstruction, and therefore can be chosen as the path estimation method for pCT reconstruction, which can aid the treatment planning and range prediction of proton radiation therapy. PMID:21212472

[Evaluation of Organ Dose Estimation from Indices of CT Dose Using Dose Index Registry].

PubMed

Iriuchijima, Akiko; Fukushima, Yasuhiro; Ogura, Akio

Direct measurement of each patient organ dose from computed tomography (CT) is not possible. Most methods to estimate patient organ dose is using Monte Carlo simulation with dedicated software. However, dedicated software is too expensive for small scale hospitals. Not every hospital can estimate organ dose with dedicated software. The purpose of this study was to evaluate the simple method of organ dose estimation using some common indices of CT dose. The Monte Carlo simulation software Radimetrics (Bayer) was used for calculating organ dose and analysis relationship between indices of CT dose and organ dose. Multidetector CT scanners were compared with those from two manufactures (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare). Using stored patient data from Radimetrics, the relationships between indices of CT dose and organ dose were indicated as each formula for estimating organ dose. The accuracy of estimation method of organ dose was compared with the results of Monte Carlo simulation using the Bland-Altman plots. In the results, SSDE was the feasible index for estimation organ dose in almost organs because it reflected each patient size. The differences of organ dose between estimation and simulation were within 23%. In conclusion, our estimation method of organ dose using indices of CT dose is convenient for clinical with accuracy.

WE-FG-207B-12: Quantitative Evaluation of a Spectral CT Scanner in a Phantom Study: Results of Spectral Reconstructions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duan, X; Arbique, G; Guild, J

Purpose: To evaluate the quantitative image quality of spectral reconstructions of phantom data from a spectral CT scanner. Methods: The spectral CT scanner (IQon Spectral CT, Philips Healthcare) is equipped with a dual-layer detector and generates conventional 80-140 kVp images and variety of spectral reconstructions, e.g., virtual monochromatic (VM) images, virtual non-contrast (VNC) images, iodine maps, and effective atomic number (Z) images. A cylindrical solid water phantom (Gammex 472, 33 cm diameter and 5 cm thick) with iodine (2.0-20.0 mg I/ml) and calcium (50-600 mg/ml) rod inserts was scanned at 120 kVp and 27 mGy CTDIvol. Spectral reconstructions were evaluatedmore » by comparing image measurements with theoretical values calculated from nominal rod compositions provided by the phantom manufacturer. The theoretical VNC was calculated using water and iodine basis material decomposition, and the theoretical Z was calculated using two common methods, the chemical formula method (Z1) and the dual-energy ratio method (Z2). Results: Beam-hardening-like artifacts between high-attenuation calcium rods (≥300 mg/ml, >800 HU) influenced quantitative measurements, so the quantitative analysis was only performed on iodine rods using the images from the scan with all the calcium rods removed. The CT numbers of the iodine rods in the VM images (50∼150 keV) were close to theoretical values with average difference of 2.4±6.9 HU. Compared with theoretical values, the average difference for iodine concentration, VNC CT number and effective Z of iodine rods were −0.10±0.38 mg/ml, −0.1±8.2 HU, 0.25±0.06 (Z1) and −0.23±0.07 (Z2). Conclusion: The results indicate that the spectral CT scanner generates quantitatively accurate spectral reconstructions at clinically relevant iodine concentrations. Beam-hardening-like artifacts still exist when high-attenuation objects are present and their impact on patient images needs further investigation. YY is an employee of

Estimation of aortic valve leaflets from 3D CT images using local shape dictionaries and linear coding

NASA Astrophysics Data System (ADS)

Liang, Liang; Martin, Caitlin; Wang, Qian; Sun, Wei; Duncan, James

2016-03-01

Aortic valve (AV) disease is a significant cause of morbidity and mortality. The preferred treatment modality for severe AV disease is surgical resection and replacement of the native valve with either a mechanical or tissue prosthetic. In order to develop effective and long-lasting treatment methods, computational analyses, e.g., structural finite element (FE) and computational fluid dynamic simulations, are very effective for studying valve biomechanics. These computational analyses are based on mesh models of the aortic valve, which are usually constructed from 3D CT images though many hours of manual annotation, and therefore an automatic valve shape reconstruction method is desired. In this paper, we present a method for estimating the aortic valve shape from 3D cardiac CT images, which is represented by triangle meshes. We propose a pipeline for aortic valve shape estimation which includes novel algorithms for building local shape dictionaries and for building landmark detectors and curve detectors using local shape dictionaries. The method is evaluated on real patient image dataset using a leave-one-out approach and achieves an average accuracy of 0.69 mm. The work will facilitate automatic patient-specific computational modeling of the aortic valve.

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

PubMed

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 < 0.05). In terms of subjective image evaluation, all 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 < 0.05), and 60% 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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, H

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 tomore » 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).« less

Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations.

PubMed

Noël, Peter B; Engels, Stephan; Köhler, Thomas; Muenzel, Daniela; Franz, Daniela; Rasper, Michael; Rummeny, Ernst J; Dobritz, Martin; Fingerle, Alexander A

2018-01-01

Background The explosive growth of computer tomography (CT) has led to a growing public health concern about patient and population radiation dose. A recently introduced technique for dose reduction, which can be combined with tube-current modulation, over-beam reduction, and organ-specific dose reduction, is iterative reconstruction (IR). Purpose To evaluate the quality, at different radiation dose levels, of three reconstruction algorithms for diagnostics of patients with proven liver metastases under tumor follow-up. Material and Methods A total of 40 thorax-abdomen-pelvis CT examinations acquired from 20 patients in a tumor follow-up were included. All patients were imaged using the standard-dose and a specific low-dose CT protocol. Reconstructed slices were generated by using three different reconstruction algorithms: a classical filtered back projection (FBP); a first-generation iterative noise-reduction algorithm (iDose4); and a next generation model-based IR algorithm (IMR). Results The overall detection of liver lesions tended to be higher with the IMR algorithm than with FBP or iDose4. The IMR dataset at standard dose yielded the highest overall detectability, while the low-dose FBP dataset showed the lowest detectability. For the low-dose protocols, a significantly improved detectability of the liver lesion can be reported compared to FBP or iDose 4 ( P = 0.01). The radiation dose decreased by an approximate factor of 5 between the standard-dose and the low-dose protocol. Conclusion The latest generation of IR algorithms significantly improved the diagnostic image quality and provided virtually noise-free images for ultra-low-dose CT imaging.

Joint reconstruction of activity and attenuation in Time-of-Flight PET: A Quantitative Analysis.

PubMed

Rezaei, Ahmadreza; Deroose, Christophe M; Vahle, Thomas; Boada, Fernando; Nuyts, Johan

2018-03-01

Joint activity and attenuation reconstruction methods from time of flight (TOF) positron emission tomography (PET) data provide an effective solution to attenuation correction when no (or incomplete/inaccurate) information on the attenuation is available. One of the main barriers limiting their use in clinical practice is the lack of validation of these methods on a relatively large patient database. In this contribution, we aim at validating the activity reconstructions of the maximum likelihood activity reconstruction and attenuation registration (MLRR) algorithm on a whole-body patient data set. Furthermore, a partial validation (since the scale problem of the algorithm is avoided for now) of the maximum likelihood activity and attenuation reconstruction (MLAA) algorithm is also provided. We present a quantitative comparison of the joint reconstructions to the current clinical gold-standard maximum likelihood expectation maximization (MLEM) reconstruction with CT-based attenuation correction. Methods: The whole-body TOF-PET emission data of each patient data set is processed as a whole to reconstruct an activity volume covering all the acquired bed positions, which helps to reduce the problem of a scale per bed position in MLAA to a global scale for the entire activity volume. Three reconstruction algorithms are used: MLEM, MLRR and MLAA. A maximum likelihood (ML) scaling of the single scatter simulation (SSS) estimate to the emission data is used for scatter correction. The reconstruction results are then analyzed in different regions of interest. Results: The joint reconstructions of the whole-body patient data set provide better quantification in case of PET and CT misalignments caused by patient and organ motion. Our quantitative analysis shows a difference of -4.2% (±2.3%) and -7.5% (±4.6%) between the joint reconstructions of MLRR and MLAA compared to MLEM, averaged over all regions of interest, respectively. Conclusion: Joint activity and attenuation

Microvascular transplants in head and neck reconstruction: 3D evaluation of volume loss.

PubMed

Bittermann, Gido; Thönissen, Philipp; Poxleitner, Philipp; Zimmerer, Ruediger; Vach, Kirstin; Metzger, Marc C

2015-10-01

Despite oversized latissimus dorsi free flap reconstruction in the head and neck area, esthetic and functional problems continue to exist due to the well-known occurrence of transplant shrinkage. The purpose of this study was to acquire an estimation of the volume and time of the shrinkage process. The assessment of volume loss was performed using a 3D evaluation of two postoperative CT scans. A retrospective review was conducted on all latissimus dorsi free flap reconstructions performed between 2004 and 2013. Inclusion criteria for the assessment were: resection of an oral carcinoma and microsurgical defect coverage with latissimus dorsi free flap; a first postoperative CT (CT1) performed between 3 weeks and a maximum of 3 months after reconstruction surgery; and an additional CT scan (CT2) performed at least one year postoperatively. The exclusion criterion was surgical intervention in the local area between the acquisition of CT1 and CT2. The effect of adjuvant radiation therapy was considered. Volume determination of the transplant was carried out in CT1 and CT2 by manual segmentation of the graft. Fifteen patients were recruited. 3D evaluation showed an average volume loss of 34.4%. In the consideration of postoperative radiotherapy the volume reduction was 39.2% in patients with radiotherapy and 31.3% in patients without radiotherapy. The reconstruction flap volume required for overcorrection of the surgical defect was investigated. This study indicates that a volume loss of more than 30% could be expected one or more years after latissimus dorsi free flap reconstruction. Clinical trial number DRKS00007534. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Multiresolution Iterative Reconstruction in High-Resolution Extremity Cone-Beam CT

PubMed Central

Cao, Qian; Zbijewski, Wojciech; Sisniega, Alejandro; Yorkston, John; Siewerdsen, Jeffrey H; Stayman, J Webster

2016-01-01

Application of model-based iterative reconstruction (MBIR) to high resolution cone-beam CT (CBCT) is computationally challenging because of the very fine discretization (voxel size <100 µm) of the reconstructed volume. Moreover, standard MBIR techniques require that the complete transaxial support for the acquired projections is reconstructed, thus precluding acceleration by restricting the reconstruction to a region-of-interest. To reduce the computational burden of high resolution MBIR, we propose a multiresolution Penalized-Weighted Least Squares (PWLS) algorithm, where the volume is parameterized as a union of fine and coarse voxel grids as well as selective binning of detector pixels. We introduce a penalty function designed to regularize across the boundaries between the two grids. The algorithm was evaluated in simulation studies emulating an extremity CBCT system and in a physical study on a test-bench. Artifacts arising from the mismatched discretization of the fine and coarse sub-volumes were investigated. The fine grid region was parameterized using 0.15 mm voxels and the voxel size in the coarse grid region was varied by changing a downsampling factor. No significant artifacts were found in either of the regions for downsampling factors of up to 4×. For a typical extremities CBCT volume size, this downsampling corresponds to an acceleration of the reconstruction that is more than five times faster than a brute force solution that applies fine voxel parameterization to the entire volume. For certain configurations of the coarse and fine grid regions, in particular when the boundary between the regions does not cross high attenuation gradients, downsampling factors as high as 10× can be used without introducing artifacts, yielding a ~50× speedup in PWLS. The proposed multiresolution algorithm significantly reduces the computational burden of high resolution iterative CBCT reconstruction and can be extended to other applications of MBIR where

Is the evaluation of the anterior inferior iliac spine (AIIS) in the AP pelvis possible? Analysis of conventional X-rays and 3D-CT reconstructions.

PubMed

Krueger, David R; Windler, Markus; Geßlein, Markus; Schuetz, Michael; Perka, Carsten; Schroeder, Joerg H

2017-07-01

A hypertrophic AIIS has been identified as a cause for extraarticular hip impingement and is classified according to Hetsroni using 3D-CT reconstructions. The role of the conventional AP pelvis X-ray, which is the first standard imaging step for the evaluation of hip pain, has not been investigated yet. AP pelvis X-rays and 3D-CT reconstructions of patients were evaluated regarding their morphology of the AIIS. The conventional X-rays were categorized into three groups according to the projection of the AIIS: above (A) or below (B) the acetabular sourcil or even exceeding the anterior acetabular rim (C). They were compared to the morphologic types in the 3D-CT reconstruction (Hetsroni type I-III). Ninety patients with an equal distribution of type A, B or C projection in the AP pelvis were evaluated and compared to the morphology in the 3D-CT reconstruction. The projection of the AIIS below the acetabular sourcil (B + C) showed only moderate sensitivity (0.76) and specificity (0.64) for a hypertrophic AIIS (Hetsroni type II + III), but if the AIIS exceeds the anterior rim, all cases showed a hypertrophic AIIS in the 3D-CT reconstructions (Hetsroni type II + III). Distinct differentiation of the AIIS morphology in the AP pelvis is not possible, but the projection of the AIIS below the anterior acetabular rim represented a hypertrophic AIIS in all cases and should, therefore, be critically investigated for a relevant AIIS impingement.

Estimation of 3D reconstruction errors in a stereo-vision system

NASA Astrophysics Data System (ADS)

Belhaoua, A.; Kohler, S.; Hirsch, E.

2009-06-01

The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.

Adaptive statistical iterative reconstruction use for radiation dose reduction in pediatric lower-extremity CT: impact on diagnostic image quality.

PubMed

Shah, Amisha; Rees, Mitchell; Kar, Erica; Bolton, Kimberly; Lee, Vincent; Panigrahy, Ashok

2018-06-01

For the past several years, increased levels of imaging radiation and cumulative radiation to children has been a significant concern. Although several measures have been taken to reduce radiation dose during computed tomography (CT) scan, the newer dose reduction software adaptive statistical iterative reconstruction (ASIR) has been an effective technique in reducing radiation dose. To our knowledge, no studies are published that assess the effect of ASIR on extremity CT scans in children. To compare radiation dose, image noise, and subjective image quality in pediatric lower extremity CT scans acquired with and without ASIR. The study group consisted of 53 patients imaged on a CT scanner equipped with ASIR software. The control group consisted of 37 patients whose CT images were acquired without ASIR. Image noise, Computed Tomography Dose Index (CTDI) and dose length product (DLP) were measured. Two pediatric radiologists rated the studies in subjective categories: image sharpness, noise, diagnostic acceptability, and artifacts. The CTDI (p value = 0.0184) and DLP (p value <0.0002) were significantly decreased with the use of ASIR compared with non-ASIR studies. However, the subjective ratings for sharpness (p < 0.0001) and diagnostic acceptability of the ASIR images (p < 0.0128) were decreased compared with standard, non-ASIR CT studies. Adaptive statistical iterative reconstruction reduces radiation dose for lower extremity CTs in children, but at the expense of diagnostic imaging quality. Further studies are warranted to determine the specific utility of ASIR for pediatric musculoskeletal CT imaging.

Paediatric cardiac CT examinations: impact of the iterative reconstruction method ASIR on image quality--preliminary findings.

PubMed

Miéville, Frédéric A; Gudinchet, François; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Bochud, François O; Verdun, Francis R

2011-09-01

Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI(vol) 4.8-7.9 mGy, DLP 37.1-178.9 mGy·cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone.

Improving the quality of reconstructed X-ray CT images of polymer gel dosimeters: zero-scan coupled with adaptive mean filtering.

PubMed

Kakakhel, M B; Jirasek, A; Johnston, H; Kairn, T; Trapp, J V

2017-03-01

This study evaluated the feasibility of combining the 'zero-scan' (ZS) X-ray computed tomography (CT) based polymer gel dosimeter (PGD) readout with adaptive mean (AM) filtering for improving the signal to noise ratio (SNR), and to compare these results with available average scan (AS) X-ray CT readout techniques. NIPAM PGD were manufactured, irradiated with 6 MV photons, CT imaged and processed in Matlab. AM filter for two iterations, with 3 × 3 and 5 × 5 pixels (kernel size), was used in two scenarios (a) the CT images were subjected to AM filtering (pre-processing) and these were further employed to generate AS and ZS gel images, and (b) the AS and ZS images were first reconstructed from the CT images and then AM filtering was carried out (post-processing). SNR was computed in an ROI of 30 × 30 for different pre and post processing cases. Results showed that the ZS technique combined with AM filtering resulted in improved SNR. Using the previously-recommended 25 images for reconstruction the ZS pre-processed protocol can give an increase of 44% and 80% in SNR for 3 × 3 and 5 × 5 kernel sizes respectively. However, post processing using both techniques and filter sizes introduced blur and a reduction in the spatial resolution. Based on this work, it is possible to recommend that the ZS method may be combined with pre-processed AM filtering using appropriate kernel size, to produce a large increase in the SNR of the reconstructed PGD images.

Optimization of view weighting in tilted-plane-based reconstruction algorithms to minimize helical artifacts in multi-slice helical CT

NASA Astrophysics Data System (ADS)

Tang, Xiangyang

2003-05-01

In multi-slice helical CT, the single-tilted-plane-based reconstruction algorithm has been proposed to combat helical and cone beam artifacts by tilting a reconstruction plane to fit a helical source trajectory optimally. Furthermore, to improve the noise characteristics or dose efficiency of the single-tilted-plane-based reconstruction algorithm, the multi-tilted-plane-based reconstruction algorithm has been proposed, in which the reconstruction plane deviates from the pose globally optimized due to an extra rotation along the 3rd axis. As a result, the capability of suppressing helical and cone beam artifacts in the multi-tilted-plane-based reconstruction algorithm is compromised. An optomized tilted-plane-based reconstruction algorithm is proposed in this paper, in which a matched view weighting strategy is proposed to optimize the capability of suppressing helical and cone beam artifacts and noise characteristics. A helical body phantom is employed to quantitatively evaluate the imaging performance of the matched view weighting approach by tabulating artifact index and noise characteristics, showing that the matched view weighting improves both the helical artifact suppression and noise characteristics or dose efficiency significantly in comparison to the case in which non-matched view weighting is applied. Finally, it is believed that the matched view weighting approach is of practical importance in the development of multi-slive helical CT, because it maintains the computational structure of fan beam filtered backprojection and demands no extra computational services.

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

PubMed

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

2016-01-01

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. 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 readers using a five

Noninvasive Vascular Displacement Estimation for Relative Elastic Modulus Reconstruction in Transversal Imaging Planes

PubMed Central

Hansen, Hendrik H.G.; Richards, Michael S.; Doyley, Marvin M.; de Korte, Chris L.

2013-01-01

Atherosclerotic plaque rupture can initiate stroke or myocardial infarction. Lipid-rich plaques with thin fibrous caps have a higher risk to rupture than fibrotic plaques. Elastic moduli differ for lipid-rich and fibrous tissue and can be reconstructed using tissue displacements estimated from intravascular ultrasound radiofrequency (RF) data acquisitions. This study investigated if modulus reconstruction is possible for noninvasive RF acquisitions of vessels in transverse imaging planes using an iterative 2D cross-correlation based displacement estimation algorithm. Furthermore, since it is known that displacements can be improved by compounding of displacements estimated at various beam steering angles, we compared the performance of the modulus reconstruction with and without compounding. For the comparison, simulated and experimental RF data were generated of various vessel-mimicking phantoms. Reconstruction errors were less than 10%, which seems adequate for distinguishing lipid-rich from fibrous tissue. Compounding outperformed single-angle reconstruction: the interquartile range of the reconstructed moduli for the various homogeneous phantom layers was approximately two times smaller. Additionally, the estimated lateral displacements were a factor of 2–3 better matched to the displacements corresponding to the reconstructed modulus distribution. Thus, noninvasive elastic modulus reconstruction is possible for transverse vessel cross sections using this cross-correlation method and is more accurate with compounding. PMID:23478602

COMPARISON OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION (ASIR™) AND MODEL-BASED ITERATIVE RECONSTRUCTION (VEO™) FOR PAEDIATRIC ABDOMINAL CT EXAMINATIONS: AN OBSERVER PERFORMANCE STUDY OF DIAGNOSTIC IMAGE QUALITY.

PubMed

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

2016-06-01

The diagnostic image quality of 75 paediatric abdominal computed tomography (CT) examinations reconstructed with two different iterative reconstruction (IR) algorithms-adaptive statistical IR (ASiR™) and model-based IR (Veo™)-was compared. Axial and coronal images were reconstructed with 70 % ASiR with the Soft™ 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. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Polychromatic sparse image reconstruction and mass attenuation spectrum estimation via B-spline basis function expansion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Renliang, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu; Dogandžić, Aleksandar, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu

2015-03-31

We develop a sparse image reconstruction method for polychromatic computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. To obtain a parsimonious measurement model parameterization, we first rewrite the measurement equation using our mass-attenuation parameterization, which has the Laplace integral form. The unknown mass-attenuation spectrum is expanded into basis functions using a B-spline basis of order one. We develop a block coordinate-descent algorithm for constrained minimization of a penalized negative log-likelihood function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and sparsity of themore » density map image in the wavelet domain. This algorithm alternates between a Nesterov’s proximal-gradient step for estimating the density map image and an active-set step for estimating the incident spectrum parameters. Numerical simulations demonstrate the performance of the proposed scheme.« less

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

PubMed

Zhang, Lingli; Zeng, Li; Guo, Yumeng

2018-01-01

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

Low-dose CT imaging of a total hip arthroplasty phantom using model-based iterative reconstruction and orthopedic metal artifact reduction.

PubMed

Wellenberg, R H H; Boomsma, M F; van Osch, J A C; Vlassenbroek, A; Milles, J; Edens, M A; Streekstra, G J; Slump, C H; Maas, M

2017-05-01

To compare quantitative measures of image quality, in terms of CT number accuracy, noise, signal-to-noise-ratios (SNRs), and contrast-to-noise ratios (CNRs), at different dose levels with filtered-back-projection (FBP), iterative reconstruction (IR), and model-based iterative reconstruction (MBIR) alone and in combination with orthopedic metal artifact reduction (O-MAR) in a total hip arthroplasty (THA) phantom. Scans were acquired from high- to low-dose (CTDI vol : 40.0, 32.0, 24.0, 16.0, 8.0, and 4.0 mGy) at 120- and 140- kVp. Images were reconstructed using FBP, IR (iDose 4 level 2, 4, and 6) and MBIR (IMR, level 1, 2, and 3) with and without O-MAR. CT number accuracy in Hounsfield Units (HU), noise or standard deviation, SNRs, and CNRs were analyzed. The IMR technique showed lower noise levels (p < 0.01), higher SNRs (p < 0.001) and CNRs (p < 0.001) compared with FBP and iDose 4 in all acquisitions from high- to low-dose with constant CT numbers. O-MAR reduced noise (p < 0.01) and improved SNRs (p < 0.01) and CNRs (p < 0.001) while improving CT number accuracy only at a low dose. At the low dose of 4.0 mGy, IMR level 1, 2, and 3 showed 83%, 89%, and 95% lower noise values, a factor 6.0, 9.2, and 17.9 higher SNRs, and 5.7, 8.8, and 18.2 higher CNRs compared with FBP respectively. Based on quantitative analysis of CT number accuracy, noise values, SNRs, and CNRs, we conclude that the combined use of IMR and O-MAR enables a reduction in radiation dose of 83% compared with FBP and iDose 4 in the CT imaging of a THA phantom.

TH-CD-207B-10: Effect of CT Reconstruction Filter On Measured Hounsfield Values in Lung Nodules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Little, K; Reiser, I; Sanchez, A

Purpose: Measured Hounsfield numbers in CT are used by radiologists to determine the presence of calcium or fat in lung nodules, either of which suggests a benign diagnosis. However, substantial variations in Hounsfield number may arise due to the use of different reconstruction parameters such as the filter/kernel, leading to measurement inaccuracies. This quality improvement project was developed to demonstrate measurement pitfalls and to identify acceptable conditions for incorporating Hounsfield values as a factor in lung nodule diagnosis. Methods: 12 mm-diameter spheres of polyurethane and urethane foam were placed into an anthropomorphic chest phantom, and 10 mm-diameter tubes with varyingmore » iodine concentrations were placed into a 16 cm PMMA cylindrical phantom. Additionally, 11 mm-diameter PMMA and HDPE spheres were placed in a 10 cm PMMA cylindrical phantom. Phantoms were scanned at 120 kVp using a Siemens Biograph mCT and on a Philips iCT and reconstructed using various reconstruction filters. Results: For the Siemens system, both sharp kernels and smooth kernels altered the Hounsfield numbers. Hounsfield numbers varied within a range of 8.9 HU for urethane foam and varied within 58.7 HU for polyurethane. The iodine measurements varied up to 37.9 HU for the lowest concentration. For the Philips system, Hounsfield numbers were relatively consistent but were higher for the “Detail” and “Lung Enhanced” filters, varying by 36.9 HU for PMMA and 15.9 HU for HDPE. Conclusion: Reconstruction filters can change the measured Hounsfield numbers of nodular objects, especially with detail-enhancing (sharpening) filters commonly used in lung imaging. Measured values should only be used for diagnostic decision support with filters that have demonstrated accuracy and consistency. While filter accuracy statements are available from manufacturers, radiologists are likely not aware of the extent of potential variations that can occur in a clinical setting.« less

3D algebraic iterative reconstruction for cone-beam x-ray differential phase-contrast computed tomography.

PubMed

Fu, Jian; Hu, Xinhua; Velroyen, Astrid; Bech, Martin; Jiang, Ming; Pfeiffer, Franz

2015-01-01

Due to the potential of compact imaging systems with magnified spatial resolution and contrast, cone-beam x-ray differential phase-contrast computed tomography (DPC-CT) has attracted significant interest. The current proposed FDK reconstruction algorithm with the Hilbert imaginary filter will induce severe cone-beam artifacts when the cone-beam angle becomes large. In this paper, we propose an algebraic iterative reconstruction (AIR) method for cone-beam DPC-CT and report its experiment results. This approach considers the reconstruction process as the optimization of a discrete representation of the object function to satisfy a system of equations that describes the cone-beam DPC-CT imaging modality. Unlike the conventional iterative algorithms for absorption-based CT, it involves the derivative operation to the forward projections of the reconstructed intermediate image to take into account the differential nature of the DPC projections. This method is based on the algebraic reconstruction technique, reconstructs the image ray by ray, and is expected to provide better derivative estimates in iterations. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured with a three-grating interferometer and a mini-focus x-ray tube source. It is shown that the proposed method can reduce the cone-beam artifacts and performs better than FDK under large cone-beam angles. This algorithm is of interest for future cone-beam DPC-CT applications.

Non-contrast CT at comparable dose to an abdominal radiograph in patients with acute renal colic; impact of iterative reconstruction on image quality and diagnostic performance.

PubMed

McLaughlin, P D; Murphy, K P; Hayes, S A; Carey, K; Sammon, J; Crush, L; O'Neill, F; Normoyle, B; McGarrigle, A M; Barry, J E; Maher, M M

2014-04-01

The aim was to assess the performance of low-dose non-contrast CT of the urinary tract (LD-CT) acquired at radiation exposures close to that of abdominal radiography using adaptive statistical iterative reconstruction (ASiR). Thirty-three patients with clinically suspected renal colic were prospectively included. Conventional dose (CD-CT) and LD-CT data sets were contemporaneously acquired. LD-CT images were reconstructed with 40 %, 70 % and 90 % ASiR. Image quality was subjectively and objectively measured. Images were also clinically interpreted. Mean ED was 0.48 ± 0.07 mSv for LD-CT compared with 4.43 ± 3.14 mSv for CD-CT. Increasing the percentage ASiR resulted in a step-wise reduction in mean objective noise (p < 0.001 for all comparisons). Seventy % ASiR LD-CT images had higher diagnostic acceptability and spatial resolution than 90 % ASiR LD-CT images (p < 0.001). Twenty-seven calculi (diameter = 5.5 ± 1.7 mm), including all ureteric stones, were correctly identified using 70 % ASiR LD-CT with two false positives and 16 false negatives (diameter = 2.3 ± 0.7 mm) equating to a sensitivity and specificity of 72 % and 94 %. Seventy % ASiR LD-CT had a sensitivity and specificity of 87 % and 100 % for detection of calculi >3 mm. Reconstruction of LD-CT images with 70 % ASiR resulted in superior image quality than FBP, 40 % ASIR and 90 % ASIR. LD-CT with ASIR demonstrates high sensitivity and specificity for detection of calculi >3 mm. • Low-dose CT studies for urinary calculus detection were performed with a mean dose of 0.48 ± 0.07 mSv • Low-dose CT with 70 % ASiR detected calculi >3 mm with a sensitivity and specificity of 87 % and 100 % • Reconstruction with 70 % ASiR was superior to filtered back projection, 40 % ASiR and 90 % ASiR images.

Contrast adaptive total p-norm variation minimization approach to CT reconstruction for artifact reduction in reduced-view brain perfusion CT

NASA Astrophysics Data System (ADS)

Kim, Chang-Won; Kim, Jong-Hyo

2011-03-01

Perfusion CT (PCT) examinations are getting more frequently used for diagnosis of acute brain diseases such as hemorrhage and infarction, because the functional map images it produces such as regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), and mean transit time (MTT) may provide critical information in the emergency work-up of patient care. However, a typical PCT scans the same slices several tens of times after injection of contrast agent, which leads to much increased radiation dose and is inevitability of growing concern for radiation-induced cancer risk. Reducing the number of views in projection in combination of TV minimization reconstruction technique is being regarded as an option for radiation reduction. However, reconstruction artifacts due to insufficient number of X-ray projections become problematic especially when high contrast enhancement signals are present or patient's motion occurred. In this study, we present a novel reconstruction technique using contrast-adaptive TpV minimization that can reduce reconstruction artifacts effectively by using different p-norms in high contrast and low contrast objects. In the proposed method, high contrast components are first reconstructed using thresholded projection data and low p-norm total variation to reflect sparseness in both projection and reconstruction spaces. Next, projection data are modified to contain only low contrast objects by creating projection data of reconstructed high contrast components and subtracting them from original projection data. Then, the low contrast projection data are reconstructed by using relatively high p-norm TV minimization technique, and are combined with the reconstructed high contrast component images to produce final reconstructed images. The proposed algorithm was applied to numerical phantom and a clinical data set of brain PCT exam, and the resultant images were compared with those using filtered back projection (FBP) and conventional TV

Monoenergetic reconstructions for imaging of coronary artery stents using spectral detector CT: In-vitro experience and comparison to conventional images.

PubMed

Hickethier, Tilman; Baeßler, Bettina; Kroeger, Jan Robert; Doerner, Jonas; Pahn, Gregor; Maintz, David; Michels, Guido; Bunck, Alexander C

Accurate assessment of coronary stents using non-invasive CT imaging remains challenging despite new stent materials and improvements in CT technology. Virtual monoenergetic (monoE) images reconstructed from dual energy CT acquisitions potentially decrease artifacts caused by coronary stents. A novel spectral detector technology provides monoE and conventional images simultaneously for all conducted scans. The purpose of our study was to systematically investigate the influence of different monoE reconstructions on the visualization of coronary stent lumen in comparison to conventional images. Ten different coronary stents (diameter 3.0 mm) embedded in plastic tubes filled with contrast agent (500 HU) were scanned with a 128-row spectral detector CT (IQon, Philips, 120 kV, 125 mAs). Images were reconstructed (0.67 mm slice thickness, 0.35 mm increment) with a stent-specific conventional reconstruction kernel and 6 different monoE settings (60, 70, 80, 90, 100, 150 keV). Image quality for each stent and reconstruction was quantified using established parameters: image noise (standard deviation (SD) within a standardized ROI), in-stent attenuation difference (mean attenuation difference between stented and non-stented lumen) and visible lumen diameter (mean visible diameter of the stented tube). Image noise was significantly lower in all monoE data dets compared to conventional images (conventional: 13.41, 60 keV: 11.62, 70 keV: 11.67, 80 keV: 11.69, 90 keV: 11.71, 100 keV: 11.75, 150 keV: 11.80 HU SD; p < 0.01). The in-stent attenuation difference was significantly smaller in monoE data with higher keV levels than in conventional images (conventional: 148.18, 60 keV: 154.13 p = 0.036, 70 keV: 143.43 p = 0.109, 80 keV: 137.25 p = 0.052, 90 keV: 133.02 p = 0.043, 100 keV: 130.12 p = 0.039, 150 keV: 123.99 HU p = 0.035). The visible lumen diameter was significantly greater in monoE data with higher keV levels than in conventional images

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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 metricmore » 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

Modeling of polychromatic attenuation using computed tomography reconstructed images

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

1999-01-01

This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.

Task-based optimization of image reconstruction in breast CT

NASA Astrophysics Data System (ADS)

Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

2014-03-01

We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

Estimating radiation risk induced by CT screening for Korean population

NASA Astrophysics Data System (ADS)

Yang, Won Seok; Yang, Hye Jeong; Min, Byung In

2017-02-01

The purposes of this study are to estimate the radiation risks induced by chest/abdomen computed tomography (CT) screening for healthcare and to determine the cancer risk level of the Korean population compared to other populations. We used an ImPACT CT Patient Dosimetry Calculator to compute the organ effective dose induced by CT screening (chest, low-dose chest, abdomen/pelvis, and chest/abdomen/pelvis CT). A risk model was applied using principles based on the BEIR VII Report in order to estimate the lifetime attributable risk (LAR) using the Korean Life Table 2010. In addition, several countries including Hong Kong, the United States (U.S.), and the United Kingdom, were selected for comparison. Herein, each population exposed radiation dose of 100 mSv was classified according to country, gender and age. For each CT screening the total organ effective dose calculated by ImPACT was 6.2, 1.5, 5.2 and 11.4 mSv, respectively. In the case of Korean female LAR, it was similar to Hong Kong female but lower than those of U.S. and U.K. females, except for those in their twenties. The LAR of Korean males was the highest for all types of CT screening. However, the difference of the risk level was negligible because of the quite low value.

Born iterative reconstruction using perturbed-phase field estimates.

PubMed

Astheimer, Jeffrey P; Waag, Robert C

2008-10-01

A method of image reconstruction from scattering measurements for use in ultrasonic imaging is presented. The method employs distorted-wave Born iteration but does not require using a forward-problem solver or solving large systems of equations. These calculations are avoided by limiting intermediate estimates of medium variations to smooth functions in which the propagated fields can be approximated by phase perturbations derived from variations in a geometric path along rays. The reconstruction itself is formed by a modification of the filtered-backpropagation formula that includes correction terms to account for propagation through an estimated background. Numerical studies that validate the method for parameter ranges of interest in medical applications are presented. The efficiency of this method offers the possibility of real-time imaging from scattering measurements.

SU-F-207-02: Use of Postmortem Subjects for Subjective Image Quality Assessment in Abdominal CT Protocols with Iterative Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mench, A; Lipnharski, I; Carranza, C

Purpose: New radiation dose reduction technologies are emerging constantly in the medical imaging field. The latest of these technologies, iterative reconstruction (IR) in CT, presents the ability to reduce dose significantly and hence provides great opportunity for CT protocol optimization. However, without effective analysis of image quality, the reduction in radiation exposure becomes irrelevant. This work explores the use of postmortem subjects as an image quality assessment medium for protocol optimizations in abdominal CT. Methods: Three female postmortem subjects were scanned using the Abdomen-Pelvis (AP) protocol at reduced minimum tube current and target noise index (SD) settings of 12.5, 17.5,more » 20.0, and 25.0. Images were reconstructed using two strengths of iterative reconstruction. Radiologists and radiology residents from several subspecialties were asked to evaluate 8 AP image sets including the current facility default scan protocol and 7 scans with the parameters varied as listed above. Images were viewed in the soft tissue window and scored on a 3-point scale as acceptable, borderline acceptable, and unacceptable for diagnosis. The facility default AP scan was identified to the reviewer while the 7 remaining AP scans were randomized and de-identified of acquisition and reconstruction details. The observers were also asked to comment on the subjective image quality criteria they used for scoring images. This included visibility of specific anatomical structures and tissue textures. Results: Radiologists scored images as acceptable or borderline acceptable for target noise index settings of up to 20. Due to the postmortem subjects’ close representation of living human anatomy, readers were able to evaluate images as they would those of actual patients. Conclusion: Postmortem subjects have already been proven useful for direct CT organ dose measurements. This work illustrates the validity of their use for the crucial evaluation of image

Task-based image quality evaluation of iterative reconstruction methods for low dose CT using computer simulations

NASA Astrophysics Data System (ADS)

Xu, Jingyan; Fuld, Matthew K.; Fung, George S. K.; Tsui, Benjamin M. W.

2015-04-01

Iterative reconstruction (IR) methods for x-ray CT is a promising approach to improve image quality or reduce radiation dose to patients. The goal of this work was to use task based image quality measures and the channelized Hotelling observer (CHO) to evaluate both analytic and IR methods for clinical x-ray CT applications. We performed realistic computer simulations at five radiation dose levels, from a clinical reference low dose D0 to 25% D0. A fixed size and contrast lesion was inserted at different locations into the liver of the XCAT phantom to simulate a weak signal. The simulated data were reconstructed on a commercial CT scanner (SOMATOM Definition Flash; Siemens, Forchheim, Germany) using the vendor-provided analytic (WFBP) and IR (SAFIRE) methods. The reconstructed images were analyzed by CHOs with both rotationally symmetric (RS) and rotationally oriented (RO) channels, and with different numbers of lesion locations (5, 10, and 20) in a signal known exactly (SKE), background known exactly but variable (BKEV) detection task. The area under the receiver operating characteristic curve (AUC) was used as a summary measure to compare the IR and analytic methods; the AUC was also used as the equal performance criterion to derive the potential dose reduction factor of IR. In general, there was a good agreement in the relative AUC values of different reconstruction methods using CHOs with RS and RO channels, although the CHO with RO channels achieved higher AUCs than RS channels. The improvement of IR over analytic methods depends on the dose level. The reference dose level D0 was based on a clinical low dose protocol, lower than the standard dose due to the use of IR methods. At 75% D0, the performance improvement was statistically significant (p < 0.05). The potential dose reduction factor also depended on the detection task. For the SKE/BKEV task involving 10 lesion locations, a dose reduction of at least 25% from D0 was achieved.

Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.

PubMed

Solomon, Justin; Mileto, Achille; Nelson, Rendon C; Roy Choudhury, Kingshuk; Samei, Ehsan

2016-04-01

To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT). Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features. Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

2015-01-01

To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024). Subjective image quality improved with increasing IR levels. Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers.

PubMed

Bellesi, Luca; Wyttenbach, Rolf; Gaudino, Diego; Colleoni, Paolo; Pupillo, Francesco; Carrara, Mauro; Braghetti, Antonio; Puligheddu, Carla; Presilla, Stefano

2017-01-01

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images. Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

Image reconstruction in cone-beam CT with a spherical detector using the BPF algorithm

NASA Astrophysics Data System (ADS)

Zuo, Nianming; Zou, Yu; Jiang, Tianzi; Pan, Xiaochuan

2006-03-01

Both flat-panel detectors and cylindrical detectors have been used in CT systems for data acquisition. The cylindrical detector generally offers a sampling of a transverse image plane more uniformly than does a flat-panel detector. However, in the longitudinal dimension, the cylindrical and flat-panel detectors offer similar sampling of the image space. In this work, we investigate a detector of spherical shape, which can yield uniform sampling of the 3D image space because the solid angle subtended by each individual detector bin remains unchanged. We have extended the backprojection-filtration (BPF) algorithm, which we have developed previously for cone-beam CT, to reconstruct images in cone-beam CT with a spherical detector. We also conduct computer-simulation studies to validate the extended BPF algorithm. Quantitative results in these numerical studies indicate that accurate images can be obtained from data acquired with a spherical detector by use of our extended BPF cone-beam algorithms.

A feature refinement approach for statistical interior CT reconstruction

NASA Astrophysics Data System (ADS)

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-01

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

A feature refinement approach for statistical interior CT reconstruction.

PubMed

Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

2016-07-21

Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

Low-dose CT reconstruction via L1 dictionary learning regularization using iteratively reweighted least-squares.

PubMed

Zhang, Cheng; Zhang, Tao; Li, Ming; Peng, Chengtao; Liu, Zhaobang; Zheng, Jian

2016-06-18

In order to reduce the radiation dose of CT (computed tomography), compressed sensing theory has been a hot topic since it provides the possibility of a high quality recovery from the sparse sampling data. Recently, the algorithm based on DL (dictionary learning) was developed to deal with the sparse CT reconstruction problem. However, the existing DL algorithm focuses on the minimization problem with the L2-norm regularization term, which leads to reconstruction quality deteriorating while the sampling rate declines further. Therefore, it is essential to improve the DL method to meet the demand of more dose reduction. In this paper, we replaced the L2-norm regularization term with the L1-norm one. It is expected that the proposed L1-DL method could alleviate the over-smoothing effect of the L2-minimization and reserve more image details. The proposed algorithm solves the L1-minimization problem by a weighting strategy, solving the new weighted L2-minimization problem based on IRLS (iteratively reweighted least squares). Through the numerical simulation, the proposed algorithm is compared with the existing DL method (adaptive dictionary based statistical iterative reconstruction, ADSIR) and other two typical compressed sensing algorithms. It is revealed that the proposed algorithm is more accurate than the other algorithms especially when further reducing the sampling rate or increasing the noise. The proposed L1-DL algorithm can utilize more prior information of image sparsity than ADSIR. By transforming the L2-norm regularization term of ADSIR with the L1-norm one and solving the L1-minimization problem by IRLS strategy, L1-DL could reconstruct the image more exactly.

Feasibility of dual-low scheme combined with iterative reconstruction technique in acute cerebral infarction volume CT whole brain perfusion imaging.

PubMed

Wang, Tao; Gong, Yi; Shi, Yibing; Hua, Rong; Zhang, Qingshan

2017-07-01

The feasibility of application of low-concentration contrast agent and low tube voltage combined with iterative reconstruction in whole brain computed tomography perfusion (CTP) imaging of patients with acute cerebral infarction was investigated. Fifty-nine patients who underwent whole brain CTP examination and diagnosed with acute cerebral infarction from September 2014 to March 2016 were selected. Patients were randomly divided into groups A and B. There were 28 cases in group A [tube voltage, 100 kV; contrast agent, iohexol (350 mg I/ml), reconstructed by filtered back projection] and 31 cases in group B [tube voltage, 80 kV; contrast agent, iodixanol (270 mg I/ml), reconstructed by algebraic reconstruction technique]. The artery CT value, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), dose length product, effective dose (ED) of radiation and brain iodine intake of both groups were measured and statistically analyzed. Two physicians carried out kappa (κ) analysis on the consistency of image quality evaluation. The difference in subjective image quality evaluation between the groups was tested by χ 2 . The differences in CT value, SNR, CNR, CTP and CT angiography subjective image quality evaluation between both groups were not statistically significant (P>0.05); the diagnosis rate of the acute infarcts between the two groups was not significantly different; while the ED and iodine intake in group B (dual low-dose group) were lower than group A. In conclusion, combination of low tube voltage and iterative reconstruction technique, and application of low-concentration contrast agent (270 mg I/ml) in whole brain CTP examination reduced ED and iodine intake without compromising image quality, thereby reducing the risk of contrast-induced nephropathy.

Update on orbital reconstruction.

PubMed

Chen, Chien-Tzung; Chen, Yu-Ray

2010-08-01

Orbital trauma is common and frequently complicated by ocular injuries. The recent literature on orbital fracture is analyzed with emphasis on epidemiological data assessment, surgical timing, method of approach and reconstruction materials. Computed tomographic (CT) scan has become a routine evaluation tool for orbital trauma, and mobile CT can be applied intraoperatively if necessary. Concomitant serious ocular injury should be carefully evaluated preoperatively. Patients presenting with nonresolving oculocardiac reflex, 'white-eyed' blowout fracture, or diplopia with a positive forced duction test and CT evidence of orbital tissue entrapment require early surgical repair. Otherwise, enophthalmos can be corrected by late surgery with a similar outcome to early surgery. The use of an endoscope-assisted approach for orbital reconstruction continues to grow, offering an alternative method. Advances in alloplastic materials have improved surgical outcome and shortened operating time. In this review of modern orbital reconstruction, several controversial issues such as surgical indication, surgical timing, method of approach and choice of reconstruction material are discussed. Preoperative fine-cut CT image and thorough ophthalmologic examination are key elements to determine surgical indications. The choice of surgical approach and reconstruction materials much depends on the surgeon's experience and the reconstruction area. Prefabricated alloplastic implants together with image software and stereolithographic models are significant advances that help to more accurately reconstruct the traumatized orbit. The recent evolution of orbit reconstruction improves functional and aesthetic results and minimizes surgical complications.

Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness

PubMed Central

2015-01-01

Background Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of species richness estimation ride on the assumption that the reads in each assembled contig correspond to only one of the microbial genomes in the population. This assumption and the underlying probabilistic formulations of existing methods are not useful for quasispecies populations where the strains are highly genetically related. The lack of knowledge on the number of different strains in a quasispecies population is observed to hinder the precision of existing Viral Quasispecies Spectrum Reconstruction (QSR) methods due to the uncontrolled reconstruction of a large number of in silico false positives. In this work, we formulated a novel probabilistic method for strain richness estimation specifically targeting viral quasispecies. By using this approach we improved our recently proposed spectrum reconstruction pipeline ViQuaS to achieve higher levels of precision in reconstructed quasispecies spectra without compromising the recall rates. We also discuss how one other existing popular QSR method named ShoRAH can be improved using this new approach. Results On benchmark data sets, our estimation method provided accurate richness estimates (< 0.2 median estimation error) and improved the precision of ViQuaS by 2%-13% and F-score by 1%-9% without compromising the recall rates. We also demonstrate that our estimation method can be used to improve the precision and F-score of ShoRAH by 0%-7% and 0%-5% respectively. Conclusions The proposed probabilistic estimation method can be used to estimate the richness of viral populations with a quasispecies behavior and to improve the accuracy of the quasispecies spectra reconstructed by the existing methods ViQuaS and ShoRAH in the presence of a moderate level of technical sequencing errors. Availability http://sourceforge.net/projects/viquas/ PMID:26678073

Born iterative reconstruction using perturbed-phase field estimates

PubMed Central

Astheimer, Jeffrey P.; Waag, Robert C.

2008-01-01

A method of image reconstruction from scattering measurements for use in ultrasonic imaging is presented. The method employs distorted-wave Born iteration but does not require using a forward-problem solver or solving large systems of equations. These calculations are avoided by limiting intermediate estimates of medium variations to smooth functions in which the propagated fields can be approximated by phase perturbations derived from variations in a geometric path along rays. The reconstruction itself is formed by a modification of the filtered-backpropagation formula that includes correction terms to account for propagation through an estimated background. Numerical studies that validate the method for parameter ranges of interest in medical applications are presented. The efficiency of this method offers the possibility of real-time imaging from scattering measurements. PMID:19062873

Estimation of feline renal volume using computed tomography and ultrasound.

PubMed

Tyson, Reid; Logsdon, Stacy A; Werre, Stephen R; Daniel, Gregory B

2013-01-01

Renal volume estimation is an important parameter for clinical evaluation of kidneys and research applications. A time efficient, repeatable, and accurate method for volume estimation is required. The purpose of this study was to describe the accuracy of ultrasound and computed tomography (CT) for estimating feline renal volume. Standardized ultrasound and CT scans were acquired for kidneys of 12 cadaver cats, in situ. Ultrasound and CT multiplanar reconstructions were used to record renal length measurements that were then used to calculate volume using the prolate ellipsoid formula for volume estimation. In addition, CT studies were reconstructed at 1 mm, 5 mm, and 1 cm, and transferred to a workstation where the renal volume was calculated using the voxel count method (hand drawn regions of interest). The reference standard kidney volume was then determined ex vivo using water displacement with the Archimedes' principle. Ultrasound measurement of renal length accounted for approximately 87% of the variability in renal volume for the study population. The prolate ellipsoid formula exhibited proportional bias and underestimated renal volume by a median of 18.9%. Computed tomography volume estimates using the voxel count method with hand-traced regions of interest provided the most accurate results, with increasing accuracy for smaller voxel sizes in grossly normal kidneys (-10.1 to 0.6%). Findings from this study supported the use of CT and the voxel count method for estimating feline renal volume in future clinical and research studies. © 2012 Veterinary Radiology & Ultrasound.

Evaluation of the resolving potency of a novel reconstruction filter on periodontal ligament space with dental cone-beam CT: a quantitative phantom study

NASA Astrophysics Data System (ADS)

Houno, Yuuki; Hishikawa, Toshimitsu; Gotoh, Ken-ichi; Naitoh, Munetaka; Ariji, Eiichiro; Kodera, Yoshie

2014-03-01

Diagnosis of the alveolar bone condition is important for the treatment planning of periodontal disease. Especially the determination of periodontal ligament space is the most important remark because it represents the periodontal tissue support for tooth retention. However, owing to the image blur of the current cone-beam CT (CBCT) imaging technique, the periodontal ligament space is difficult to visualize. In this study, we developed an original periodontal ligament phantom (PLP) and evaluated the image quality of simulated periodontal ligament space using a novel reconstruction filter for CBCT that emphasized high frequency component. PLP was composed from two resin blocks of different materials, the bone equivalent block and the dentine equivalent block. They were assembled to make continuously changing space from 0.0 to 1.0 millimeter that mimics periodontal ligament space. PLP was placed in water and the image was obtained by using Alphard-3030 dental cone-beam CT (Asahi Roentgen Industry Co., Ltd.). Then we reconstructed the projection data with a novel reconstruction filter. The axial images were compared with conventional reconstructed images. In novel filter reconstruction images, 0.4 millimeter of the space width was steadily detected by calculation of pixel value, on the other hand 0.6 millimeter was in conventional images. With our method, the resolving potency of conebeam CT images was improved.

Technical Note: FreeCT_wFBP: A robust, efficient, open-source implementation of weighted filtered backprojection for helical, fan-beam CT.

PubMed

Hoffman, John; Young, Stefano; Noo, Frédéric; McNitt-Gray, Michael

2016-03-01

With growing interest in quantitative imaging, radiomics, and CAD using CT imaging, the need to explore the impacts of acquisition and reconstruction parameters has grown. This usually requires extensive access to the scanner on which the data were acquired and its workflow is not designed for large-scale reconstruction projects. Therefore, the authors have developed a freely available, open-source software package implementing a common reconstruction method, weighted filtered backprojection (wFBP), for helical fan-beam CT applications. FreeCT_wFBP is a low-dependency, GPU-based reconstruction program utilizing c for the host code and Nvidia CUDA C for GPU code. The software is capable of reconstructing helical scans acquired with arbitrary pitch-values, and sampling techniques such as flying focal spots and a quarter-detector offset. In this work, the software has been described and evaluated for reconstruction speed, image quality, and accuracy. Speed was evaluated based on acquisitions of the ACR CT accreditation phantom under four different flying focal spot configurations. Image quality was assessed using the same phantom by evaluating CT number accuracy, uniformity, and contrast to noise ratio (CNR). Finally, reconstructed mass-attenuation coefficient accuracy was evaluated using a simulated scan of a FORBILD thorax phantom and comparing reconstructed values to the known phantom values. The average reconstruction time evaluated under all flying focal spot configurations was found to be 17.4 ± 1.0 s for a 512 row × 512 column × 32 slice volume. Reconstructions of the ACR phantom were found to meet all CT Accreditation Program criteria including CT number, CNR, and uniformity tests. Finally, reconstructed mass-attenuation coefficient values of water within the FORBILD thorax phantom agreed with original phantom values to within 0.0001 mm(2)/g (0.01%). FreeCT_wFBP is a fast, highly configurable reconstruction package for third-generation CT available under

Improved Range Estimation Model for Three-Dimensional (3D) Range Gated Reconstruction

PubMed Central

Chua, Sing Yee; Guo, Ningqun; Tan, Ching Seong; Wang, Xin

2017-01-01

Accuracy is an important measure of system performance and remains a challenge in 3D range gated reconstruction despite the advancement in laser and sensor technology. The weighted average model that is commonly used for range estimation is heavily influenced by the intensity variation due to various factors. Accuracy improvement in term of range estimation is therefore important to fully optimise the system performance. In this paper, a 3D range gated reconstruction model is derived based on the operating principles of range gated imaging and time slicing reconstruction, fundamental of radiant energy, Laser Detection And Ranging (LADAR), and Bidirectional Reflection Distribution Function (BRDF). Accordingly, a new range estimation model is proposed to alleviate the effects induced by distance, target reflection, and range distortion. From the experimental results, the proposed model outperforms the conventional weighted average model to improve the range estimation for better 3D reconstruction. The outcome demonstrated is of interest to various laser ranging applications and can be a reference for future works. PMID:28872589

Simultaneous reconstruction of emission activity and attenuation coefficient distribution from TOF data, acquired with external transmission source

NASA Astrophysics Data System (ADS)

Panin, V. Y.; Aykac, M.; Casey, M. E.

2013-06-01

The simultaneous PET data reconstruction of emission activity and attenuation coefficient distribution is presented, where the attenuation image is constrained by exploiting an external transmission source. Data are acquired in time-of-flight (TOF) mode, allowing in principle for separation of emission and transmission data. Nevertheless, here all data are reconstructed at once, eliminating the need to trace the position of the transmission source in sinogram space. Contamination of emission data by the transmission source and vice versa is naturally modeled. Attenuated emission activity data also provide additional information about object attenuation coefficient values. The algorithm alternates between attenuation and emission activity image updates. We also proposed a method of estimation of spatial scatter distribution from the transmission source by incorporating knowledge about the expected range of attenuation map values. The reconstruction of experimental data from the Siemens mCT scanner suggests that simultaneous reconstruction improves attenuation map image quality, as compared to when data are separated. In the presented example, the attenuation map image noise was reduced and non-uniformity artifacts that occurred due to scatter estimation were suppressed. On the other hand, the use of transmission data stabilizes attenuation coefficient distribution reconstruction from TOF emission data alone. The example of improving emission images by refining a CT-based patient attenuation map is presented, revealing potential benefits of simultaneous CT and PET data reconstruction.

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

NASA Astrophysics Data System (ADS)

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.

Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose

PubMed Central

Wenz, Holger; Maros, Máté E.; Meyer, Mathias; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O.; Flohr, Thomas; Leidecker, Christianne; Groden, Christoph; Scharf, Johann; Henzler, Thomas

2015-01-01

Objectives To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT) spiral cranial CT (cCT) to a sequential 4-slice Multi-Slice-CT (MSCT) while maintaining identical intra-individual radiation dose levels. Methods 35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP) and 3rd-generation iterative reconstruction (IR) algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR) being subsequently calculated. Results Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05). Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024). Subjective image quality improved with increasing IR levels. Conclusion Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels. PMID:26288186

Image quality comparison of two adaptive statistical iterative reconstruction (ASiR, ASiR-V) algorithms and filtered back projection in routine liver CT.

PubMed

Chen, Li-Hong; Jin, Chao; Li, Jian-Ying; Wang, Ge-Liang; Jia, Yong-Jun; Duan, Hai-Feng; Pan, Ning; Guo, Jianxin

2018-06-06

To compare image quality of two adaptive statistical iterative reconstruction (ASiR and ASiR-V) algorithms using objective and subjective metrics for routine liver CT, with the conventional filtered back projection (FBP) reconstructions as reference standards. This institutional review board-approved study included 52 patients with clinically suspected hepatic metastases. Patients were divided equally into ASiR and ASiR-V groups with same scan parameters. Images were reconstructed with ASiR and ASiR-V from 0 (FBP) to 100% blending percentages at 10% interval in its respective group. Mean and standard deviation of CT numbers for liver parenchyma were recorded. Two experienced radiologists reviewed all images for image quality blindly and independently. Data were statistically analyzed. There was no difference in CT dose index between ASiR and ASiR-V groups. As the percentage of ASiR and ASiR-V increased from 10 to 100% , image noise reduced by 8.6 -57.9% and 8.9-81.6%, respectively, compared with FBP. There was substantial interobserver agreement in image quality assessment for ASiR and ASiR-V images. Compared with FBP reconstruction, subjective image quality scores of ASiR and ASiR-V improved significantly as percentage increased from 10 to 80% for ASiR (peaked at 50% with 32.2% noise reduction) and from 10 to 90% (peaked at 60% with 51.5% noise reduction) for ASiR-V. Both ASiR and ASiR-V improved the objective and subjective image quality for routine liver CT compared with FBP. ASiR-V provided further image quality improvement with higher acceptable percentage than ASiR, and ASiR-V60% had the highest image quality score. Advances in knowledge: (1) Both ASiR and ASiR-V significantly reduce image noise compared with conventional FBP reconstruction. (2) ASiR-V with 60 blending percentage provides the highest image quality score in routine liver CT.

A validated methodology for the 3D reconstruction of cochlea geometries using human microCT images

NASA Astrophysics Data System (ADS)

Sakellarios, A. I.; Tachos, N. S.; Rigas, G.; Bibas, T.; Ni, G.; Böhnke, F.; Fotiadis, D. I.

2017-05-01

Accurate reconstruction of the inner ear is a prerequisite for the modelling and understanding of the inner ear mechanics. In this study, we present a semi-automated methodology for accurate reconstruction of the major inner ear structures (scalae, basilar membrane, stapes and semicircular canals). For this purpose, high resolution microCT images of a human specimen were used. The segmentation methodology is based on an iterative level set algorithm which provides the borders of the structures of interest. An enhanced coupled level set method which allows the simultaneous multiple image labeling without any overlapping regions has been developed for this purpose. The marching cube algorithm was applied in order to extract the surface from the segmented volume. The reconstructed geometries are then post-processed to improve the basilar membrane geometry to realistically represent physiologic dimensions. The final reconstructed model is compared to the available data from the literature. The results show that our generated inner ear structures are in good agreement with the published ones, while our approach is the most realistic in terms of the basilar membrane thickness and width reconstruction.

Convolution-based estimation of organ dose in tube current modulated CT

NASA Astrophysics Data System (ADS)

Tian, Xiaoyu; Segars, W. Paul; Dixon, Robert L.; Samei, Ehsan

2016-05-01

Estimating organ dose for clinical patients requires accurate modeling of the patient anatomy and the dose field of the CT exam. The modeling of patient anatomy can be achieved using a library of representative computational phantoms (Samei et al 2014 Pediatr. Radiol. 44 460-7). The modeling of the dose field can be challenging for CT exams performed with a tube current modulation (TCM) technique. The purpose of this work was to effectively model the dose field for TCM exams using a convolution-based method. A framework was further proposed for prospective and retrospective organ dose estimation in clinical practice. The study included 60 adult patients (age range: 18-70 years, weight range: 60-180 kg). Patient-specific computational phantoms were generated based on patient CT image datasets. A previously validated Monte Carlo simulation program was used to model a clinical CT scanner (SOMATOM Definition Flash, Siemens Healthcare, Forchheim, Germany). A practical strategy was developed to achieve real-time organ dose estimation for a given clinical patient. CTDIvol-normalized organ dose coefficients ({{h}\\text{Organ}} ) under constant tube current were estimated and modeled as a function of patient size. Each clinical patient in the library was optimally matched to another computational phantom to obtain a representation of organ location/distribution. The patient organ distribution was convolved with a dose distribution profile to generate {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} values that quantified the regional dose field for each organ. The organ dose was estimated by multiplying {{≤ft(\\text{CTD}{{\\text{I}}\\text{vol}}\\right)}\\text{organ, \\text{convolution}}} with the organ dose coefficients ({{h}\\text{Organ}} ). To validate the accuracy of this dose estimation technique, the organ dose of the original clinical patient was estimated using Monte Carlo program with TCM profiles explicitly modeled. The

Analysis of metal artifact reduction tools for dental hardware in CT scans of the oral cavity: kVp, iterative reconstruction, dual-energy CT, metal artifact reduction software: does it make a difference?

PubMed

De Crop, An; Casselman, Jan; Van Hoof, Tom; Dierens, Melissa; Vereecke, Elke; Bossu, Nicolas; Pamplona, Jaime; D'Herde, Katharina; Thierens, Hubert; Bacher, Klaus

2015-08-01

Metal artifacts may negatively affect radiologic assessment in the oral cavity. The aim of this study was to evaluate different metal artifact reduction techniques for metal artifacts induced by dental hardware in CT scans of the oral cavity. Clinical image quality was assessed using a Thiel-embalmed cadaver. A Catphan phantom and a polymethylmethacrylate (PMMA) phantom were used to evaluate physical-technical image quality parameters such as artifact area, artifact index (AI), and contrast detail (IQFinv). Metal cylinders were inserted in each phantom to create metal artifacts. CT images of both phantoms and the Thiel-embalmed cadaver were acquired on a multislice CT scanner using 80, 100, 120, and 140 kVp; model-based iterative reconstruction (Veo); and synthesized monochromatic keV images with and without metal artifact reduction software (MARs). Four radiologists assessed the clinical image quality, using an image criteria score (ICS). Significant influence of increasing kVp and the use of Veo was found on clinical image quality (p = 0.007 and p = 0.014, respectively). Application of MARs resulted in a smaller artifact area (p < 0.05). However, MARs reconstructed images resulted in lower ICS. Of all investigated techniques, Veo shows to be most promising, with a significant improvement of both the clinical and physical-technical image quality without adversely affecting contrast detail. MARs reconstruction in CT images of the oral cavity to reduce dental hardware metallic artifacts is not sufficient and may even adversely influence the image quality.

Pseudo CT estimation from MRI using patch-based random forest

NASA Astrophysics Data System (ADS)

Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian

2017-02-01

Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.

Patient dose estimation from CT scans at the Mexican National Neurology and Neurosurgery Institute

NASA Astrophysics Data System (ADS)

Alva-Sánchez, Héctor; Reynoso-Mejía, Alberto; Casares-Cruz, Katiuzka; Taboada-Barajas, Jesús

2014-11-01

In the radiology department of the Mexican National Institute of Neurology and Neurosurgery, a dedicated institute in Mexico City, on average 19.3 computed tomography (CT) examinations are performed daily on hospitalized patients for neurological disease diagnosis, control scans and follow-up imaging. The purpose of this work was to estimate the effective dose received by hospitalized patients who underwent a diagnostic CT scan using typical effective dose values for all CT types and to obtain the estimated effective dose distributions received by surgical and non-surgical patients. Effective patient doses were estimated from values per study type reported in the applications guide provided by the scanner manufacturer. This retrospective study included all hospitalized patients who underwent a diagnostic CT scan between 1 January 2011 and 31 December 2012. A total of 8777 CT scans were performed in this two-year period. Simple brain scan was the CT type performed the most (74.3%) followed by contrasted brain scan (6.1%) and head angiotomography (5.7%). The average number of CT scans per patient was 2.83; the average effective dose per patient was 7.9 mSv; the mean estimated radiation dose was significantly higher for surgical (9.1 mSv) than non-surgical patients (6.0 mSv). Three percent of the patients had 10 or more brain CT scans and exceeded the organ radiation dose threshold set by the International Commission on Radiological Protection for deterministic effects of the eye-lens. Although radiation patient doses from CT scans were in general relatively low, 187 patients received a high effective dose (>20 mSv) and 3% might develop cataract from cumulative doses to the eye lens.

Impact of PET/CT system, reconstruction protocol, data analysis method, and repositioning on PET/CT precision: An experimental evaluation using an oncology and brain phantom.

PubMed

Mansor, Syahir; Pfaehler, Elisabeth; Heijtel, Dennis; Lodge, Martin A; Boellaard, Ronald; Yaqub, Maqsood

2017-12-01

In longitudinal oncological and brain PET/CT studies, it is important to understand the repeatability of quantitative PET metrics in order to assess change in tracer uptake. The present studies were performed in order to assess precision as function of PET/CT system, reconstruction protocol, analysis method, scan duration (or image noise), and repositioning in the field of view. Multiple (repeated) scans have been performed using a NEMA image quality (IQ) phantom and a 3D Hoffman brain phantom filled with 18 F solutions on two systems. Studies were performed with and without randomly (< 2 cm) repositioning the phantom and all scans (12 replicates for IQ phantom and 10 replicates for Hoffman brain phantom) were performed at equal count statistics. For the NEMA IQ phantom, we studied the recovery coefficients (RC) of the maximum (SUV max ), peak (SUV peak ), and mean (SUV mean ) uptake in each sphere as a function of experimental conditions (noise level, reconstruction settings, and phantom repositioning). For the 3D Hoffman phantom, the mean activity concentration was determined within several volumes of interest and activity recovery and its precision was studied as function of experimental conditions. The impact of phantom repositioning on RC precision was mainly seen on the Philips Ingenuity PET/CT, especially in the case of smaller spheres (< 17 mm diameter, P < 0.05). This effect was much smaller for the Siemens Biograph system. When exploring SUV max , SUV peak , or SUV mean of the spheres in the NEMA IQ phantom, it was observed that precision depended on phantom repositioning, reconstruction algorithm, and scan duration, with SUV max being most and SUV peak least sensitive to phantom repositioning. For the brain phantom, regional averaged SUVs were only minimally affected by phantom repositioning (< 2 cm). The precision of quantitative PET metrics depends on the combination of reconstruction protocol, data analysis methods and scan duration (scan

CT Evaluation of Small-Diameter Coronary Artery Stents: Effect of an Integrated Circuit Detector with Iterative Reconstruction.

PubMed

Geyer, Lucas L; Glenn, G Russell; De Cecco, Carlo Nicola; Van Horn, Mark; Canstein, Christian; Silverman, Justin R; Krazinski, Aleksander W; Kemper, Jenny M; Bucher, Andreas; Ebersberger, Ullrich; Costello, Philip; Bamberg, Fabian; Schoepf, U Joseph

2015-09-01

To use suitable objective methods of analysis to assess the influence of the combination of an integrated-circuit computed tomographic (CT) detector and iterative reconstruction (IR) algorithms on the visualization of small (≤3-mm) coronary artery stents. By using a moving heart phantom, 18 data sets obtained from three coronary artery stents with small diameters were investigated. A second-generation dual-source CT system equipped with an integrated-circuit detector was used. Images were reconstructed with filtered back-projection (FBP) and IR at a section thickness of 0.75 mm (FBP75 and IR75, respectively) and IR at a section thickness of 0.50 mm (IR50). Multirow intensity profiles in Hounsfield units were modeled by using a sum-of-Gaussians fit to analyze in-plane image characteristics. Out-of-plane image characteristics were analyzed with z upslope of multicolumn intensity profiles in Hounsfield units. Statistical analysis was conducted with one-way analysis of variance and the Student t test. Independent of stent diameter and heart rate, IR75 resulted in significantly increased xy sharpness, signal-to-noise ratio, and contrast-to-noise ratio, as well as decreased blurring and noise compared with FBP75 (eg, 2.25-mm stent, 0 beats per minute; xy sharpness, 278.2 vs 252.3; signal-to-noise ratio, 46.6 vs 33.5; contrast-to-noise ratio, 26.0 vs 16.8; blurring, 1.4 vs 1.5; noise, 15.4 vs 21.2; all P < .001). In the z direction, the upslopes were substantially higher in the IR50 reconstructions (2.25-mm stent: IR50, 94.0; IR75, 53.1; and FBP75, 48.1; P < .001). The implementation of an integrated-circuit CT detector provides substantially sharper out-of-plane resolution of coronary artery stents at 0.5-mm section thickness, while the use of iterative image reconstruction mostly improves in-plane stent visualization.

Soft-tissue imaging with C-arm cone-beam CT using statistical reconstruction

NASA Astrophysics Data System (ADS)

Wang, Adam S.; Webster Stayman, J.; Otake, Yoshito; Kleinszig, Gerhard; Vogt, Sebastian; Gallia, Gary L.; Khanna, A. Jay; Siewerdsen, Jeffrey H.

2014-02-01

The potential for statistical image reconstruction methods such as penalized-likelihood (PL) to improve C-arm cone-beam CT (CBCT) soft-tissue visualization for intraoperative imaging over conventional filtered backprojection (FBP) is assessed in this work by making a fair comparison in relation to soft-tissue performance. A prototype mobile C-arm was used to scan anthropomorphic head and abdomen phantoms as well as a cadaveric torso at doses substantially lower than typical values in diagnostic CT, and the effects of dose reduction via tube current reduction and sparse sampling were also compared. Matched spatial resolution between PL and FBP was determined by the edge spread function of low-contrast (˜40-80 HU) spheres in the phantoms, which were representative of soft-tissue imaging tasks. PL using the non-quadratic Huber penalty was found to substantially reduce noise relative to FBP, especially at lower spatial resolution where PL provides a contrast-to-noise ratio increase up to 1.4-2.2× over FBP at 50% dose reduction across all objects. Comparison of sampling strategies indicates that soft-tissue imaging benefits from fully sampled acquisitions at dose above ˜1.7 mGy and benefits from 50% sparsity at dose below ˜1.0 mGy. Therefore, an appropriate sampling strategy along with the improved low-contrast visualization offered by statistical reconstruction demonstrates the potential for extending intraoperative C-arm CBCT to applications in soft-tissue interventions in neurosurgery as well as thoracic and abdominal surgeries by overcoming conventional tradeoffs in noise, spatial resolution, and dose.

Reduction in radiation dose with reconstruction technique in the brain perfusion CT

NASA Astrophysics Data System (ADS)

Kim, H. J.; Lee, H. K.; Song, H.; Ju, M. S.; Dong, K. R.; Chung, W. K.; Cho, M. S.; Cho, J. H.

2011-12-01

The principal objective of this study was to verify the utility of the reconstruction imaging technique in the brain perfusion computed tomography (PCT) scan by assessing reductions in the radiation dose and analyzing the generated images. The setting used for image acquisition had a detector coverage of 40 mm, a helical thickness of 0.625 mm, a helical shuttle mode scan type and a rotation time of 0.5 s as the image parameters used for the brain PCT scan. Additionally, a phantom experiment and an animal experiment were carried out. In the phantom and animal experiments, noise was measured in the scanning with the tube voltage fixed at 80 kVp (kilovolt peak) and the level of the adaptive statistical iterative reconstruction (ASIR) was changed from 0% to 100% at 10% intervals. The standard deviation of the CT coefficient was measured three times to calculate the mean value. In the phantom and animal experiments, the absorbed dose was measured 10 times under the same conditions as the ones for noise measurement before the mean value was calculated. In the animal experiment, pencil-type and CT-dedicated ionization chambers were inserted into the central portion of pig heads for measurement. In the phantom study, as the level of the ASIR changed from 0% to 100% under identical scanning conditions, the noise value and dose were proportionally reduced. In our animal experiment, the noise value was lowest when the ASIR level was 50%, unlike in the phantom study. The dose was reduced as in the phantom study.

Feasibility Study of Radiation Dose Reduction in Adult Female Pelvic CT Scan with Low Tube-Voltage and Adaptive Statistical Iterative Reconstruction

PubMed Central

Wang, Xinlian; Chen, Jianghong; Hu, Zhihai; Zhao, Liqin

2015-01-01

Objective To evaluate image quality of female pelvic computed tomography (CT) scans reconstructed with the adaptive statistical iterative reconstruction (ASIR) technique combined with low tube-voltage and to explore the feasibility of its clinical application. Materials and Methods Ninety-four patients were divided into two groups. The study group used 100 kVp, and images were reconstructed with 30%, 50%, 70%, and 90% ASIR. The control group used 120 kVp, and images were reconstructed with 30% ASIR. The noise index was 15 for the study group and 11 for the control group. The CT values and noise levels of different tissues were measured. The contrast to noise ratio (CNR) was calculated. A subjective evaluation was carried out by two experienced radiologists. The CT dose index volume (CTDIvol) was recorded. Results A 44.7% reduction in CTDIvol was observed in the study group (8.18 ± 3.58 mGy) compared with that in the control group (14.78 ± 6.15 mGy). No significant differences were observed in the tissue noise levels and CNR values between the 70% ASIR group and the control group (p = 0.068-1.000). The subjective scores indicated that visibility of small structures, diagnostic confidence, and the overall image quality score in the 70% ASIR group was the best, and were similar to those in the control group (1.87 vs. 1.79, 1.26 vs. 1.28, and 4.53 vs. 4.57; p = 0.122-0.585). No significant difference in diagnostic accuracy was detected between the study group and the control group (42/47 vs. 43/47, p = 1.000). Conclusion Low tube-voltage combined with automatic tube current modulation and 70% ASIR allowed the low CT radiation dose to be reduced by 44.7% without losing image quality on female pelvic scan. PMID:26357499

Pre-operative CT angiography and three-dimensional image post processing for deep inferior epigastric perforator flap breast reconstructive surgery.

PubMed

Lam, D L; Mitsumori, L M; Neligan, P C; Warren, B H; Shuman, W P; Dubinsky, T J

2012-12-01

Autologous breast reconstructive surgery with deep inferior epigastric artery (DIEA) perforator flaps has become the mainstay for breast reconstructive surgery. CT angiography and three-dimensional image post processing can depict the number, size, course and location of the DIEA perforating arteries for the pre-operative selection of the best artery to use for the tissue flap. Knowledge of the location and selection of the optimal perforating artery shortens operative times and decreases patient morbidity.

A phantom-based JAFROC observer study of two CT reconstruction methods: the search for optimisation of lesion detection and effective dose

NASA Astrophysics Data System (ADS)

Thompson, John D.; Chakraborty, Dev P.; Szczepura, Katy; Vamvakas, Ioannis; Tootell, Andrew; Manning, David J.; Hogg, Peter

2015-03-01

Purpose: To investigate the dose saving potential of iterative reconstruction (IR) in a computed tomography (CT) examination of the thorax. Materials and Methods: An anthropomorphic chest phantom containing various configurations of simulated lesions (5, 8, 10 and 12mm; +100, -630 and -800 Hounsfield Units, HU) was imaged on a modern CT system over a tube current range (20, 40, 60 and 80mA). Images were reconstructed with (IR) and filtered back projection (FBP). An ATOM 701D (CIRS, Norfolk, VA) dosimetry phantom was used to measure organ dose. Effective dose was calculated. Eleven observers (15.11+/-8.75 years of experience) completed a free response study, localizing lesions in 544 single CT image slices. A modified jackknife alternative free-response receiver operating characteristic (JAFROC) analysis was completed to look for a significant effect of two factors: reconstruction method and tube current. Alpha was set at 0.05 to control the Type I error in this study. Results: For modified JAFROC analysis of reconstruction method there was no statistically significant difference in lesion detection performance between FBP and IR when figures-of-merit were averaged over tube current (F(1,10)=0.08, p = 0.789). For tube current analysis, significant differences were revealed between multiple pairs of tube current settings (F(3,10) = 16.96, p<0.001) when averaged over image reconstruction method. Conclusion: The free-response study suggests that lesion detection can be optimized at 40mA in this phantom model, a measured effective dose of 0.97mSv. In high-contrast regions the diagnostic value of IR, compared to FBP, is less clear.

Three-dimensional monochromatic x-ray CT

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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 (p<0.05). 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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Pulmonary nodules: effect of adaptive statistical iterative reconstruction (ASIR) technique on performance of a computer-aided detection (CAD) system-comparison of performance between different-dose CT scans.