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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.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Pulmonary Ventilation Imaging Based on 4-Dimensional Computed Tomography: Comparison With Pulmonary Function Tests and SPECT Ventilation Images

Purpose: 4-dimensional computed tomography (4D-CT)-based pulmonary ventilation imaging is an emerging functional imaging modality. The purpose of this study was to investigate the physiological significance of 4D-CT ventilation imaging by comparison with pulmonary function test (PFT) measurements and single-photon emission CT (SPECT) ventilation images, which are the clinical references for global and regional lung function, respectively. Methods and Materials: In an institutional review board–approved prospective clinical trial, 4D-CT imaging and PFT and/or SPECT ventilation imaging were performed in thoracic cancer patients. Regional ventilation (V{sub 4DCT}) was calculated by deformable image registration of 4D-CT images and quantitative analysis for regional volume change. V{sub 4DCT} defect parameters were compared with the PFT measurements (forced expiratory volume in 1 second (FEV{sub 1}; % predicted) and FEV{sub 1}/forced vital capacity (FVC; %). V{sub 4DCT} was also compared with SPECT ventilation (V{sub SPECT}) to (1) test whether V{sub 4DCT} in V{sub SPECT} defect regions is significantly lower than in nondefect regions by using the 2-tailed t test; (2) to quantify the spatial overlap between V{sub 4DCT} and V{sub SPECT} defect regions with Dice similarity coefficient (DSC); and (3) to test ventral-to-dorsal gradients by using the 2-tailed t test. Results: Of 21 patients enrolled in the study, 18 patients for whom 4D-CT and either PFT or SPECT were acquired were included in the analysis. V{sub 4DCT} defect parameters were found to have significant, moderate correlations with PFT measurements. For example, V{sub 4DCT}{sup HU} defect volume increased significantly with decreasing FEV{sub 1}/FVC (R=−0.65, P<.01). V{sub 4DCT} in V{sub SPECT} defect regions was significantly lower than in nondefect regions (mean V{sub 4DCT}{sup HU} 0.049 vs 0.076, P<.01). The average DSCs for the spatial overlap with SPECT ventilation defect regions were only moderate (V{sub 4DCT}{sup HU}0.39 ± 0.11). Furthermore, ventral-to-dorsal gradients of V{sub 4DCT} were strong (V{sub 4DCT}{sup HU} R{sup 2} = 0.69, P=.08), which was similar to V{sub SPECT} (R{sup 2} = 0.96, P<.01). Conclusions: An 18-patient study demonstrated significant correlations between 4D-CT ventilation and PFT measurements as well as SPECT ventilation, providing evidence toward the validation of 4D-CT ventilation imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

An image classification deep-learning algorithm for shrapnel detection from ultrasound images

Ultrasound imaging is essential for non-invasively diagnosing injuries where advanced diagnostics may not be possible. However, image interpretation remains a challenge as proper expertise may not be available. In response, artificial intelligence algorithms are being investigated to automate image analysis and diagnosis. Here, we highlight an image classification convolutional neural network for detecting shrapnel in ultrasound images. As an initial application, different shrapnel types and sizes were embedded first in a tissue mimicking phantom and then in swine thigh tissue. The algorithm architecture was optimized stepwise by minimizing validation loss and maximizing F1 score. The final algorithm design trained on tissue phantom image sets had an F1 score of 0.95 and an area under the ROC curve of 0.95. It maintained higher than a 90% accuracy for each of 8 shrapnel types. When trained only on swine image sets, the optimized algorithm format had even higher metrics: F1 and area under the ROC curve of 0.99. Overall, the algorithm developed resulted in strong classification accuracy for both the tissue phantom and animal tissue. This framework can be applied to other trauma relevant imaging applications such as internal bleeding to further simplify trauma medicine when resources and image interpretation are scarce.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Improved image quality of cone beam CT scans for radiotherapy image guidance using fiber-interspaced antiscatter grid

Purpose: Medical linear accelerator mounted cone beam CT (CBCT) scanner provides useful soft tissue contrast for purposes of image guidance in radiotherapy. The presence of extensive scattered radiation has a negative effect on soft tissue visibility and uniformity of CBCT scans. Antiscatter grids (ASG) are used in the field of diagnostic radiography to mitigate the scatter. They usually do increase the contrast of the scan, but simultaneously increase the noise. Therefore, and considering other scatter mitigation mechanisms present in a CBCT scanner, the applicability of ASGs with aluminum interspacing for a wide range of imaging conditions has been inconclusive in previous studies. In recent years, grids using fiber interspacers have appeared, providing grids with higher scatter rejection while maintaining reasonable transmission of primary radiation. The purpose of this study was to evaluate the impact of one such grid on CBCT image quality. Methods: The grid used (Philips Medical Systems) had ratio of 21:1, frequency 36 lp/cm, and nominal selectivity of 11.9. It was mounted on the kV flat panel detector of an Elekta Synergy linear accelerator and tested in a phantom and a clinical study. Due to the flex of the linac and presence of gridline artifacts an angle dependent gain correction algorithm was devised to mitigate resulting artifacts. Scan reconstruction was performed using XVI4.5 augmented with inhouse developed image lag correction and Hounsfield unit calibration. To determine the necessary parameters for Hounsfield unit calibration and software scatter correction parameters, the Catphan 600 (The Phantom Laboratory) phantom was used. Image quality parameters were evaluated using CIRS CBCT Image Quality and Electron Density Phantom (CIRS) in two different geometries: one modeling head and neck and other pelvic region. Phantoms were acquired with and without the grid and reconstructed with and without software correction which was adapted for the different acquisition scenarios. Parameters used in the phantom study weret{sub cup} for nonuniformity and contrast-to-noise ratio (CNR) for soft tissue visibility. Clinical scans were evaluated in an observer study in which four experienced radiotherapy technologists rated soft tissue visibility and uniformity of scans with and without the grid. Results: The proposed angle dependent gain correction algorithm suppressed the visible ring artifacts. Grid had a beneficial impact on nonuniformity, contrast to noise ratio, and Hounsfield unit accuracy for both scanning geometries. The nonuniformity reduced by 90% for head sized object and 91% for pelvic-sized object. CNR improved compared to no corrections on average by a factor 2.8 for the head sized object, and 2.2 for the pelvic sized phantom. Grid outperformed software correction alone, but adding additional software correction to the grid was overall the best strategy. In the observer study, a significant improvement was found in both soft tissue visibility and nonuniformity of scans when grid is used. Conclusions: The evaluated fiber-interspaced grid improved the image quality of the CBCT system for broad range of imaging conditions. Clinical scans show significant improvement in soft tissue visibility and uniformity without the need to increase the imaging dose.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-A-12A-02: Novel Lung Ventilation Imaging with Single Energy CT After Single Inhalation of Xenon: Comparison with SPECT Ventilation Images

Purpose: We propose a novel lung functional imaging method to determine the spatial distribution of xenon (Xe) gas in a single inhalation as a measure of regional ventilation. We compare Xe-CT ventilation to single-photon emission CT (SPECT) ventilation, which is the current clinical reference. Regional lung ventilation information may be useful for the diagnosis and monitoring of pulmonary diseases such as COPD, radiotherapy planning, and assessing the progression of toxicity after radiation therapy. Methods: In an IRB-approved clinical study, Xe-CT and SPECT ventilation scans were acquired for three patients including one patient with severe emphysema and two lung cancer patients treated with radiotherapy. For Xe- CT, we acquired two breath-hold single energy CT images of the entire lung with inspiration of 100% O2 and a mixture of 70% Xe and 30% O2, respectively. A video biofeedback system was used to achieve reproducible breath-holds. We used deformable image registration to align the breathhold images with each other to accurately subtract them, producing a map of the distribution of Xe as a surrogate of lung ventilation. We divided each lung into twelve parts and correlated the Hounsfield unit (HU) enhancement at each part with the SPECT ventilation count of the corresponding part of the lung. Results: The mean of the Pearson linear correlation coefficient values between the Xe-CT and ventilation SPECT count for all three patients were 0.62 (p<0.01). The Xe-CT image had a higher resolution than SPECT, and did not show central airway deposition artifacts that were present in the SPECT image. Conclusion: We developed a rapid, safe, clinically practical, and potentially widely accessible method for regional lung functional imaging. We demonstrated strong correlations between the Xe-CT ventilation image and SPECT ventilation image as the clinical reference. This ongoing study will investigate more patients to confirm this finding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Commissioning of a proton gantry equipped with dual x-ray imagers and a robotic patient positioner, and evaluation of the accuracy of single-beam image registration for this system

Purpose: To check the accuracy of a gantry equipped with dual x-ray imagers and a robotic patient positioner for proton radiotherapy, and to evaluate the accuracy and feasibility of single-beam registration using the robotic positioner. Methods: One of the proton treatment rooms at their institution was upgraded to include a robotic patient positioner (couch) with 6 degrees of freedom and dual orthogonal kilovoltage x-ray imaging panels. The wander of the proton beam central axis, the wander of the beamline, and the orthogonal image panel crosswires from the gantry isocenter were measured for different gantry angles. The couch movement accuracy and couch wander from the gantry isocenter were measured for couch loadings of 50–300 lb with couch rotations from 0° to ±90°. The combined accuracy of the gantry, couch, and imagers was checked using a custom-made 30 × 30 × 30 cm{sup 3} Styrofoam phantom with beekleys embedded in it. A treatment in this room can be set up and registered at a setup field location, then moved precisely to any other treatment location without requiring additional image registration. The accuracy of the single-beam registration strategy was checked for treatments containing multiple beams with different combinations of gantry angles, couch yaws, and beam locations. Results: The proton beam central axis wander from the gantry isocenter was within 0.5 mm with gantry rotations in both clockwise (CW) and counterclockwise (CCW) directions. The maximum wander of the beamline and orthogonal imager crosswire centers from the gantry isocenter were within 0.5 and 0.8 mm, respectively, with the gantry rotations in CW and CCW directions. Vertical and horizontal couch wanders from the gantry isocenter were within 0.4 and 1.3 mm, respectively, for couch yaw from 0° to ±90°. For a treatment with multiple beams with different gantry angles, couch yaws, and beam locations, the measured displacements of treatment beam locations from the one based on the initial setup beam registered at the gantry at 0°/180° and couch yaw at 0° were within 1.5 mm in three translations and 0.5° in three rotations for a 200 lb couch loading. Conclusions: Results demonstrate that the gantry equipped with a robotic patient positioner and dual imaging panels satisfies treatment requirements for proton radiotherapy. The combined accuracy of the gantry, couch, and imagers allows a patient to be registered at one setup position and then moved precisely to another treatment position by commanding the robotic patient positioner and delivering treatment without requiring additional image registration.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and a wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within a patient-specific anatomical model to optimize image acquisition and reconstruction techniques, thereby improving imaging performance beyond that achievable with conventional approaches. 2R01-CA-112163; R01-EB-017226; U01-EB-018758; Siemens Healthcare (Forcheim, Germany)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

SNIa Cosmology Analysis Results from Simulated LSST Images: From Difference Imaging to Constraints on Dark Energy

Abstract The Vera Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to process ∼10 6 transient detections per night. For precision measurements of cosmological parameters and rates, it is critical to understand the detection efficiency, magnitude limits, artifact contamination levels, and biases in the selection and photometry. Here we rigorously test the LSST Difference Image Analysis (DIA) pipeline using simulated images from the Rubin Observatory LSST Dark Energy Science Collaboration Data Challenge (DC2) simulation for the Wide-Fast-Deep survey area. DC2 is the first large-scale (300 deg 2 ) image simulation of a transient survey that includes realistic cadence, variable observing conditions, and CCD image artifacts. We analyze ∼15 deg 2 of DC2 over a 5 yr time span in which artificial point sources from Type Ia supernova (SNIa) light curves have been overlaid onto the images. The magnitude limits per filter are u = 23.66 mag, g = 24.69 mag, r = 24.06 mag, i = 23.45 mag, z = 22.54 mag, and y = 21.62 mag. The artifact contamination levels are ∼90% of all detections, corresponding to ∼1000 artifacts deg –2 in g band, and falling to 300 deg –2 in y band. The photometry has biases <1% for magnitudes 19.5 < m < 23. Our DIA performance on simulated images is similar to that of the Dark Energy Survey difference-imaging pipeline on real images. We also characterize DC2 image properties to produce catalog-level simulations needed for distance bias corrections. We find good agreement between DC2 data and simulations for distributions of signal-to-noise ratio, redshift, and fitted light-curve properties. Applying a realistic SNIa cosmology analysis for redshifts z < 1, we recover the input cosmology parameters to within statistical uncertainties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

Image understanding and interpretation in microwave diversity imaging

The authors investigate microwave imaging of metallic objects using a diversity method and interpret and predict the reconstructed image from an approach based on analysis of the scattering mechanism and a back-projection algorithm used in image retrieval. The connection between the various scattering mechanisms and the reconstructed images is discussed, what the images represent is interpreted, and a prediction is made as to what the image will look like over given spectral and angular windows. A brief description is given of the microwave diversity imaging system and the formulation of the microwave diversity imaging based on the physical optics approximation. The scattering mechanism of a complex shaped metallic object is then briefly reviewed and an alternate approach to interpreting the reconstructed image based on the understanding of the scattering mechanism and the reconstruction algorithm is given. Several numerical and experimental examples are included to support this interpretation approach.

Li, Hsueh-Jyh↗
NASA NTRS1994

An adaptive technique to maximize lossless image data compression of satellite images

Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

Stewart, Robert J.↗
NASA NTRS2019

GOES-R Solar UltraViolet Imager Extended Coronal Imaging

GOES-16 and GOES-17 each hosts a Solar UltraViolet Imager (SUVI) that images the Sun in six extreme ultraviolet (EUV) wavelengths: 9.4 nm, 13.1nm, 17.1nm, 19.5nm, 28.4nm, and 30.4nm. The SUVI is nominally Sun-pointed and has a four-minute imaging sequence covering all the channels and meeting the dynamic range requirements. Based on the SUVI capabilities observed on-orbit, a campaign to image the extended solar corona was undertaken in 2018. This was performed by off-pointing the SUVI line-of-sight to the left and right of the Sun and producing a composite image by stitching together the off-pointed and the Sun-centered images. The imaging area in the composite is about three times the nominal image area in the East-West direction (about 5 RSun versus 1.8 RSun for nominal images). The campaign was conducted in February (4 hours), June (72 hours), and August-September of 2018 (5 weeks). Results from the campaign indicated the presence of solar corona to three solar radii, even in the quiet Sun part of the solar cycle. NOAA can operationalize this concept by tasking the SUVI on one of GOES-E and GOES-W. Such long-term operation will provide data that is needed to establish the much needed connectivity between the EUV and white light coronagraph data for the CME events.

Extended Coronal↗
DOE OSTI2018

A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging

Many facets of an image acquisition workflow leave a digital footprint, making workflow analysis amenable to an informatics-based solution. This paper describes a detailed framework for analyzing workflow and uses acute stroke response timeliness in CT as a practical demonstration. We review methods for accessing the digital footprints resulting from common technologist/device interactions. This overview lays a foundation for obtaining data for workflow analysis. We demonstrate the method by analyzing CT imaging efficiency in the setting of acute stroke. We successfully used digital footprints of CT technologists to analyze their workflow. We presented an overview of other digital footprints including but not limited to contrast administration, patient positioning, billing, reformat creation, and scheduling. A framework for analyzing image acquisition workflow was presented. This framework is transferable to any modality, as the key steps of image acquisition, image reconstruction, image post processing, and image transfer to PACS are common to any imaging modality in diagnostic radiology.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Review methods for image segmentation from computed tomography images

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affect the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Manifold projection image segmentation for nano-XANES imaging

As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Quantifying element incorporation in multispecies biofilms using nanoscale secondary ion mass spectrometry image analysis

Elucidating nutrient exchange in microbial communities is an important step in understanding the relationships between microbial systems and global biogeochemical cycles, but these communities are complex and the interspecies interactions that occur within them are not well understood. Phototrophic consortia are useful and relevant experimental systems to investigate such interactions as they are not only prevalent in the environment, but some are cultivable in vitro and amenable to controlled scientific experimentation. Nanoscale secondary ion mass spectrometry (NanoSIMS) is a powerful, high spatial resolution tool capable of visualizing the metabolic activities of single cells within a biofilm, but quantitative analysis of the resulting data has typically been a manual process, resulting in a task that is both laborious and susceptible to human error. In this work, the authors describe the creation and application of a semiautomated image-processing pipeline that can analyze NanoSIMS-generated data, applied to phototrophic biofilms as an example. The tool employs an image analysis process, which includes both elemental and morphological segmentation, producing a final segmented image that allows for discrimination between autotrophic and heterotrophic biomass, the detection of individual cyanobacterial filaments and heterotrophic cells, the quantification of isotopic incorporation of individual heterotrophic cells, and calculation of relevant population statistics. The authors demonstrate the functionality of the tool by using it to analyze the uptake of 15 N provided as either nitrate or ammonium through the unicyanobacterial consortium UCC-O and imaged via NanoSIMS. The authors found that the degree of 15N incorporation by individual cells was highly variable when labeled with 15 NH 4 + , but much more even when biofilms were labeled with 15 NO 3 – . In the 15 NH 4 + -amended biofilms, the heterotrophic distribution of 15 N incorporation was highly skewed, with a large population showing moderate 15 N incorporation and a small number of organisms displaying very high 15 N uptake. The results showed that analysis of NanoSIMS data can be performed in a way that allows for quantitation of the elemental uptake of individual cells, a technique necessary for advancing research into the metabolic networks that exist within biofilms with statistical analyses that are supported by automated, user-friendly processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Parametrization of textural patterns in {sup 123}I-ioflupane imaging for the automatic detection of Parkinsonism

Purpose: A novel approach to a computer aided diagnosis system for the Parkinson's disease is proposed. This tool is intended as a supporting tool for physicians, based on fully automated methods that lead to the classification of{sup 123}I-ioflupane SPECT images. Methods: {sup 123}I-ioflupane images from three different databases are used to train the system. The images are intensity and spatially normalized, then subimages are extracted and a 3D gray-level co-occurrence matrix is computed over these subimages, allowing the characterization of the texture using Haralick texture features. Finally, different discrimination estimation methods are used to select a feature vector that can be used to train and test the classifier. Results: Using the leave-one-out cross-validation technique over these three databases, the system achieves results up to a 97.4% of accuracy, and 99.1% of sensitivity, with positive likelihood ratios over 27. Conclusions: The system presents a robust feature extraction method that helps physicians in the diagnosis task by providing objective, operator-independent textural information about{sup 123}I-ioflupane images, commonly used in the diagnosis of the Parkinson's disease. Textural features computation has been optimized by using a subimage selection algorithm, and the discrimination estimation methods used here makes the system feature-independent, allowing us to extend it to other databases and diseases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

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

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

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Imaging post-stereotactic body radiation therapy responses for hepatocellular carcinoma: typical imaging patterns and pitfalls

Stereotactic body radiation therapy (SBRT) has increased utility in the management of hepatocellular carcinoma (HCC) ranging from local therapy in early-stage HCC not suitable for other focal therapies to end-stage HCC. As the indications for the use of SBRT in HCC expand, diagnostic imaging is being increasingly used to assess response to treatment. The imaging features of tumor response do not parallel those of other focal therapies such as radiofrequency ablation or trans-arterial chemoembolization that immediately devascularize the tumor. The tumor response to SBRT on imaging takes much longer and often shows gradual changes including the reduction of enhancement and size over several months. It is essential to recognize the typical imaging patterns of response, as well as the appearance of focal liver reaction in the non-target liver that can confound image interpretation. The timing of treatment response assessment imaging is fundamental to minimize the potential for false negative response. The purpose of this article is to review the variable post-SBRT imaging features of HCC and adjacent liver parenchyma and discuss the potential pitfalls of imaging evaluation after SBRT for HCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

A dual wavelength imaging system for plasma-surface interaction studies on the National Spherical Torus Experiment Upgrade

A two-channel spectral imaging system based on a charge injection device radiation-hardened intensified camera was built for studies of plasma-surface interactions on divertor plasma facing components in the National Spherical Torus Experiment Upgrade (NSTX-U) tokamak. By means of commercially available mechanically referenced optical components, the two-wavelength setup images the light from the plasma, relayed by a fiber optic bundle, at two different wavelengths side-by-side on the same detector. Remotely controlled filter wheels are used for narrow bandpass and neutral density filters on each optical path allowing for simultaneous imaging of emission at wavelengths differing in brightness up to 3 orders of magnitude. Applications on NSTX-U will include the measurement of impurity influxes in the lower divertor strike point region and the imaging of plasma-material interaction on the head of the surface analysis probe MAPP (Material Analysis and Particle Probe). The diagnostic setup and initial results from its application on the lithium tokamak experiment are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗