Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Iterative”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-E-I-01: Iterative CBCT Reconstruction with a Feature-Preserving Penalty

Purpose: Low-dose CBCT is desired in various clinical applications. Iterative image reconstruction algorithms have shown advantages in suppressing noise in low-dose CBCT. However, due to the smoothness constraint enforced during the reconstruction process, edges may be blurred and image features may lose in the reconstructed image. In this work, we proposed a new penalty design to preserve image features in the image reconstructed by iterative algorithms. Methods: Low-dose CBCT is reconstructed by minimizing the penalized weighted least-squares (PWLS) objective function. Binary Robust Independent Elementary Features (BRIEF) of the image were integrated into the penalty of PWLS. BRIEF is a general purpose point descriptor that can be used to identify important features of an image. In this work, BRIEF distance of two neighboring pixels was used to weigh the smoothing parameter in PWLS. For pixels of large BRIEF distance, weaker smooth constraint will be enforced. Image features will be better preserved through such a design. The performance of the PWLS algorithm with BRIEF penalty was evaluated by a CatPhan 600 phantom. Results: The image quality reconstructed by the proposed PWLS-BRIEF algorithm is superior to that by the conventional PWLS method and the standard FDK method. At matched noise level, edges in PWLS-BRIEF reconstructed image are better preserved. Conclusion: This study demonstrated that the proposed PWLS-BRIEF algorithm has great potential on preserving image features in low-dose CBCT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-86: Ultra-Low Dose Computed Tomography Attenuation Correction for Pediatric PET CT Using Adaptive Statistical Iterative Reconstruction (ASiR™)

Purpose: To develop ultra-low 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 ultra-low doses (10–35 mAs). CT quantitation: noise, low-contrast resolution, and CT numbers for eleven tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% CTDIvol (0.39/3.64; mGy) radiation dose from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUVbw) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation organ dose, as derived from patient exam size specific dose estimate (SSDE), was converted to effective dose using the standard ICRP report 103 method. Effective dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative patient population dose reduction and noise control. Results: CT numbers were constant to within 10% from the non-dose reduced CTAC image down to 90% dose reduction. No change in SUVbw, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols reconstructed with ASiR and down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62%–86% (3.2/8.3−0.9/6.2; mSv). Noise magnitude in dose-reduced patient images increased but was not statistically different from pre dose-reduced patient images. Conclusion: Using ASiR allowed for aggressive reduction in CTAC dose with no change in PET reconstructed images while maintaining sufficient image quality for co-localization of hybrid CT anatomy and PET radioisotope uptake.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-69: Iterative Deconvolution of the Initial Photon Fluence for EPID Dosimetry: A Monte Carlo Based Study

Purpose: Developing a fast and accurate calculation model to reconstruct the applied photon fluence from an external photon radiation therapy treatment based on an image recorded by an electronic portal image device (EPID). Methods: To reconstruct the initial photon fluence the 2D EPID image was corrected for scatter from the patient/phantom and EPID to generate the transmitted primary photon fluence. This was done by an iterative deconvolution using precalculated point spread functions (PSF). The transmitted primary photon fluence was then backprojected through the patient/phantom geometry considering linear attenuation to receive the initial photon fluence applied for the treatment.The calculation model was verified using Monte Carlo simulations performed with the EGSnrc code system. EPID images were produced by calculating the dose deposition in the EPID from a 6 MV photon beam irradiating a water phantom with air and bone inhomogeneities and the ICRP anthropomorphic voxel phantom. Results: The initial photon fluence was reconstructed using a single PSF and position dependent PSFs which depend on the radiological thickness of the irradiated object. Appling position dependent point spread functions the mean uncertainty of the reconstructed initial photon fluence could be reduced from 1.13 % to 0.13 %. Conclusion: This study presents a calculation model for fluence reconstruction from EPID images. The{sup Result} show a clear advantage when position dependent PSF are used for the iterative reconstruction. The basic work of a reconstruction method was established and further evaluations must be made in an experimental study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-111: An Iterative Approach to Modelling Dosimetric Properties of a Varian MLC

Purpose: In effort to efficiently and accurately model MLC parameters for use in Varian Eclipse treatment planning system (TPS), an iterative technique for characterizing the dosimetric properties of MLCs has been developed. Methods: The initial characterization of the dosimetric leaf gap (DLG) and MLC transmission was performed using varied sizes of moving gaps and transmission measurements through central axis of the radiation beam. These values were determined during the initial data collection. After the initial values were determined and entered into the TPS, two plans were calculated to test the veracity of DLG and transmission independently. The plan used to determine the DLG has openings of varied sizes which are affected differently by the DLG. A large field uniform fluence that required a MLC carriage shift was used to determine the transmission value independent of DLG. After characterizing the dosimetric properties of the MLC independently, clinical IMRT plans were tested and used to tweak the final values. Results: This approach to modelling MLC dosimetric properties was employed for: standard 120 leaf MLC (SDMLC) and 120 leaf high definition MLC (HDMLC). Both types were successfully commissioned, tested, and approved for clinical use on 4 SDMLC machines and 2 HDMLC machines. The pass rate of clinical IMRT plans was 96.9% for 6MV and 98.3% for 10MV for SDMLC and 96.3% for 6MV, 96.5% for 6FFF, and 97.5% for 10FFF for HDMLCs using MapCheck2 with gamma analysis of 2%/2mm and 10% threshold. The final DLG and transmission parameters for 6X were 0.5mm and 0.01, and 1.35mm and 0.02 for HD and SD MLCs respectively. Conclusion: This iterative approach of determining dosimetric properties of MLCs is viable for both SDMLC and HDMLC and multiple energies. This approach accurately and efficiently determines the values needed for commissioning MLCs when they are employed for modulated therapies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

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

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, 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 quality during CT protocol optimization, especially when investigating the effects of new technologies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-F-CAMPUS-I-02: Contrast Enhanced Cone Beam CT Imaging with Dual- Gantry Image Acquisition and Constrained Iterative Reconstruction-a Simulation Study for Liver Imaging Application

Purpose: Contrast time-density curves may help differentiate malignant tumors from normal tissues or benign tumors. Repetitive scans using conventional CT or cone beam CT techniques, which Result in unacceptably high dose, may not achieve the desired temporal resolution. In this study we describe and demonstrate a 4D imaging technique for imaging and quantifying contrast flows requiring only one or two 360° scans. Methods: A dual-gantry system is used to simultaneously acquire two projection images at orthogonal orientations. Following the scan, each or both of the two 360° projection sets are used to reconstruct an average contrast enhanced image set which is then segmented to form a 3D contrast map. Alternatively, a pre-injection scan may be made and used to reconstruct a pre-injection image set which is subtracted from the post-injection image set to form the 3D contrast map. Each of the two 360° projection sets is divided into 12 subsets, thus creating 12 pairs of 30° limited angle projection sets, each corresponding to a time spanning over 1/12 of the scanning time. Each pair of the projection sets are reconstructed as a time specific 3D image set with the maximum likelihood estimation iterative algorithm using the contrast map as the constraint. As a demonstration, a 4D abdominal phantom was constructed from clinical CT images with blood flow through the normal tissue and a tumor modeled and imaging process simulated. Results: We have successfully generated a 4D image phantom, and calculated the projection images. The time density curves derived from the reconstructed image set matched well with the flow model used to generate the phantom. Conclusion: Dual-gantry image acquisition and constrained iterative reconstruction algorithm may help to obtain time-density curves of contrast agents in blood flows, which may help differentiate malignant tumors from normal tissues or benign tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-204-06: Grid-Line Artifact Minimization for High Resolution Detectors Using Iterative Residual Scatter Correction

Purpose: Anti-scatter grid-line artifacts are more prominent for high-resolution x-ray detectors since the fraction of a pixel blocked by the grid septa is large. Direct logarithmic subtraction of the artifact pattern is limited by residual scattered radiation and we investigate an iterative method for scatter correction. Methods: A stationary Smit-Rοntgen anti-scatter grid was used with a high resolution Dexela 1207 CMOS X-ray detector (75 µm pixel size) to image an artery block (Nuclear Associates, Model 76-705) placed within a uniform head equivalent phantom as the scattering source. The image of the phantom was divided by a flat-field image obtained without scatter but with the grid to eliminate grid-line artifacts. Constant scatter values were subtracted from the phantom image before dividing by the averaged flat-field-with-grid image. The standard deviation of pixel values for a fixed region of the resultant images with different subtracted scatter values provided a measure of the remaining grid-line artifacts. Results: A plot of the standard deviation of image pixel values versus the subtracted scatter value shows that the image structure noise reaches a minimum before going up again as the scatter value is increased. This minimum corresponds to a minimization of the grid-line artifacts as demonstrated in line profile plots obtained through each of the images perpendicular to the grid lines. Artifact-free images of the artery block were obtained with the optimal scatter value obtained by this iterative approach. Conclusion: Residual scatter subtraction can provide improved grid-line artifact elimination when using the flat-field with grid “subtraction” technique. The standard deviation of image pixel values can be used to determine the optimal scatter value to subtract to obtain a minimization of grid line artifacts with high resolution x-ray imaging detectors. This study was supported by NIH Grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-G-207-07: Iterative CT Shading Correction Method with No Prior Information

Purpose: Shading artifacts are caused by scatter contamination, beam hardening effects and other non-ideal imaging condition. Our Purpose is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT imaging (e.g., cone-beam CT, low-kVp CT) without relying on prior information. Methods: Our method applies general knowledge of the relatively uniform CT number distribution in one tissue component. Image segmentation is applied to construct template image where each structure is filled with the same CT number of that specific tissue. By subtracting the ideal template from CT image, the residual from various error sources are generated. Since the forward projection is an integration process, the non-continuous low-frequency shading artifacts in the image become continuous and low-frequency signals in the line integral. Residual image is thus forward projected and its line integral is filtered using Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error using standard FDK algorithm and added to the original image to obtain the shading corrected one. Since the segmentation is not accurate on shaded CT image, the proposed scheme is iterated until the variation of residual image is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT angiography scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative algorithm for shading correction in CT imaging. Being different from existing algorithms, our method is only assisted by general anatomical and physical information in CT imaging without relying on prior knowledge. Our method is thus practical and attractive as a general solution to CT shading correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

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

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: 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 images were quantified using the relative root mean square error (rRMSE) and the universal quality index (UQI) in numerical simulations. The performance of the SMART-RECON algorithm was compared with that of the prior image constrained compressed sensing (PICCS) reconstruction quantitatively in simulations and qualitatively in human subject exam. Results: In numerical simulations, the 240{sup ∘} short scan angular span was divided into four consecutive 60{sup ∘} angular subsectors. SMART-RECON enables four high temporal fidelity images without limited-view artifacts. The average rRMSE is 16% and UQIs are 0.96 and 0.95 for the two local regions of interest, respectively. In contrast, the corresponding average rRMSE and UQIs are 25%, 0.78, and 0.81, respectively, for the PICCS reconstruction. Note that only one filtered backprojection image can be reconstructed from the same data set with an average rRMSE and UQIs are 45%, 0.71, and 0.79, respectively, to benchmark reconstruction accuracies. For in vivo contrast enhanced cone beam CT data acquired from a short scan angular span of 200{sup ∘}, three 66{sup ∘} angular subsectors were used in SMART-RECON. The results demonstrated clear contrast difference in three SMART-RECON reconstructed image volumes without limited-view artifacts. In contrast, for the same angular sectors, PICCS cannot reconstruct images without limited-view artifacts and with clear contrast difference in three reconstructed image volumes. Conclusions: In time-resolved CT, the proposed SMART-RECON method provides a new method to eliminate limited-view artifacts using data acquired in an ultranarrow temporal window, which corresponds to approximately 60{sup ∘} angular subsectors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

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

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

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

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 in 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 the stationary region while reducing its influence in the dynamic region.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-D-206-04: Iterative CBCT Scatter Shading Correction Without Prior Information

Purpose: To estimate and remove the scatter contamination in the acquired projection of cone-beam CT (CBCT), to suppress the shading artifacts and improve the image quality without prior information. Methods: The uncorrected CBCT images containing shading artifacts are reconstructed by applying the standard FDK algorithm on CBCT raw projections. The uncorrected image is then segmented to generate an initial template image. To estimate scatter signal, the differences are calculated by subtracting the simulated projections of the template image from the raw projections. Since scatter signals are dominantly continuous and low-frequency in the projection domain, they are estimated by low-pass filtering the difference signals and subtracted from the raw CBCT projections to achieve the scatter correction. Finally, the corrected CBCT image is reconstructed from the corrected projection data. Since an accurate template image is not readily segmented from the uncorrected CBCT image, the proposed scheme is iterated until the produced template is not altered. Results: The proposed scheme is evaluated on the Catphan©600 phantom data and CBCT images acquired from a pelvis patient. The result shows that shading artifacts have been effectively suppressed by the proposed method. Using multi-detector CT (MDCT) images as reference, quantitative analysis is operated to measure the quality of corrected images. Compared to images without correction, the method proposed reduces the overall CT number error from over 200 HU to be less than 50 HU and can increase the spatial uniformity. Conclusion: An iterative strategy without relying on the prior information is proposed in this work to remove the shading artifacts due to scatter contamination in the projection domain. The method is evaluated in phantom and patient studies and the result shows that the image quality is remarkably improved. The proposed method is efficient and practical to address the poor image quality issue of CBCT images. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRA-11: Tumor Tracking in An Iterative Volume of Interest Based 4D CBCT Reconstruction

Purpose: 4D CBCT can allow evaluation of tumor motion immediately prior to radiation therapy, but suffers from heavy artifacts that limit its ability to track tumors. Various iterative and compressed sensing reconstructions have been proposed to reduce these artifacts, but are costly time-wise and can degrade the image quality of bony anatomy for alignment with regularization. We have previously proposed an iterative volume of interest (I4D VOI) method which minimizes reconstruction time and maintains image quality of bony anatomy by focusing a 4D reconstruction within a VOI. The purpose of this study is to test the tumor tracking accuracy of this method compared to existing methods. Methods: Long scan (8–10 mins) CBCT data with corresponding RPM data was collected for 12 lung cancer patients. The full data set was sorted into 8 phases and reconstructed using FDK cone beam reconstruction to serve as a gold standard. The data was reduced in way that maintains a normal breathing pattern and used to reconstruct 4D images using FDK, low and high regularization TV minimization (λ=2,10), and the proposed I4D VOI method with PTVs used for the VOI. Tumor trajectories were found using rigid registration within the VOI for each reconstruction and compared to the gold standard. Results: The root mean square error (RMSE) values were 2.70mm for FDK, 2.50mm for low regularization TV, 1.48mm for high regularization TV, and 2.34mm for I4D VOI. Streak artifacts in I4D VOI were reduced compared to FDK and images were less blurred than TV reconstructed images. Conclusion: I4D VOI performed at least as well as existing methods in tumor tracking, with the exception of high regularization TV minimization. These results along with the reconstruction time and outside VOI image quality advantages suggest I4D VOI to be an improvement over existing methods. Funding support provided by CPRIT grant RP110562-P2-01.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

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

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. Distinct 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.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Erosion products of plasma facing materials formed under ITER-like transient load and deuterium retention in them

Erosion of the plasma-facing materials in particular evaporation of the materials in a fusion reactor under intense transient events is one of the problems of the ITER. The current experimental data are insufficient to predict the properties of the erosion products, a significant part of which will be formed during transient events (edge-localized modes (ELMs) and disruptions). The paper concerns the experimental investigation of the graphite and tungsten erosion products deposited under pulsed plasma load at the QSPA-T: heat load on the target was 2.6 MJ/m{sup 2} with 0.5 ms pulse duration. The designed diagnostics for measuring the deposition rate made it possible to determine that the deposition of eroded material occurs during discharge, and the deposition rate is in the range (0.1–100) × 10{sup 19} at/(cm{sup 2} s), which is much higher than that for stationary processes. It is found that the relative atomic concentrations D/C and D/(W + C) in the erosion products deposited during the pulse process are on the same level as for the stationary processes. An exposure of erosion products to photonic energy densities typical of those expected at mitigated disruptions in the ITER (pulse duration of 0.5–1 ms, integral energy density of radiation of 0.1–0.5 MJ/m2) significantly decreases the concentration of trapped deuterium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Development of a laser cleaning method for the first mirror surface of the charge exchange recombination spectroscopy diagnostics on ITER

A set of optical diagnostics is expected for measuring the plasma characteristics in ITER. Optical elements located inside discharge chambers are exposed to an intense radiation load, sputtering due to collisions with energetic atoms formed in the charge transfer processes, and contamination due to recondensation of materials sputtered from different parts of the construction of the chamber. Removing the films of the sputtered materials from the mirrors with the aid of pulsed laser radiation is an efficient cleaning method enabling recovery of the optical properties of the mirrors. In this work, we studied the efficiency of removal of metal oxide films by pulsed radiation of a fiber laser. Optimization of the laser cleaning conditions was carried out on samples representing metal substrates polished with optical quality with deposition of films on them imitating the chemical composition and conditions expected in ITER. It is shown that, by a proper selection of modes of radiation exposure to the surface with a deposited film, it is feasible to restore the original high reflection characteristics of optical elements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗