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DOE OSTI2021

Single-shot x-ray phase-contrast and dark-field imaging based on coded binary phase mask

We introduce a coded-mask-based multi-contrast imaging method for high-resolution phase-contrast and dark-field imaging. The method uses a binary phase mask designed to provide an ultra-high-contrast pattern and reference-free single-shot measurement and an algorithm based on maximum-likelihood optimization and automatic differentiation to perform simultaneous reconstruction of absorption, phase, and dark-field object images. Further, we demonstrate that the method has great potential for real-time quantitative phase imaging and wavefront sensing when combined with deep learning.

Qiao, Zhi (ORCID:0000000286285320)↗

DOE OSTI2015

Threshold selection for classification of MR brain images by clustering method

Given a grey-intensity image, our method detects the optimal threshold for a suitable binarization of MR brain images. In MR brain image processing, the grey levels of pixels belonging to the object are not substantially different from the grey levels belonging to the background. Threshold optimization is an effective tool to separate objects from the background and further, in classification applications. This paper gives a detailed investigation on the selection of thresholds. Our method does not use the well-known method for binarization. Instead, we perform a simple threshold optimization which, in turn, will allow the best classification of the analyzed images into healthy and multiple sclerosis disease. The dissimilarity (or the distance between classes) has been established using the clustering method based on dendrograms. We tested our method using two classes of images: the first consists of 20 T2-weighted and 20 proton density PD-weighted scans from two healthy subjects and from two patients with multiple sclerosis. For each image and for each threshold, the number of the white pixels (or the area of white objects in binary image) has been determined. These pixel numbers represent the objects in clustering operation. The following optimum threshold values are obtained, T = 80 for PD images and T = 30 for T2w images. Each mentioned threshold separate clearly the clusters that belonging of the studied groups, healthy patient and multiple sclerosis disease.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

SU-F-J-189: A Method to Improve the Spatial Resolution of Prompt Gamma Based Compton Imaging for Proton Range Verification

Purpose: To test two new techniques, the distance-of-closest approach (DCA) and Compton line (CL) filters, developed as a means of improving the spatial resolution of Compton camera (CC) imaging. Methods: Gammas emitted from {sup 22}Na, {sup 137}Cs, and {sup 60}Co point sources were measured with a prototype 3-stage CC. The energy deposited and position of each interaction in each stage were recorded and used to calculate a “cone-of-origin” for each gamma that scattered twice in the CC. A DCA filter was developed which finds the shortest distance from the gamma’s cone-of-origin surface to the location of the gamma source. The DCA filter was applied to the data to determine the initial energy of the gamma and to remove “bad” interactions that only contribute noise to the image. Additionally, a CL filter, which removes gamma events that do not follow the theoretical predictions of the Compton scatter equation, was used to further remove “bad” interactions from the measured data. Then images were reconstructed with raw, unfiltered data, DCA filtered data, and DCA+CL filtered data and the achievable image resolution of each dataset was compared. Results: Spatial resolutions of ∼2 mm, and better than 2 mm, were achievable with the DCA and DCA+CL filtered data, respectively, compared to > 5 mm for the raw, unfiltered data. Conclusion: In many special cases in medical imaging where information about the source position may be known, such as proton radiotherapy range verification, the application of the DCA and CL filters can result in considerable improvements in the achievable spatial resolutions of Compton imaging.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

High order mitotic chromosome structure investigation using 3D microscopy

Here, the enigma of how a metaphase chromosome is constructed remains unclear with the higher order structure still under investigation. It is clear that this is a 3D structural problem requiring the development of new technologies necessary to answer this long standing mystery. This mini-review highlights new and recent, advanced 3D imaging methods that have been used to image mitotic human chromosomes. These 3D methods have advantages and limitations that are both discussed, Furthermore chromosome sample preparation and future imaging directions are also highlighted.

3D↗

DOE OSTI2016

Patient-specific quantification of image quality: An automated method for measuring spatial resolution in clinical CT images

Purpose: To develop and validate an automated technique for evaluating the spatial resolution characteristics of clinical computed tomography (CT) images. Methods: Twenty one chest and abdominopelvic clinical CT datasets were examined in this study. An algorithm was developed to extract a CT resolution index (RI) analogous to the modulation transfer function from clinical CT images by measuring the edge-spread function (ESF) across the patient’s skin. A polygon mesh of the air-skin boundary was created. The faces of the mesh were then used to measure the ESF across the air-skin interface. The ESF was differentiated to obtain the line-spread function (LSF), and the LSF was Fourier transformed to obtain the RI. The algorithm’s ability to detect the radial dependence of the RI was investigated. RIs measured with the proposed method were compared with a conventional phantom-based method across two reconstruction algorithms (FBP and iterative) using the spatial frequency at 50% RI, f{sub 50}, as the metric for comparison. Three reconstruction kernels were investigated for each reconstruction algorithm. Finally, an observer study was conducted to determine if observers could visually perceive the differences in the measured blurriness of images reconstructed with a given reconstruction method. Results: RI measurements performed with the proposed technique exhibited the expected dependencies on the image reconstruction. The measured f{sub 50} values increased with harder kernels for both FBP and iterative reconstruction. Furthermore, the proposed algorithm was able to detect the radial dependence of the RI. Patient-specific measurements of the RI were comparable to the phantom-based technique, but the patient data exhibited a large spread in the measured f{sub 50}, indicating that some datasets were blurrier than others even when the projection data were reconstructed with the same reconstruction algorithm and kernel. Results from the observer study substantiated this finding. Conclusions: Clinically informed, patient-specific spatial resolution can be measured from clinical datasets. The method is sufficiently sensitive to reflect changes in spatial resolution due to different reconstruction parameters. The method can be applied to automatically assess the spatial resolution of patient images and quantify dependencies that may not be captured in phantom data.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Combined Ventilation and Perfusion Imaging Correlates With the Dosimetric Parameters of Radiation Pneumonitis in Radiation Therapy Planning for Lung Cancer

Purpose: The purpose of this study was to prospectively investigate clinical correlations between dosimetric parameters associated with radiation pneumonitis (RP) and functional lung imaging. Methods and Materials: Functional lung imaging was performed using four-dimensional computed tomography (4D-CT) for ventilation imaging, single-photon emission computed tomography (SPECT) for perfusion imaging, or both (V/Q-matched region). Using 4D-CT, ventilation imaging was derived from a low attenuation area according to CT numbers below different thresholds (vent-860 and -910). Perfusion imaging at the 10th, 30th, 50th, and 70th percentile perfusion levels (F10-F70) were defined as the top 10%, 30%, 50%, and 70% hyperperfused normal lung, respectively. All imaging data were incorporated into a 3D planning system to evaluate correlations between RP dosimetric parameters (where fV20 is the percentage of functional lung volume irradiated with >20 Gy, or fMLD, the mean dose administered to functional lung) and the percentage of functional lung volume. Radiation pneumonitis was evaluated using Common Terminology Criteria for Adverse Events version 4.0. Statistical significance was defined as a P value of <.05. Results: Sixty patients who underwent curative radiation therapy were enrolled (48 patients for non-small cell lung cancer, and 12 patients for small cell lung cancer). Grades 1, 2, and ≥3 RP were observed in 16, 44, and 6 patients, respectively. Significant correlations were observed between the percentage of functional lung volume and fV20 (r=0.4475 in vent-860 and 0.3508 in F30) or fMLD (r=0.4701 in vent-860 and 0.3128 in F30) in patients with grade ≥2 RP. F30∩vent-860 results exhibited stronger correlations with fV20 and fMLD in patients with grade ≥2 (r=0.5509 in fV20 and 0.5320 in fMLD) and grade ≥3 RP (r=0.8770 in fV20 and 0.8518 in fMLD). Conclusions: RP dosimetric parameters correlated significantly with functional lung imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

High-resolution source imaging and moment tensor estimation of acoustic emissions during brittle creep of basalt undergoing carbonation

SUMMARY As the high-frequency analogue to field-scale earthquakes, acoustic emissions (AEs) provide a valuable complement to study rock deformation mechanisms. During the load-stepping creep experiments with CO2-saturated water injection into a basaltic sample from Carbfix site in Iceland, 8791 AE events are detected by at least one of the seven piezoelectric sensors. Here, we apply a cross-correlation-based source imaging method, called geometric-mean reverse-time migration (GmRTM) to locate those AE events. Besides the attractive picking-free feature shared with other waveform-based methods (e.g. time-reversal imaging), GmRTM is advantageous in generating high-resolution source images with reduced imaging artefacts, especially for experiments with relatively sparse receivers. In general, the imaged AE locations are found to be scattered across the sample, suggesting a complicated fracture network rather than a well-defined major shear fracture plane, in agreement with X-ray computed tomography imaging results after retrieval of samples from the deformation apparatus. Clustering the events in space and time using the nearest-neighbour approach revealed a group of ‘repeaters’, which are spatially co-located over an elongated period of time and likely indicate crack, or shear band growth. Furthermore, we select 2196 AE events with high signal-to-noise-ratio (SNR) and conduct moment tensor estimation using the adjoint (backpropagated) strain tensor fields at the locations of AE sources. The resulting AE locations and focal mechanisms support our previously assertion that creep of basalt at the experimental conditions is accommodated dominantly by distributed microcracking.

58 GEOSCIENCES↗

DOE OSTI2016

Sci-Fri PM: Radiation Therapy, Planning, Imaging, and Special Techniques - 11: Quantification of chest wall motion during deep inspiration breast hold treatments using cine EPID images and a physics based algorithm

Purpose: This work presents an algorithm used to quantify intra-fraction motion for patients treated using deep inspiration breath hold (DIBH). The algorithm quantifies the position of the chest wall in breast tangent fields using electronic portal images. Methods: The algorithm assumes that image profiles, taken along a direction perpendicular to the medial border of the field, follow a monotonically and smooth decreasing function. This assumption is invalid in the presence of lung and can be used to calculate chest wall position. The algorithm was validated by determining the position of the chest wall for varying field edge positions in portal images of a thoracic phantom. The algorithm was used to quantify intra-fraction motion in cine images for 7 patients treated with DIBH. Results: Phantom results show that changes in the distance between chest wall and field edge were accurate within 0.1 mm on average. For a fixed field edge, the algorithm calculates the position of the chest wall with a 0.2 mm standard deviation. Intra-fraction motion for DIBH patients was within 1 mm 91.4% of the time and within 1.5 mm 97.9% of the time. The maximum intra-fraction motion was 3.0 mm. Conclusions: A physics based algorithm was developed and can be used to quantify the position of chest wall irradiated in tangent portal images with an accuracy of 0.1 mm and precision of 0.6 mm. Intra-fraction motion for patients treated with DIBH at our clinic is less than 3 mm.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2013

Herschel Observations of the Debris Disc Around HIP 92043

Context: Typical debris discs are composed of particles ranging from several micron sized dust grains to kilometer-sized asteroidal bodies, and their infrared emission peaks at wavelengths 60-100 microns. Recent Herschel DUNES (Dust Around Nearby Stars) observations have identified several debris discs around nearby Sun-like stars (F, G and K spectral type) with significant excess emission only at 160 microns. Aims: We observed HIP 92043 (110 Her, HD 173667) at far-infrared and sub-millimetre wavelengths with Herschel PACS (Photodetector Array Camera and Spectrometer) and SPIRE (Spectral and Photometric Imaging Receiver).Identification of the presence of excess emission from HIP 92043 and the origin and physical properties of any excess was undertaken through analysis of its spectral energy distribution (SED) and the PACS images. Methods: The PACS and SPIRE images were produced using the HIPE (Herschel Interactive Processing Environment) photProject map maker routine. Fluxes were measured using aperture photometry. A stellar photosphere model was scaled to optical and near infrared photometry and subtracted from the far-infared and sub-mm fluxes to determine the presence of excess emission. Source radial profiles were fitted using a 2D Gaussian and compared to a PSF (Point Spread Function) model based on Herschel observations of alpha Boo to check for extended emission. Results: Clear excess emission from HIP 92043 was observed at 70 and 100 microns. Marginal excess was observed at 160 and 250 microns.Analysis of the images reveals that the source is extended at 160 microns. A fit to the source SED is inconsistent with a photosphere and single temperature black body. Conclusions: The excess emission from HIP 92043 is consistent with the presence of an unresolved circumstellar debris disc at 70and 100 microns, with low probability of background contamination. The extended 160 micron emission may be interpreted as an additional cold component to the debris disc or as the result of background contamination along the line of sight. The nature of the 160 micron excess cannot be determined absolutely from the available data, but we favour a debris disc interpretation, drawing parallels with previously identified cold disc sources in the DUNES sample.

debris discs↗

DOE OSTI2016

Single-energy computed tomography-based pulmonary perfusion imaging: Proof-of-principle in a canine model

Purpose: Radiotherapy (RT) that selectively avoids irradiating highly functional lung regions may reduce pulmonary toxicity, which is substantial in lung cancer RT. Single-energy computed tomography (CT) pulmonary perfusion imaging has several advantages (e.g., higher resolution) over other modalities and has great potential for widespread clinical implementation, particularly in RT. The purpose of this study was to establish proof-of-principle for single-energy CT perfusion imaging. Methods: Single-energy CT perfusion imaging is based on the following: (1) acquisition of end-inspiratory breath-hold CT scans before and after intravenous injection of iodinated contrast agents, (2) deformable image registration (DIR) for spatial mapping of those two CT image data sets, and (3) subtraction of the precontrast image data set from the postcontrast image data set, yielding a map of regional Hounsfield unit (HU) enhancement, a surrogate for regional perfusion. In a protocol approved by the institutional animal care and use committee, the authors acquired CT scans in the prone position for a total of 14 anesthetized canines (seven canines with normal lungs and seven canines with diseased lungs). The elastix algorithm was used for DIR. The accuracy of DIR was evaluated based on the target registration error (TRE) of 50 anatomic pulmonary landmarks per subject for 10 randomly selected subjects as well as on singularities (i.e., regions where the displacement vector field is not bijective). Prior to perfusion computation, HUs of the precontrast end-inspiratory image were corrected for variation in the lung inflation level between the precontrast and postcontrast end-inspiratory CT scans, using a model built from two additional precontrast CT scans at end-expiration and midinspiration. The authors also assessed spatial heterogeneity and gravitationally directed gradients of regional perfusion for normal lung subjects and diseased lung subjects using a two-sample two-tailed t-test. Results: The mean TRE (and standard deviation) was 0.6 ± 0.7 mm (smaller than the voxel dimension) for DIR between pre contrast and postcontrast end-inspiratory CT image data sets. No singularities were observed in the displacement vector fields. The mean HU enhancement (and standard deviation) was 37.3 ± 10.5 HU for normal lung subjects and 30.7 ± 13.5 HU for diseased lung subjects. Spatial heterogeneity of regional perfusion was found to be higher for diseased lung subjects than for normal lung subjects, i.e., a mean coefficient of variation of 2.06 vs 1.59 (p = 0.07). The average gravitationally directed gradient was strong and significant (R{sup 2} = 0.99, p < 0.01) for normal lung dogs, whereas it was moderate and nonsignificant (R{sup 2} = 0.61, p = 0.12) for diseased lung dogs. Conclusions: This canine study demonstrated the accuracy of DIR with subvoxel TREs on average, higher spatial heterogeneity of regional perfusion for diseased lung subjects than for normal lung subjects, and a strong gravitationally directed gradient for normal lung subjects, providing proof-of-principle for single-energy CT pulmonary perfusion imaging. Further studies such as comparison with other perfusion imaging modalities will be necessary to validate the physiological significance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

WE-DE-BRA-09: Fast Megavoltage CT Imaging with Rapid Scan Time and Low Imaging Dose in Helical Tomotherapy

Purpose: Megavoltage computed tomography (MVCT) imaging has been widely used for daily patient setup with helical tomotherapy (HT). One drawback of MVCT is its very long imaging time, owing to slow couch speed. The purpose of this study was to develop an MVCT imaging method allowing faster couch speeds, and to assess its accuracy for image guidance for HT. Methods: Three cadavers (mimicking closest physiological and physical system of patients) were scanned four times with couch speeds of 1, 2, 3, and 4 mm/s. The resulting MVCT images were reconstructed using an iterative reconstruction (IR) algorithm. The MVCT images were registered with kilovoltage CT images, and the registration errors were compared with the errors with conventional filtered back projection (FBP) algorithm. Moreover, the fast MVCT imaging was tested in three cases of total marrow irradiation as a clinical trial. Results: Three-dimensional registration errors of the MVCT images reconstructed with the IR algorithm were significantly smaller (p < 0.05) than the errors of images reconstructed with the FBP algorithm at fast couch speeds (3, 4 mm/s). The scan time and imaging dose at a speed of 4 mm/s were reduced to 30% of those from a conventional coarse mode scan. For the patient imaging, a limited number of conventional MVCT (1.2 mm/s) and fast MVCT (3 mm/s) reveals acceptable reduced imaging time and dose able to use for anatomical registration. Conclusion: Fast MVCT with IR algorithm maybe clinically feasible alternative for rapid 3D patient localization. This technique may also be useful for calculating daily dose distributions or organ motion analyses in HT treatment over a wide area.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2001

One-Dimensional Spontaneous Raman Measurements Made in a Gas Turbine Combustor

The NASA Glenn Research Center and the aerospace industry are designing and testing low-emission combustor concepts to build the next generation of cleaner, more fuel efficient aircraft powerplants. These combustors will operate at much higher inlet temperatures and at pressures that are up to 3 to 5 times greater than combustors in the current fleet. From a test and analysis viewpoint, there is an increasing need for measurements from these combustors that are nonintrusive, simultaneous, multipoint, and more quantitative. Glenn researchers have developed several unique test facilities (refs. 1 and 2) that allow, for the first time, optical interrogation of combustor flow fields, including subcomponent performance, at pressures ranging from 1 to 60 bar (1 to 60 atm). Experiments conducted at Glenn are the first application of a visible laser-pumped, one-dimensional, spontaneous Raman-scattering technique to analyze the flow in a high-pressure, advanced-concept fuel injector at pressures thus far reaching 12 bar (12 atm). This technique offers a complementary method to the existing two- and three-dimensional imaging methods used, such as planar laser-induced fluorescence. Raman measurements benefit from the fact that the signal from each species is a linear function of its density, and the relative densities of all major species can be acquired simultaneously with good precision. The Raman method has the added potential to calibrate multidimensional measurements by providing an independent measurement of species number-densities at known points within the planar laser-induced fluorescence images. The visible Raman method is similar to an ultraviolet-Raman technique first tried in the same test facility (ref. 3). However, the visible method did not suffer from the ultraviolet technique's fuel-born polycyclic aromatic hydrocarbon fluorescence interferences.

DeGroot, Wilhelmus A.↗

DOE OSTI2015

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET image and substantially enhanced image quality of low-dose brain [{sup 18}F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [{sup 18}F]FDG PET image using low-dose brain [{sup 18}F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [{sup 18}F]FDG PET can be well-predicted using MRI and low-dose brain [{sup 18}F]FDG PET.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Validation of a method for in vivo 3D dose reconstruction for IMRT and VMAT treatments using on-treatment EPID images and a model-based forward-calculation algorithm

Purpose: Radiation treatments are trending toward delivering higher doses per fraction under stereotactic radiosurgery and hypofractionated treatment regimens. There is a need for accurate 3D in vivo patient dose verification using electronic portal imaging device (EPID) measurements. This work presents a model-based technique to compute full three-dimensional patient dose reconstructed from on-treatment EPID portal images (i.e., transmission images). Methods: EPID dose is converted to incident fluence entering the patient using a series of steps which include converting measured EPID dose to fluence at the detector plane and then back-projecting the primary source component of the EPID fluence upstream of the patient. Incident fluence is then recombined with predicted extra-focal fluence and used to calculate 3D patient dose via a collapsed-cone convolution method. This method is implemented in an iterative manner, although in practice it provides accurate results in a single iteration. The robustness of the dose reconstruction technique is demonstrated with several simple slab phantom and nine anthropomorphic phantom cases. Prostate, head and neck, and lung treatments are all included as well as a range of delivery techniques including VMAT and dynamic intensity modulated radiation therapy (IMRT). Results: Results indicate that the patient dose reconstruction algorithm compares well with treatment planning system computed doses for controlled test situations. For simple phantom and square field tests, agreement was excellent with a 2%/2 mm 3D chi pass rate ≥98.9%. On anthropomorphic phantoms, the 2%/2 mm 3D chi pass rates ranged from 79.9% to 99.9% in the planning target volume (PTV) region and 96.5% to 100% in the low dose region (>20% of prescription, excluding PTV and skin build-up region). Conclusions: An algorithm to reconstruct delivered patient 3D doses from EPID exit dosimetry measurements was presented. The method was applied to phantom and patient data sets, as well as for dynamic IMRT and VMAT delivery techniques. Results indicate that the EPID dose reconstruction algorithm presented in this work is suitable for clinical implementation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Integrated imaging assembly and method for using

Certain disclosed embodiments concern an integrated imaging system that combined light-sheet microscopy, which enables considerable speed and phototoxicity gains, with quantitative-phase imaging. A method for using such imaging systems also is disclosed. In an exemplary embodiment, an integrated imaging system was used for multivariate investigation of live-cells in microfluidics.

Vasdekis, Andreas E.↗

DOE OSTI2016

TU-FG-209-12: Treatment Site and View Recognition in X-Ray Images with Hierarchical Multiclass Recognition Models

Purpose: To investigate an approach of automatically recognizing anatomical sites and imaging views (the orientation of the image acquisition) in 2D X-ray images. Methods: A hierarchical (binary tree) multiclass recognition model was developed to recognize the treatment sites and views in x-ray images. From top to bottom of the tree, the treatment sites are grouped hierarchically from more general to more specific. Each node in the hierarchical model was designed to assign images to one of two categories of anatomical sites. The binary image classification function of each node in the hierarchical model is implemented by using a PCA transformation and a support vector machine (SVM) model. The optimal PCA transformation matrices and SVM models are obtained by learning from a set of sample images. Alternatives of the hierarchical model were developed to support three scenarios of site recognition that may happen in radiotherapy clinics, including two or one X-ray images with or without view information. The performance of the approach was tested with images of 120 patients from six treatment sites – brain, head-neck, breast, lung, abdomen and pelvis – with 20 patients per site and two views (AP and RT) per patient. Results: Given two images in known orthogonal views (AP and RT), the hierarchical model achieved a 99% average F1 score to recognize the six sites. Site specific view recognition models have 100 percent accuracy. The computation time to process a new patient case (preprocessing, site and view recognition) is 0.02 seconds. Conclusion: The proposed hierarchical model of site and view recognition is effective and computationally efficient. It could be useful to automatically and independently confirm the treatment sites and views in daily setup x-ray 2D images. It could also be applied to guide subsequent image processing tasks, e.g. site and view dependent contrast enhancement and image registration. The senior author received research grants from ViewRay Inc. and Varian Medical System.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-FG-209-02: Development of a Virtual Breast Phantom From a Multi-Modality Perspective

This symposium will review recent advances in the simulation methods for evaluation of novel breast imaging systems – the subject of AAPM Task Group TG234. Our focus will be on the various approaches to development and validation of software anthropomorphic phantoms and their use in the statistical assessment of novel imaging systems using such phantoms along with computational models for the x-ray image formation process. Due to the dynamic development and complex design of modern medical imaging systems, the simulation of anatomical structures, image acquisition modalities, and the image perception and analysis offers substantial benefits of reduced cost, duration, and radiation exposure, as well as the known ground-truth and wide variability in simulated anatomies. For these reasons, Virtual Clinical Trials (VCTs) have been increasingly accepted as a viable tool for preclinical assessment of x-ray and other breast imaging methods. Activities of TG234 have encompassed the optimization of protocols for simulation studies, including phantom specifications, the simulated data representation, models of the imaging process, and statistical assessment of simulated images. The symposium will discuss the state-of-the-science of VCTs for novel breast imaging systems, emphasizing recent developments and future directions. Presentations will discuss virtual phantoms for intermodality breast imaging performance comparisons, extension of the breast anatomy simulation to the cellular level, optimized integration of the simulated imaging chain, and the novel directions in the observer models design. Learning Objectives: Review novel results in developing and applying virtual phantoms for inter-modality breast imaging performance comparisons; Discuss the efforts to extend the computer simulation of breast anatomy and pathology to the cellular level; Summarize the state of the science in optimized integration of modules in the simulated imaging chain; Compare novel directions in the design of observer models for task based validation of imaging systems. PB: Research funding support from the NIH, NSF, and Komen for the Cure; NIH funded collaboration with Barco, Inc. and Hologic, Inc.; Consultant to Delaware State Univ. and NCCPM, UK. AA: Employed at Barco Healthcare.; P. Bakic, NIH: (NIGMS P20 #GM103446, NCI R01 #CA154444); M. Das, NIH Research grants.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

MO-FG-209-05: Towards a Feature-Based Anthropomorphic Model Observer

60 APPLIED LIFE SCIENCES↗