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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
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

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 ↗
DOE OSTI2016

Preliminary design of a tangentially viewing imaging bolometer for NSTX-U

The infrared imaging video bolometer (IRVB) measures plasma radiated power images using a thin metal foil. Two different designs with a tangential view of NSTX-U are made assuming a 640 × 480 (1280 × 1024) pixel, 30 (105) fps, 50 (20) mK, IR camera imaging the 9 cm × 9 cm × 2 μm Pt foil. The foil is divided into 40 × 40 (64 × 64) IRVB channels. This gives a spatial resolution of 3.4 (2.2) cm on the machine mid-plane. The noise equivalent power density of the IRVB is given as 113 (46) μW/cm{sup 2} for a time resolution of 33 (20) ms. Synthetic images derived from Scrape Off Layer Plasma Simulation data using the IRVB geometry show peak signal levels ranging from ∼0.8 to ∼80 (∼0.36 to ∼26) mW/cm{sup 2}.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Proton pinhole imaging on the National Ignition Facility

Pinhole imaging of large (mm scale) carbon-deuterium (CD) plasmas by proton self-emission has been used for the first time to study the microphysics of shock formation, which is of astrophysical relevance. The 3 MeV deuterium-deuterium (DD) fusion proton self-emission from these plasmas is imaged using a novel pinhole imaging system, with up to five different 1 mm diameter pinholes positioned 25 cm from target-chamber center. CR39 is used as the detector medium, positioned at 100 cm distance from the pinhole for a magnification of 4 ×. A Wiener deconvolution algorithm is numerically demonstrated and used to interpret the images. When the spatial morphology is known, this algorithm accurately reproduces the size of features larger than about half the pinhole diameter. For these astrophysical plasma experiments on the National Ignition Facility, this provides a strong constraint on simulation modeling of the experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Detailed characterization of the LLNL imaging proton spectrometer

Ultra-intense short pulse lasers incident on solid targets (e.g., thin Au foils) produce well collimated, broad-spectrum proton beams. These proton beams can be used to characterize magnetic fields, electric fields, and density gradients in high energy-density systems. The LLNL-Imaging Proton Spectrometer (L-IPS) was designed and built [H. Chen et al., Rev. Sci. Instrum. 81, 10D314 (2010)] for use with such laser produced proton beams. The L-IPS has an energy range of 50 keV-40 MeV with a resolving power (E/dE) of about 275 at 1 MeV and 21 at 20 MeV, as well as a single spatial imaging axis. In order to better characterize the dispersion and imaging capability of this diagnostic, a 3D finite element analysis solver is used to calculate the magnetic field of the L-IPS. Particle trajectories are then obtained via numerical integration to determine the dispersion relation of the L-IPS in both energy and angular space.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Depth-resolved ballistic imaging in a low-depth-of-field optical Kerr gated imaging system

We demonstrate depth-resolved imaging in a ballistic imaging system, in which a heterodyned femtosecond optical Kerr gate is introduced to extract useful imaging photons for detecting an object hidden in turbid media and a compound lens is proposed to ensure both the depth-resolved imaging capability and the long working distance. Two objects of about 15-μm widths hidden in a polystyrene-sphere suspension have been successfully imaged with approximately 600-μm depth resolution. Modulation-transfer-function curves with the object in and away from the object plane have also been measured to confirm the depth-resolved imaging capability of the low-depth-of-field (low-DOF) ballistic imaging system. This imaging approach shows potential for application in research of the internal structure of highly scattering fuel spray.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

GEMINI PLANET IMAGER OBSERVATIONS OF THE AU MICROSCOPII DEBRIS DISK: ASYMMETRIES WITHIN ONE ARCSECOND

We present Gemini Planet Imager (GPI) observations of AU Microscopii, a young M dwarf with an edge-on, dusty debris disk. Integral field spectroscopy and broadband imaging polarimetry were obtained during the commissioning of GPI. In our broadband imaging polarimetry observations, we detect the disk only in total intensity and find asymmetries in the morphology of the disk between the southeast (SE) and northwest (NW) sides. The SE side of the disk exhibits a bump at 1″ (10 AU projected separation) that is three times more vertically extended and three times fainter in peak surface brightness than the NW side at similar separations. This part of the disk is also vertically offset by 69 ± 30 mas to the northeast at 1″ when compared to the established disk midplane and is consistent with prior Atacama Large Millimeter/submillimeter Array and Hubble Space Telescope/Space Telescope Imaging Spectrograph observations. We see hints that the SE bump might be a result of detecting a horizontal sliver feature above the main disk that could be the disk backside. Alternatively, when including the morphology of the NW side, where the disk midplane is offset in the opposite direction ∼50 mas between 0.″4 and 1.″2, the asymmetries suggest a warp-like feature. Using our integral field spectroscopy data to search for planets, we are 50% complete for ∼4 M{sub Jup} planets at 4 AU. We detect a source, resolved only along the disk plane, that could either be a candidate planetary mass companion or a compact clump in the disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

TH-A-18C-11: An Investigation of KV CBCT Image Quality and Dose Reduction for Volume-Of-Interest Imaging Using Dynamic Collimation

Purpose: The focus of this work was to investigate the improvements in image quality and dose reduction for volume-of-interest (VOI) kV-CBCT using dynamic collimation. Methods: A prototype iris aperture was used to track a VOI during a CBCT acquisition. The current aperture design is capable of one-dimensional translation as a function of gantry angle and dynamic adjustment of the iris radius. The aperture occupies the location of the bow-tie filter on a Varian OBI system. CBCT and planar image quality was investigated as a function of aperture radius, while maintaining the same dose to the VOI, for a 20 cm diameter cylindrical water phantom with a 9 mm diameter bone insert centered on isocenter. Corresponding scatter-to-primary ratios (SPR) were determined at the detector plane with Monte Carlo simulation using EGSnrc. Dose distributions for various anatomical sites were modeled using a dynamic BEAMnrc library and DOSXYZnrc. The resulting VOI dose distributions were compared to full-field distributions. Results: SPR was reduced by a factor of 8.4 when decreasing iris diameter from 21.2 cm to 2.4 cm (at isocenter). Similarly, this change in iris diameter corresponds to a factor increase of approximately 1.4 and 1.5 in image contrast for CBCT and planar images, respectively, and similarly a factor decrease in image noise of approximately 1.7 and 1.5. This results in a measured gain in contrast-to-noise ratio of a factor of approximately 2.3 for both CBCT and planar images. Depending upon the anatomical site, dose was reduced to 10%–70% of the full field value along the central axis plane and down to 2% along the axial planes, while maintaining the same dose to the VOI compared to full-field techniques. Conclusion: The presented VOI technique offers improved image quality for image-guided radiotherapy while sparing the surrounding volume of unnecessary dose compared to full-field techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

The image quality of ion computed tomography at clinical imaging dose levels

Purpose: Accurately predicting the range of radiotherapy ions in vivo is important for the precise delivery of dose in particle therapy. Range uncertainty is currently the single largest contribution to the dose margins used in planning and leads to a higher dose to normal tissue. The use of ion CT has been proposed as a method to improve the range uncertainty and thereby reduce dose to normal tissue of the patient. A wide variety of ions have been proposed and studied for this purpose, but no studies evaluate the image quality obtained with different ions in a consistent manner. However, imaging doses ion CT is a concern which may limit the obtainable image quality. In addition, the imaging doses reported have not been directly comparable with x-ray CT doses due to the different biological impacts of ion radiation. The purpose of this work is to develop a robust methodology for comparing the image quality of ion CT with respect to particle therapy, taking into account different reconstruction methods and ion species. Methods: A comparison of different ions and energies was made. Ion CT projections were simulated for five different scenarios: Protons at 230 and 330 MeV, helium ions at 230 MeV/u, and carbon ions at 430 MeV/u. Maps of the water equivalent stopping power were reconstructed using a weighted least squares method. The dose was evaluated via a quality factor weighted CT dose index called the CT dose equivalent index (CTDEI). Spatial resolution was measured by the modulation transfer function. This was done by a noise-robust fit to the edge spread function. Second, the image quality as a function of the number of scanning angles was evaluated for protons at 230 MeV. In the resolution study, the CTDEI was fixed to 10 mSv, similar to a typical x-ray CT scan. Finally, scans at a range of CTDEI’s were done, to evaluate dose influence on reconstruction error. Results: All ions yielded accurate stopping power estimates, none of which were statistically different from the ground truth image. Resolution (as defined by the modulation transfer function = 10% point) was the best for the helium ions (18.21 line pairs/cm) and worst for the lower energy protons (9.37 line pairs/cm). The weighted quality factor for the different ions ranged from 1.23 for helium to 2.35 for carbon ions. For the angle study, a sharp increase in absolute error was observed below 45 distinct angles, giving the impression of a threshold, rather than smooth, limit to the number of angles. Conclusions: The method presented for comparing various ion CT modalities is feasible for practical use. While all studied ions would improve upon x-ray CT for particle range estimation, helium appears to give the best results and deserves further study for imaging.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

SU-E-J-36: Comparison of CBCT Image Quality for Manufacturer Default Imaging Modes

Purpose CBCT is being increasingly used in patient setup for radiotherapy. Often the manufacturer default scan modes are used for performing these CBCT scans with the assumption that they are the best options. To quantitatively assess the image quality of these scan modes, all of the scan modes were tested as well as options with the reconstruction algorithm. Methods A CatPhan 504 phantom was scanned on a TrueBeam Linear Accelerator using the manufacturer scan modes (FSRT Head, Head, Image Gently, Pelvis, Pelvis Obese, Spotlight, & Thorax). The Head mode scan was then reconstructed multiple times with all filter options (Smooth, Standard, Sharp, & Ultra Sharp) and all Ring Suppression options (Disabled, Weak, Medium, & Strong). An open source ImageJ tool was created for analyzing the CatPhan 504 images. Results The MTF curve was primarily dictated by the voxel size and the filter used in the reconstruction algorithm. The filters also impact the image noise. The CNR was worst for the Image Gently mode, followed by FSRT Head and Head. The sharper the filter, the worse the CNR. HU varied significantly between scan modes. Pelvis Obese had lower than expected HU values than most while the Image Gently mode had higher than expected HU values. If a therapist tried to use preset window and level settings, they would not show the desired tissue for some scan modes. Conclusion Knowing the image quality of the set scan modes, will enable users to better optimize their setup CBCT. Evaluation of the scan mode image quality could improve setup efficiency and lead to better treatment outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-50: An Evaluation of the Stability of Image Quality Parameters of the Elekta XVI and IView Imaging Systems

Introduction Quality assurance of the image quality for image guided localization systems is crucial to ensure accurate visualization and localization of target volumes. In this study, the long term stability of selected image parameters was assessed and evaluated for CBCT mode, planar radiographic kV mode and MV mode. Methods and Materials: The CATPHAN, QckV-1 and QC-3 phantoms were used to evaluate the image quality parameters. The planar radiographic images were analyzed in PIPSpro™ with spatial resolution (f30, f40, f50) being recorded. For XVI CBCT, Head and Neck Small20 (S20) and Pelvis Medium20 (M20) standard acquisition modes were evaluated for Uniformity, Noise, Spatial Resolution and HU constancy. Dose and kVp for the XVI were recorded using the Unfors RaySafe Xi system with the R/F Low Detector for the kV planar radiographic mode. Results A total of 20 and 10 measurements were acquired for the planar radiographic and CBCT systems respectively over a two month period. Values were normalized to the mean and the standard deviations (STD) were recorded. For the planar radiographic spatial resolution, the STD for f30, f40, f50 were 0.004, 0.002, 0.002 and 0.005, 0.007, 0.008 for the kV and MV, respectively. The average recorded dose for kV was 38.7±2.7 μGy. The STD of the evaluated metrics for the S20 acquisition were: 0.444(f30), 0.067(f40), 0.062(f50), 0.018(Water/poly-HU constancy), 0.028(uniformity) and 0.106(noise). The standard deviations for the M20 acquisition were: 0.108(f30), 0.073(f40), 0.091(f50), 0.008(Water/poly-HU constancy), 0.005(uniformity) and 0.005(noise). Using these, tolerances can be reported as a warning and action threshold of 1σ and 2σ. Conclusion A study was performed to assess the stability of the basic image quality parameters recommended by TG-142 for the Elekta XVI and iView imaging systems. Consistent imaging and dosimetric properties over the evaluated time frame were noted. This work was funded in part by the Cancer Prevention Research Institute of Texas Pre doctoral fellowship training grant (RP140105) to Dennis N. Stanley M.Sc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-EF-210-08: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in Ultrasound Images Using Patch-Based Anatomical Feature

Purpose: Transrectal ultrasound (TRUS) is the standard imaging modality for the image-guided prostate-cancer interventions (e.g., biopsy and brachytherapy) due to its versatility and real-time capability. Accurate segmentation of the prostate plays a key role in biopsy needle placement, treatment planning, and motion monitoring. As ultrasound images have a relatively low signal-to-noise ratio (SNR), automatic segmentation of the prostate is difficult. However, manual segmentation during biopsy or radiation therapy can be time consuming. We are developing an automated method to address this technical challenge. Methods: The proposed segmentation method consists of two major stages: the training stage and the segmentation stage. During the training stage, patch-based anatomical features are extracted from the registered training images with patient-specific information, because these training images have been mapped to the new patient’ images, and the more informative anatomical features are selected to train the kernel support vector machine (KSVM). During the segmentation stage, the selected anatomical features are extracted from newly acquired image as the input of the well-trained KSVM and the output of this trained KSVM is the segmented prostate of this patient. Results: This segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentation. The mean volume Dice Overlap Coefficient was 89.7±2.3%, and the average surface distance was 1.52 ± 0.57 mm between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D ultrasound-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentation (gold standard). This segmentation technique could be a useful tool for image-guided interventions in prostate-cancer diagnosis and treatment. This research is supported in part by DOD PCRP Award W81XWH-13-1-0269, and National Cancer Institute (NCI) Grant CA114313.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.

60 APPLIED LIFE SCIENCES↗