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At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-225: It Is Necessary to Contouring the Brainstem On MRI Images in Radiotherapy of Head and Neck Cancer

Purpose: To analyze the error in contouring the brainstem for patients with head and neck cancer who underwent radiotherapy based on computed tomography (CT) and magnetic resonance (MR) images. Methods: 20 brain tumor and 17 nasopharyngeal cancer patients were randomly selected. Each patient underwent MR and CT scanning. For each patient, one observer contoured the brainstem on CT and MR images for 10 times, and 10 observers from five centers delineated the brainstem on CT and MR images only one time. The inter- and intra-observers volume and outline variations were compared. Results: The volumes of brainstem contoured by inter- and intra-observers on CT and MR images were similar (p>0.05). The reproducibility of contouring brainstem on MR images was better than that on CT images (p<0.05) for both inter- and intra-observer variability. The inter- and intra-observer for contouring on CT images reached mean values of 0.81±0.05 (p>0.05) and of 0.85±0.05 (p>0.05), respectively, while on MR images these respective values were 0.90±0.05 (p>0.05) and 0.92±0.04 (p>0.05). Conclusion: Contouring the brainstem on MR images was more accurate and reproducible than that on CT images. Precise information might be more helpful for protecting the brainstem radiation injury the patients whose lesion were closed to brainstem.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-C-304-04: A Compact Modular Computational Platform for Automated On-Board Imager Quality Assurance

Purpose: Traditionally, the assessment of X-ray tube output and detector positioning accuracy of on-board imagers (OBI) has been performed manually and subjectively with rulers and dosimeters, and typically takes hours to complete. In this study, we have designed a compact modular computational platform to automatically analyze OBI images acquired with in-house designed phantoms as an efficient and robust surrogate. Methods: The platform was developed as an integrated and automated image analysis-based platform using MATLAB for easy modification and maintenance. Given a set of images acquired with the in-house designed phantoms, the X-ray output accuracy was examined via cross-validation of the uniqueness and integration minimization of important image quality assessment metrics, while machine geometric and positioning accuracy were validated by utilizing pattern-recognition based image analysis techniques. Results: The platform input was a set of images of an in-house designed phantom. The total processing time is about 1–2 minutes. Based on the data acquired from three Varian Truebeam machines over the course of 3 months, the designed test validation strategy achieved higher accuracy than traditional methods. The kVp output accuracy can be verified within +/−2 kVp, the exposure accuracy within 2%, and exposure linearity with a coefficient of variation (CV) of 0.1. Sub-millimeter position accuracy was achieved for the lateral and longitudinal positioning tests, while vertical positioning accuracy within +/−2 mm was achieved. Conclusion: This new platform delivers to the radiotherapy field an automated, efficient, and stable image analysis-based procedure, for the first time, acting as a surrogate for traditional tests for LINAC OBI systems. It has great potential to facilitate OBI quality assurance (QA) with the assistance of advanced image processing techniques. In addition, it provides flexible integration of additional tests for expediting other OBI quality assurance tests, such as 2D/3D image quality, making completely automated QA possible. Research Funding from Varian Medical Systems Inc. . Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-215: Towards MR-Only Image Guided Identification of Calcifications and Brachytherapy Seeds: Application to Prostate and Breast LDR Implant Dosimetry

Purpose: To identify and analyze the appearance of calcifications and brachytherapy seeds on magnitude and phase MRI images and to investigate whether they can be distinguished from each other on corrected phase images for application to prostate and breast low dose rate (LDR) implant dosimetry. Methods: An agar-based gel phantom containing two LDR brachytherapy seeds (Advantage Pd-103, IsoAid, 0.8mm diameter, 4.5mm length) and two spherical calcifications (large: 7mm diameter and small: 4mm diameter) was constructed and imaged on a 3T Philips MR scanner using a 16-channel head coil and a susceptibility weighted imaging (SWI) sequence (2mm slices, 320mm FOV, TR/ TE= 26.5/5.3ms, 15 degree flip angle). The phase images were unwrapped and corrected using a 32×32, 2D Hanning high pass filter to remove background phase noise. Appearance of the seeds and calcifications was assessed visually and quantitatively using Osirix (http://www.osirix-viewer.com/). Results: As expected, calcifications and brachytherapy seeds appeared dark (hypointense) relative to the surrounding gel on the magnitude MRI images. The diameter of each seed without the surrounding artifact was measured to be 0.1 cm on the magnitude image, while diameters of 0.79 and 0.37 cm were measured for the larger and smaller calcifications, respectively. On the corrected phase images, the brachytherapy seeds and the calcifications appeared bright (hyperintense). The diameter of the seeds was larger on the phase images (0.17 cm) likely due to the dipole effect. Conclusion: MRI has the best soft tissue contrast for accurate organ delineation leading to most accurate implant dosimetry. This work demonstrated that phase images can potentially be useful in identifying brachytherapy seeds and calcifications in the prostate and breast due to their bright appearance, which helps in their visualization and quantification for accurate dosimetry using MR-only. Future work includes optimizing phase filters to best identify and delineate seeds and calcifications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-216: A Sequence Independent Approach for Quantification of MR Image Deformations From Brachytherapy Applicators

Purpose: MRI is increasingly used as a single imaging modality for brachytherapy treatment planning. The presence of a brachytherapy applicator may cause distortions in the images, especially at higher field strengths. Our aim is to develop a procedure to quantify these distortions theoretically for any MR-sequence and to verify the estimated deformations for clinical sequences. Methods: Image distortions due to perturbation of the B0-field are proportional to the ratio of the induced frequency shift and the read-out bandwidth of the applied sequence. By reconstructing a frequency-shift map from the phase data from a multi-echo sequence, distortions can be calculated for any MR-sequence. Verification of this method for estimating distortions was performed by acquiring images with opposing read-out directions and consequently opposing distortions. The applicator shift can be determined by rigidly matching these images. Clinically, T2W-TSE-images are used for this purpose. For pre-clinical tests, EPI-sequences with narrow read-out bandwidth (19.5–47.5Hz), consequently large distortions, were added to the set of clinical MRsequences. To quantify deformations of the Utrecht Interstitial CT/MR applicator (Elekta Brachytherapy) on a Philips Ingenia 3T MRI, pre-clinical tests were performed in a phantom with the applicator in water, followed by clinical validation. Results: Deformations observed in the narrow bandwidth EPI-images were well predicted using the frequency-shift, the latter giving an overestimation up to 30%/up to 1 voxel. For clinically applied MR-sequences distortions were well below the voxel size. In patient setup distortions determined from the frequency-shift map were at sub-voxel level (<0.7mm). Using T2W-images larger distortions were found (1–2mm). This discrepancy was caused by patient movement between/during acquisition of the T2W-images with opposing read-out directions. Conclusion: Phantom experiments demonstrated the feasibility of a clinical procedure for quantification of MR-image distortions for any MR-sequence. In a clinical set-up the distortions from a Utrecht interstitial CT/MR applicator are sub-voxel level. This work was partially funded by Elekta Brachytherpy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-260: Quantitative Image Feature Analysis of Multiphase Liver CT for Hepatocellular Carcinoma (HCC) in Radiation Therapy

Purpose: To identify the effective quantitative image features (radiomics features) for prediction of response, survival, recurrence and metastasis of hepatocellular carcinoma (HCC) in radiotherapy. Methods: Multiphase contrast enhanced liver CT images were acquired in 16 patients with HCC on pre and post radiation therapy (RT). In this study, arterial phase CT images were selected to analyze the effectiveness of image features for the prediction of treatment outcome of HCC to RT. Response evaluated by RECIST criteria, survival, local recurrence (LR), distant metastasis (DM) and liver metastasis (LM) were examined. A radiation oncologist manually delineated the tumor and normal liver on pre and post CT scans, respectively. Quantitative image features were extracted to characterize the intensity distribution (n=8), spatial patterns (texture, n=36), and shape (n=16) of the tumor and liver, respectively. Moreover, differences between pre and post image features were calculated (n=120). A total of 360 features were extracted and then analyzed by unpaired student’s t-test to rank the effectiveness of features for the prediction of response. Results: The five most effective features were selected for prediction of each outcome. Significant predictors for tumor response and survival are changes in tumor shape (Second Major Axes Length, p= 0.002; Eccentricity, p=0.0002), for LR, liver texture (Standard Deviation (SD) of High Grey Level Run Emphasis and SD of Entropy, both p=0.005) on pre and post CT images, for DM, tumor texture (SD of Entropy, p=0.01) on pre CT image and for LM, liver (Mean of Cluster Shade, p=0.004) and tumor texture (SD of Entropy, p=0.006) on pre CT image. Intensity distribution features were not significant (p>0.09). Conclusion: Quantitative CT image features were found to be potential predictors of the five endpoints of HCC in RT. This work was supported in part by the National Cancer Institute Grant R01CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-J-275: Review - Computerized PET/CT Image Analysis in the Evaluation of Tumor Response to Therapy

Purpose: To review the literature in using computerized PET/CT image analysis for the evaluation of tumor response to therapy. Methods: We reviewed and summarized more than 100 papers that used computerized image analysis techniques for the evaluation of tumor response with PET/CT. This review mainly covered four aspects: image registration, tumor segmentation, image feature extraction, and response evaluation. Results: Although rigid image registration is straightforward, it has been shown to achieve good alignment between baseline and evaluation scans. Deformable image registration has been shown to improve the alignment when complex deformable distortions occur due to tumor shrinkage, weight loss or gain, and motion. Many semi-automatic tumor segmentation methods have been developed on PET. A comparative study revealed benefits of high levels of user interaction with simultaneous visualization of CT images and PET gradients. On CT, semi-automatic methods have been developed for only tumors that show marked difference in CT attenuation between the tumor and the surrounding normal tissues. Quite a few multi-modality segmentation methods have been shown to improve accuracy compared to single-modality algorithms. Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Predictive models based on machine learning technique have been constructed for correlating selected image features to response. These models showed improved performance compared to current methods using cutoff value of a single measurement for tumor response. Conclusion: This review showed that computerized PET/CT image analysis holds great potential to improve the accuracy in evaluation of tumor response. This work was supported in part by the National Cancer Institute Grant R01CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-303-02: Achieving 4D MRI in Regular Breathing Cycle with Extended Acquisition Time of Dynamic MR Images

Purpose: The purpose of this study is to develop a technique to obtain four-dimensional (4D) magnetic resonance (MR) images that are more representative of a patient’s typical breathing cycle by utilizing an extended acquisition time while minimizing the image artifacts. Methods: The 4D MR data were acquired with the balanced steady state free precession in two-dimensional sagittal plane of view. Each slice was acquired repeatedly for about 15 s, thereby obtaining multiple images at each of the 10 phases in the respiratory cycle. This improves the probability that at least one of the images were acquired at the desired phase during a regular breathing cycle. To create optimal 4D MR images, an iterative approach was used to identify the set of images that yielded the highest slice-to-slice similarity. To assess the effectiveness of the approach, the data set was truncated into periods of 7 s (50 time points), 11 s (75 time points) and the full 15 s (100 time points). The 4D MR images were then sorted with data of the three different acquisition periods for comparison. Results: In general, the 4D MR images sorted using data from longer acquisition periods showed less mismatched artifacts. In addition, the normalized cross correlation (NCC) between slices of a 4D volume increases with increased acquisition period. The average NCC was 0.791 from the 7 s period, 0.794 from the 11 s period and 0.796 from the 15 s period. Conclusion: Our preliminary study showed that extending the acquisition time with the proposed sorting technique can improve image quality and reduce artifact presence in the 4D MR images. Data acquisition over two breathing cycles is a good trade-off between artifact reduction and scan time. This research was partially funded by the the Center for Radiation Oncology Research from UT MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-F-303-11: Implementation and Applications of Rapid, SIFT-Based Cine MR Image Binning and Region Tracking

Purpose: To develop a novel and rapid, SIFT-based algorithm for assessing feature motion on cine MR images acquired during MRI-guided radiotherapy treatments. In particular, we apply SIFT descriptors toward both partitioning cine images into respiratory states and tracking regions across frames. Methods: Among a training set of images acquired during a fraction, we densely assign SIFT descriptors to pixels within the images. We cluster these descriptors across all frames in order to produce a dictionary of trackable features. Associating the best-matching descriptors at every frame among the training images to these features, we construct motion traces for the features. We use these traces to define respiratory bins for sorting images in order to facilitate robust pixel-by-pixel tracking. Instead of applying conventional methods for identifying pixel correspondences across frames we utilize a recently-developed algorithm that derives correspondences via a matching objective for SIFT descriptors. Results: We apply these methods to a collection of lung, abdominal, and breast patients. We evaluate the procedure for respiratory binning using target sites exhibiting high-amplitude motion among 20 lung and abdominal patients. In particular, we investigate whether these methods yield minimal variation between images within a bin by perturbing the resulting image distributions among bins. Moreover, we compare the motion between averaged images across respiratory states to 4DCT data for these patients. We evaluate the algorithm for obtaining pixel correspondences between frames by tracking contours among a set of breast patients. As an initial case, we track easily-identifiable edges of lumpectomy cavities that show minimal motion over treatment. Conclusions: These SIFT-based methods reliably extract motion information from cine MR images acquired during patient treatments. While we performed our analysis retrospectively, the algorithm lends itself to prospective motion assessment. Applications of these methods include motion assessment, identifying treatment windows for gating, and determining optimal margins for treatment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-EF-204-02: Hiigh Quality and Sub-MSv Cerebral CT Perfusion Imaging

Purpose: CT Perfusion (CTP) imaging is of great importance in acute ischemic stroke management due to its potential to detect hypoperfused yet salvageable tissue and distinguish it from definitely unsalvageable tissue. However, current CTP imaging suffers from poor image quality and high radiation dose (up to 5 mSv). The purpose of this work was to demonstrate that technical innovations such as Prior Image Constrained Compressed Sensing (PICCS) have the potential to address these challenges and achieve high quality and sub-mSv CTP imaging. Methods: (1) A spatial-temporal 4D cascaded system model was developed to indentify the bottlenecks in the current CTP technology; (2) A task-based framework was developed to optimize the CTP system parameters; (3) Guided by (1) and (2), PICCS was customized for the reconstruction of CTP source images. Digital anthropomorphic perfusion phantoms, animal studies, and preliminary human subject studies were used to validate and evaluate the potentials of using these innovations to advance the CTP technology. Results: The 4D cascaded model was validated in both phantom and canine stroke models. Based upon this cascaded model, it has been discovered that, as long as the spatial resolution and noise properties of the 4D source CT images are given, the 3D MTF and NPS of the final CTP maps can be analytically derived for a given set of processing methods and parameters. The cascaded model analysis also identified that the most critical technical factor in CTP is how to acquire and reconstruct high quality source images; it has very little to do with the denoising techniques often used after parametric perfusion calculations. This explained why PICCS resulted in a five-fold dose reduction or substantial improvement in image quality. Conclusion: Technical innovations generated promising results towards achieving high quality and sub-mSv CTP imaging for reliable and safe assessment of acute ischemic strokes. K. Li, K. Niu, Y. Wu: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Image-based reconstruction of three-dimensional myocardial infarct geometry for patient-specific modeling of cardiac electrophysiology

Purpose: Accurate three-dimensional (3D) reconstruction of myocardial infarct geometry is crucial to patient-specific modeling of the heart aimed at providing therapeutic guidance in ischemic cardiomyopathy. However, myocardial infarct imaging is clinically performed using two-dimensional (2D) late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) techniques, and a method to build accurate 3D infarct reconstructions from the 2D LGE-CMR images has been lacking. The purpose of this study was to address this need. Methods: The authors developed a novel methodology to reconstruct 3D infarct geometry from segmented low-resolution (Lo-res) clinical LGE-CMR images. Their methodology employed the so-called logarithm of odds (LogOdds) function to implicitly represent the shape of the infarct in segmented image slices as LogOdds maps. These 2D maps were then interpolated into a 3D image, and the result transformed via the inverse of LogOdds to a binary image representing the 3D infarct geometry. To assess the efficacy of this method, the authors utilized 39 high-resolution (Hi-res) LGE-CMR images, including 36 in vivo acquisitions of human subjects with prior myocardial infarction and 3 ex vivo scans of canine hearts following coronary ligation to induce infarction. The infarct was manually segmented by trained experts in each slice of the Hi-res images, and the segmented data were downsampled to typical clinical resolution. The proposed method was then used to reconstruct 3D infarct geometry from the downsampled images, and the resulting reconstructions were compared with the manually segmented data. The method was extensively evaluated using metrics based on geometry as well as results of electrophysiological simulations of cardiac sinus rhythm and ventricular tachycardia in individual hearts. Several alternative reconstruction techniques were also implemented and compared with the proposed method. Results: The accuracy of the LogOdds method in reconstructing 3D infarct geometry, as measured by the Dice similarity coefficient, was 82.10% ± 6.58%, a significantly higher value than those of the alternative reconstruction methods. Among outcomes of electrophysiological simulations with infarct reconstructions generated by various methods, the simulation results corresponding to the LogOdds method showed the smallest deviation from those corresponding to the manual reconstructions, as measured by metrics based on both activation maps and pseudo-ECGs. Conclusions: The authors have developed a novel method for reconstructing 3D infarct geometry from segmented slices of Lo-res clinical 2D LGE-CMR images. This method outperformed alternative approaches in reproducing expert manual 3D reconstructions and in electrophysiological simulations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-143: Initial Assessment of Image Quality of An Integrated MR-Linac System with ACR Phantom

Purpose/Objective(s): To assess the image quality of an integrated MR-Linac system and compare with other MRI systems that are primarily used for diagnostic purposes. Materials/Methods: An ACR MRI quality control (QC) phantom was used to evaluate the image quality of a fully integrated 1.5T MRI-Linac system recently installed at our institution. This system has a new split magnet design which gives the magnetic field strength of 1.5T. All images were acquired with a set of phased-array surface coils which are designed to have minimal attention of radiation beam. The anterior coil rests on a coil holder which keeps the anterior coil’s position consistent for QA purposes. The posterior coil is imbedded in the patient couch. Multiple sets of T1, T2/PD images were acquired using the protocols as prescribed by the ACR on three different dates, ranging 3 months apart. Results: The geometric distortion are within 0.5 mm in the axial scans and within 1mm in the saggital (z-direction) scans. Slice thickness accuracy, image uniformity, ghosting ratio, high contrast detectability are comparable to other 1.5T diagnostic MRI scanners. The low-contrast object detectability are lower comparatively, which is a result of using the body array coil. Additionally, the beam’s-eye-view images (oblique coronal and saggital images) have minimal geometric distortion at all linac gantry angles tested. No observable changes or drift in image quality is found from images acquired 3 month apart. Conclusion: Despite the use of a body array surface coil, the image quality is comparable to that of an 1.5T MRI scanner and is of sufficient quality to pass the ACR MRI accreditation program. The geometric distortion of the MRI system of the integrated MR-Linac is within 1mm for an object size similar to the ACR phantom, sufficient for radiation therapy treatment purpose. The authors received corporate sponsored research grants from Elekta which is the vendor for the MR-Linac evaluated in this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-206-03: MRI Image Formation - Slice Selection, Phase Encoding, Frequency Encoding, K-Space, SNR

Magnetic resonance imaging (MRI) has become an essential part of clinical imaging due to its ability to render high soft tissue contrast. Instead of ionizing radiation, MRI use strong magnetic field, radio frequency waves and field gradients to create diagnostic useful images. It can be used to image the anatomy and also functional and physiological activities within the human body. Knowledge of the basic physical principles underlying MRI acquisition is vitally important to successful image production and proper image interpretation. This lecture will give an overview of the spin physics, imaging principle of MRI, the hardware of the MRI scanner, and various pulse sequences and their applications. It aims to provide a conceptual foundation to understand the image formation process of a clinical MRI scanner. Learning Objectives: Understand the origin of the MR signal and contrast from the spin physics level. Understand the main hardware components of a MRI scanner and their purposes Understand steps for MR image formation including spatial encoding and image reconstruction Understand the main kinds of MR pulse sequences and their characteristics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Fast Neutron Scintillator Screens for Neutron Imaging Using a Layered Polymer-Phosphor Architecture

Fast neutrons enable a nondestructive examination of dense, large, and highly attenuating samples due to their lower interaction probability compared to thermal neutrons. However, this also creates a challenge in fast neutron imaging, as the thicker sensors necessary to detect fast neutrons degrade an image’s spatial resolution due to scattering within the sensor and the indeterminate depth of interaction in the sensor. This work explores the advantages of a fast neutron imaging screen with a layered polymer-phosphor screen approach as opposed to a mixed polymer-phosphor screen typically used in fast neutron imaging. Proton recoil is the primary conversion mechanism for fast neutron imaging. Simulations showed that the recoil proton range of typical fast neutrons is approximately 200 µm, however, tests at Idaho National Laboratory revealed that the light output of these screens increased at much greater polymer thicknesses. The NECTAR fast neutron beamline at FRM II was used to test the imaging performance of layered fast neutron imaging screens. Distinguishing between the fast-neutron and γ-ray signals is a major challenge in fast neutron imaging because all fast neutron sources also produce γ-rays. A relative comparison between a control plate and the fast neutron screen was made to distinguish between a γ-ray and fast neutron signals. MCNP modeling quantified the γ-ray and fast neutron contributions to the images measured at NECTAR, which were approximately a 75% γ-ray image.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

HIGH-RESOLUTION LINEAR POLARIMETRIC IMAGING FOR THE EVENT HORIZON TELESCOPE

Images of the linear polarizations of synchrotron radiation around active galactic nuclei (AGNs) highlight their projected magnetic field lines and provide key data for understanding the physics of accretion and outflow from supermassive black holes. The highest-resolution polarimetric images of AGNs are produced with Very Long Baseline Interferometry (VLBI). Because VLBI incompletely samples the Fourier transform of the source image, any image reconstruction that fills in unmeasured spatial frequencies will not be unique and reconstruction algorithms are required. In this paper, we explore some extensions of the Maximum Entropy Method (MEM) to linear polarimetric VLBI imaging. In contrast to previous work, our polarimetric MEM algorithm combines a Stokes I imager that only uses bispectrum measurements that are immune to atmospheric phase corruption, with a joint Stokes Q and U imager that operates on robust polarimetric ratios. We demonstrate the effectiveness of our technique on 7 and 3 mm wavelength quasar observations from the VLBA and simulated 1.3 mm Event Horizon Telescope observations of Sgr A* and M87. Consistent with past studies, we find that polarimetric MEM can produce superior resolution compared to the standard CLEAN algorithm, when imaging smooth and compact source distributions. As an imaging framework, MEM is highly adaptable, allowing a range of constraints on polarization structure. Polarimetric MEM is thus an attractive choice for image reconstruction with the EHT.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Mapping of Benthic Habitats at Marine Renewable Energy Sites Using Multibeam Echosounder and Sediment Profile Imaging Technologies

Objectives/Scope: The goal of this work was to develop a consistent and semi-automated seafloor survey method for generating high-resolution, benthic habitat maps for environmental assessments and monitoring of marine renewable energy sites. Sediment profile and plan view imaging (SPI/PV) technology was combined with multibeam bathymetry and acoustic backscatter methods to demonstrate a rapid, cost-effective benthic mapping protocol. A key technical innovation of this project was the development of an image processing platform that automatically measures key features from the images. Methods: Multibeam echosounder (MBES) acoustic and SPI/PV surveys were conducted at three coastal areas off the U.S. west coast, including the PacWave South energy test site off of Newport, Oregon. Point data on physical and biological sediment conditions obtained from the SPI/PV imagery were used to efficiently ground-truth the high-resolution MBES bathymetry and backscatter mosaics. The SPI camera is an optical corer that obtains an undisturbed 21 by 15 cm, high-resolution, cross-sectional image of the sediment–water interface and upper sediment column. The plan view camera attached to the SPI camera frame captures a downward looking view of the seabed immediately before the SPI image is obtained. As part of this project, we developed a computer vision image processing platform (iSPI) that uses deep convolutional neural networks and other approaches to automatically identify and measure key features in the images, such as grain size and surface relief. Results: Detailed benthic habitat maps were generated using this mapping approach for three different marine settings. The sites mapped included a silt-dominated embayment; a sloping, nearshore, transitional very fine to coarse sand bottom; and a medium, sand-dominated continental shelf marine energy test site. In each case, acoustic and imaging surveys were completed in less than week, and detailed benthic habitat maps were generated within 60 days. The results were placed within the Coastal and Marine Ecological Classification Standard (CMECS) habitat mapping framework, and various combinations of the bathymetry, backscatter, and SPI and PV data were used to generate CMECS component maps. Novel Information: This project developed and demonstrated a repeatable and cost-effective approach for efficiently mapping benthic habitat conditions over broad areas of the seafloor by combining state-of-the-art acoustic and imaging techniques. The primary survey tools used in this project have been used previously in both the offshore renewable (wind) and oil and gas sectors to map and monitor benthic environments. This project’s innovations include 1) the focused use of high-resolution SPI/PV imagery to ground-truth acoustic mosaics, and 2) the development of a computer automated image analysis processing tool that both streamlines and standardizes the generation of data from the imagery and makes the data extraction process more cost-effective and repeatable.

13 HYDRO ENERGY↗
NASA NTRS1997

Image processing for improved eye-tracking accuracy

Video cameras provide a simple, noninvasive method for monitoring a subject's eye movements. An important concept is that of the resolution of the system, which is the smallest eye movement that can be reliably detected. While hardware systems are available that estimate direction of gaze in real-time from a video image of the pupil, such systems must limit image processing to attain real-time performance and are limited to a resolution of about 10 arc minutes. Two ways to improve resolution are discussed. The first is to improve the image processing algorithms that are used to derive an estimate. Off-line analysis of the data can improve resolution by at least one order of magnitude for images of the pupil. A second avenue by which to improve resolution is to increase the optical gain of the imaging setup (i.e., the amount of image motion produced by a given eye rotation). Ophthalmoscopic imaging of retinal blood vessels provides increased optical gain and improved immunity to small head movements but requires a highly sensitive camera. The large number of images involved in a typical experiment imposes great demands on the storage, handling, and processing of data. A major bottleneck had been the real-time digitization and storage of large amounts of video imagery, but recent developments in video compression hardware have made this problem tractable at a reasonable cost. Images of both the retina and the pupil can be analyzed successfully using a basic toolbox of image-processing routines (filtering, correlation, thresholding, etc.), which are, for the most part, well suited to implementation on vectorizing supercomputers.

NASA Discipline Space Human Factors↗
DOE OSTI2015

An imaging evaluation of the simultaneously integrated boost breast radiotherapy technique

To evaluate in-field megavoltage (MV) imaging of simultaneously integrated boost (SIB) breast fields to determine its feasibility in treatment verification for the SIB breast radiotherapy technique, and to assess whether the current-imaging protocol and treatment margins are sufficient. For nine patients undergoing SIB breast radiotherapy, in-field MV images of the SIB fields were acquired on days that regular treatment verification imaging was performed. The in-field images were matched offline according to the scar wire on digitally reconstructed radiographs. The offline image correction results were then applied to a margin recipe formula to calculate safe margins that account for random and systematic uncertainties in the position of the boost volume when an offline correction protocol has been applied. After offline assessment of the acquired images, 96% were within the tolerance set in the current department-imaging protocol. Retrospectively performing the maximum position deviations on the Eclipse™ treatment planning system demonstrated that the clinical target volume (CTV) boost received a minimum dose difference of 0.4% and a maximum dose difference of 1.4% less than planned. Furthermore, applying our results to the Van Herk margin formula to ensure that 90% of patients receive 95% of the prescribed dose, the calculated CTV margins were comparable to the current departmental procedure used. Based on the in-field boost images acquired and the feasible application of these results to the margin formula the current CTV-planning target volume margins used are appropriate for the accurate treatment of the SIB boost volume without additional imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗