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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Make the Fastest Faster: Importance Mask Synthesis for Interactive Volume Visualization using Reconstruction Neural Networks

Visualizing a large-scale volumetric dataset with high resolution is challenging due to the substantial computational time and space complexity. Recent deep learning-based image inpainting methods significantly improve rendering latency by reconstructing a high-resolution image for visualization in constant time on GPU from a partially rendered image where only a portion of pixels go through the expensive rendering pipeline. However, existing solutions need to render every pixel of either a predefined regular sampling pattern or an irregular sample pattern predicted from a low-resolution image rendering. Both methods require a significant amount of expensive pixel-level rendering. In this work, we provide Importance Mask Learning (IML) and Synthesis (IMS) networks, which are the first attempts to directly synthesize important regions of the regular sampling pattern from the user’s view parameters, to further minimize the number of pixels to render by jointly considering the dataset, user behavior, and the downstream reconstruction neural network. Our solution is a unified framework to handle various types of inpainting methods through the proposed differentiable compaction/decompaction layers. Experiments show our method can further improve the overall rendering latency of state-of-the-art volume visualization methods using reconstruction neural network for free when rendering scientific volumetric datasets. Our method can also directly optimize the off-the-shelf pre-trained reconstruction neural networks without elongated retraining.

Large-scale data↗
DOE OSTI2015

A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform

Purpose: In digital x-ray radiography, an antiscatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the antiscatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded. In this study, a new stationary gridline suppression method is designed to preserve more of the useful information. Methods: The method is as follows. The input image is first recursively decomposed into several smaller subimages using a multiscale 2D discrete wavelet transform. The decomposition process stops when the gridline signal is found to be greater than a threshold in one or several of these subimages using a gridline detection module. An automatic Gaussian band-stop filter is then applied to the detected subimages to remove the gridline signal. Finally, the restored image is achieved using the corresponding 2D inverse discrete wavelet transform. Results: The processed images show that the proposed method can remove the gridline signal efficiently while maintaining the image details. The spectra of a 1D Fourier transform of the processed images demonstrate that, compared with some existing gridline removal methods, the proposed method has better information preservation after the removal of the gridline artifacts. Additionally, the performance speed is relatively high. Conclusions: The experimental results demonstrate the efficiency of the proposed method. Compared with some existing gridline removal methods, the proposed method can preserve more information within an acceptable execution time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A relative radiometric correction method for airborne SWIR hyperspectral image using the side-slither technique

Stripe noise still remains in airborne short-wave infrared (SWIR) hyperspectral (HS) images after laboratory calibration due to the stray light of HS imager, nonlinear response of infrared focal plane array, and the distinct difference of equivalent color temperature between the integrating sphere and the sun. It is difficult to get a sun-like radiation source, and we apply the side-slither technique for relative radiometric correction of HS images. The calibration data corresponding to different irradiance were obtained by the side-slither technique of imager. Then, the two-point multi-section method is used for relative radiometric correction of HS images. This paper presents the principle, the experimental results, and the analysis of the proposed method. To validate the effectiveness of this method, it was compared with other methods and evaluated by quantitative quality indices. The results reveal that this method has a good performance in relative radiometric correction of HS image and is superior to the laboratory calibration based on integrating sphere. Consequently, the proposed method can successfully eliminate the adverse effect caused by the difference of equivalent color temperature between radiation sources, and also can improve the accuracy of HS applications such as absolute radiation correction and target recognition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Effective Cloud Detection and Segmentation Using a Gradient-Based Algorithm for Satellite Imagery: Application to Improve PERSIANN-CCS

The effective identification of clouds and monitoring of their evolution are important toward more accurate quantitative precipitation estimation and forecast. In this study, a new gradient-based cloud-image segmentation algorithm is developed using image processing techniques. This method integrates morphological image gradient magnitudes to separate cloud systems and patches boundaries. A varying scale kernel is implemented to reduce the sensitivity of image segmentation to noise and to capture objects with various finenesses of the edges in remote sensing images. The proposed method is flexible and extendable from single to multispectral imagery. Case studies were carried out to validate the algorithm by applying the proposed segmentation algorithm to synthetic radiances for channels of the Geostationary Operational Environmental Satellite ( GOES-16) simulated by a high-resolution weather prediction model. The proposed method compares favorably with the existing cloud-patch-based segmentation technique implemented in the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall retrieval algorithm. Evaluation of event-based images indicates that the proposed algorithm has potentials comparing to the conventional segmentation technique used in PERSIANN-CCS to improve rain detection and estimation skills with an accuracy rate of up to 98% in identifying cloud regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Experimental study on flow characterization of a rectangular spouted bed by image processing

Systematic image processing methods are applied to characterize gas-solid flow under different operating conditions in a 30.2 mm x 101.6 mm rectangular spouted bed. Geldart D particles are imaged using a highspeed video camera. Superficial gas velocity, initial bed height, and nozzle size are investigated as influence factors. By applying adaptive thresholding and logical operation to the video frames, the original color images are transformed into binary images exposing detailed boundary information. By analyzing the binary image using a self-developed algorithm in combination with mask operations, the bed height is successfully determined, through which the variation of the bed expansion ratio with superficial gas velocity can be obtained. Additionally, the application of image morphological operations, i.e. dilation and erosion on the binarized images ensures the accurate identification of the contours of the jet and fountain so that the jet and fountain heights can be determined. Based on the image processing methods, the variation of bed expansion ratio, jet height and fountain height with the three influence factors are discussed. The current study highlights the application of image analysis in investigating the flow characterization and obtaining more hydrodynamic information in a rectangular spouted bed.

42 ENGINEERING↗
NASA NTRS1980

Enhanced orbital geochemical images by the Laplacian subtraction method

Orbital geochemical studies of the moon based on X-ray fluorescence and gamma-ray spectroscopy have been successful. There are, however, difficulties if geologic units or other features to be investigated are too small. Investigations have been conducted with the objective to improve with the aid of image enhancement methods both spatial resolution and contrast for the geochemical experiments. A description is provided of the Laplacian subtraction method of enhancement. It was found that the application of a least-squares version of this method to the Mg/Al ratios obtained by orbital X-ray fluorescence improved geochemical images considerably. The spatial resolution increased by about a factor of 2 and the contrast also increased. The Laplacian of an image can also be used to detect very small 'hot' or 'cold' spots in an image.

Schonfeld, E.↗
DOE OSTI2021

Physics‐based iterative reconstruction for dual‐source and flying focal spot computed tomography

Purpose For single‐source helical Computed Tomography (CT), both Filtered‐Back Projection (FBP) and statistical iterative reconstruction have been investigated. However, for dual‐source CT with flying focal spot (DS‐FFS CT), a statistical iterative reconstruction that accurately models the scanner geometry and acquisition physics remains unknown to researchers. Therefore, our purpose is to present a novel physics‐based iterative reconstruction method for DS‐FFS CT and assess its image quality. Methods Our algorithm uses precise physics models to reconstruct from the native cone‐beam geometry and interleaved dual‐source helical trajectory of a DS‐FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture. In addition, we design forward system models to compute the locations of deflected focal spots, the dimension, and sensitivity of voxels and detector units, as well as the length of intersection between x‐rays and voxels. The forward system models further represent the coordinated movement between the dual sources by computing their x‐ray coverage gaps and overlaps at an arbitrary helical pitch. With the above models, we reconstruct images by an advanced Consensus Equilibrium (CE) numerical method to compute the maximum a posteriori estimate to a joint optimization problem that simultaneously fits all models. Results We compared our reconstruction with Siemens ADMIRE, which is the clinical standard hybrid iterative reconstruction (IR) method for DS‐FFS CT, in terms of spatial resolution, noise profile, and image artifacts through both phantoms and clinical scan datasets. Experiments show that our reconstruction has a higher spatial resolution, with a Task‐Based Modulation Transfer Function (MTF task ) consistently higher than the clinical standard hybrid IR. In addition, our reconstruction shows a reduced magnitude of image undersampling artifacts than the clinical standard. Conclusions By modeling a precise geometry and avoiding data rebinning or interpolation, our physics‐based reconstruction achieves a higher spatial resolution and fewer image artifacts with smaller magnitude than the clinical standard hybrid IR.

Wang, Xiao↗
NASA NTRS1974

A simple method for the generation of organ and vessel contours from roentgenographic or fluoroscopic images

A simple method for outlining or contouring any area defined by a change in film density or fluoroscopic screen intensity is described. The entire process, except for the positioning of an electronic window, is accomplished using a small computer having appropriate softwave. The electronic window is operator positioned over the area to be processed. The only requirement is that the window be large enough to encompass the total area to be considered.

Newell, J. D.↗
NASA NTRS1993

Telescope for x ray and gamma ray studies in astrophysics

Imaging of x-rays has been achieved by various methods in astrophysics, nuclear physics, medicine, and material science. A new method for imaging x-ray and gamma-ray sources avoids the limitations of previously used imaging devices. Images are formed in optical wavelengths by using mirrors or lenses to reflect and refract the incoming photons. High energy x-ray and gamma-ray photons cannot be reflected except at grazing angles and pass through lenses without being refracted. Therefore, different methods must be used to image x-ray and gamma-ray sources. Techniques using total absorption, or shadow casting, can provide images in x-rays and gamma-rays. This new method uses a coder made of a pair of Fresnel zone plates and a detector consisting of a matrix of CsI scintillators and photodiodes. The Fresnel zone plates produce Moire patterns when illuminated by an off-axis source. These Moire patterns are deconvolved using a stepped sine wave fitting or an inverse Fourier transform. This type of coder provides the capability of an instantaneous image with sub-arcminute resolution while using a detector with only a coarse position-sensitivity. A matrix of the CsI/photodiode detector elements provides the necessary coarse position-sensitivity. The CsI/photodiode detector also allows good energy resolution. This imaging system provides advantages over previously used imaging devices in both performance and efficiency.

Weaver, W. D.↗
DOE OSTI2015

SU-E-T-398: Evaluation of Radiobiological Parameters Using Serial Tumor Imaging During Radiotherapy as An Inverse Ill-Posed Problem

Purpose: Combination of serial tumor imaging with radiobiological modeling can provide more accurate information on the nature of treatment response and what underlies resistance. The purpose of this article is to improve the algorithms related to imaging-based radiobilogical modeling of tumor response. Methods: Serial imaging of tumor response to radiation therapy represents a sum of tumor cell sensitivity, tumor growth rates, and the rate of cell loss which are not separated explicitly. Accurate treatment response assessment would require separation of these radiobiological determinants of treatment response because they define tumor control probability. We show that the problem of reconstruction of radiobiological parameters from serial imaging data can be considered as inverse ill-posed problem described by the Fredholm integral equation of the first kind because it is governed by a sum of several exponential processes. Therefore, the parameter reconstruction can be solved using regularization methods. Results: To study the reconstruction problem, we used a set of serial CT imaging data for the head and neck cancer and a two-level cell population model of tumor response which separates the entire tumor cell population in two subpopulations of viable and lethally damage cells. The reconstruction was done using a least squared objective function and a simulated annealing algorithm. Using in vitro data for radiobiological parameters as reference data, we shown that the reconstructed values of cell surviving fractions and potential doubling time exhibit non-physical fluctuations if no stabilization algorithms are applied. The variational regularization allowed us to obtain statistical distribution for cell surviving fractions and cell number doubling times comparable to in vitro data. Conclusion: Our results indicate that using variational regularization can increase the number of free parameters in the model and open the way to development of more advanced algorithms which take into account tumor heterogeneity, for example, related to hypoxia.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-207-12: Impact of Anatomical Noise On Detection Performance of Microcalcifications in Multi-Contrast Breast Imaging

Purpose: The anatomical noise power spectra (NPS) for differential phase contrast (DPC) and dark field (DF) imaging have recently been characterized using a power-law model with two parameters, alpha and beta, an innovative extension to the methodology used in x-ray attenuation based breast imaging such as mammography, DBT, or cone-beam CT. Beta values of 3.6, 2.6, and 1.3 have been measured for absorption, DPC, and DF respectively for cadaver breasts imaged in the coronal plane; these dramatic differences should be reflected in their detection performance. The purpose of this study was to determine the impact of anatomical noise on breast calcification detection and compare the detection performance of the three contrast mechanisms of a multi-contrast x-ray imaging system. Methods: In our studies, a calcification image object was segmented out of the multi-contrast images of a cadaver breast specimen. 50 measured total NPS were measured from breast cadavers directly. The ideal model observer detectability was calculated for a range of doses (5–100%) and a range of calcification sizes (diameter = 0.25–2.5 mm). Results: Overall we found the highest average detectability corresponded to DPC imaging (7.4 for 1 mm calc.), with DF the next highest (3.8 for 1 mm calc.), and absorption the lowest (3.2 for 1 mm calc.). However, absorption imaging also showed the slowest dependence on dose of the three modalities due to the significant anatomical noise. DPC showed a peak detectability for calcifications ∼1.25 mm in diameter, DF showed a peak for calcifications around 0.75 mm in diameter, and absorption imaging had no such peak in the range explored. Conclusion: Understanding imaging performance for DPC and DF is critical to transition these modalities to the clinic. The results presented here offer new insight into how these modalities complement absorption imaging to maximize the likelihood of detecting early breast cancers. J. Garrett, Y. Ge, K. Li: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-206-03: Promises and Challenges of Benchtop X-Ray Fluorescence CT (XFCT) for Quantitative in Vivo Imaging

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffers from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Progressive CPU Volume Rendering with Sample Accumulation

Here, we present a new method for progressive volume rendering by accumulating object-space samples over successively rendered frames. Existing methods for progressive refinement either use image space methods or average pixels over frames, which can blur features or integrate incorrectly with respect to depth. Our approach stores samples along each ray, accumulates new samples each frame into a buffer, and progressively interleaves and integrates these samples. Though this process requires additional memory, it ensures interactivity and is well suited for CPU architectures with large memory and cache. This approach also extends well to distributed rendering in cluster environments. We implement this technique in Intel’s open source OSPRay CPU ray tracing framework and demonstrate that it is particularly useful for rendering volumetric data with costly sampling functions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Lossless compression of AVIRIS data: Comparison of methods and instrument constraints

A family of lossless compression methods, allowing exact image reconstruction, are evaluated for compressing Airborne Visible/Infrared Imaging Spectrometers (AVIRIS) image data. The methods are used on Differential Pulse Code Modulation (DPCM). The compressed data have an entropy of order 6 bits/pixel. A theoretical model indicates that significantly better lossless compression is unlikely to be achieved because of limits caused by the noise in the AVIRIS channels. AVIRIS data differ from data produced by other visible/near-infrared sensors, such as LANDSAT-TM or SPOT, in several ways. Firstly, the data are recorded at a greater resolution (12 bits, though packed into 16-bit words). Secondly, the spectral channels are relatively narrow and provide continuous coverage of the spectrum so that the data in adjacent channels are generally highly correlated. Thirdly, the noise characteristics of the AVIRIS are defined by the channels' Noise Equivalent Radiances (NER's), and these NER's show that, at some wavelengths, the least significant 5 or 6 bits of data are essentially noise.

Roger, R. E.↗
DOE OSTI2019

Multi-scale fusion algorithm of intensity and polarization-difference images based on edge information enhancement

To better integrate complementary and redundant information from different source images, improve the edge information, and facilitate the target detection. A multi-scale fusion algorithm of intensity and polarization-difference (PD) images based on edge information enhancement is proposed. Firstly, intensity images are obtained by the polarization information analysis method. PD images are obtained by the adaptive polarization-difference imaging approach based on the principle of minimum mutual information. Secondly, guided filter, affine transformations and Block-Matching and 3D filtering are embedded in visibility enhancement to improve the intensity and PD images. Thirdly, the two images are decomposed into high-frequency and low-frequency images by the dual-tree complex wavelet transform (DT-CWT). The high-frequency and low-frequency images are fused by the fusion rules based on edge detection and the regional variance matching degree respectively. Finally, the fusion image is obtained by the inverse DT-CWT. Experimental results demonstrate that fusion images of the proposed algorithm are significantly improved in information entropy, average gradient, and spatial frequency. Compared with the existing methods, it can achieve a better edge enhancement for images in a turbid medium.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1983

Image sharpening for mixed spatial and spectral resolution satellite systems

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

Hallada, W. A.↗
DOE OSTI2020

SnowPac : a multiscale cubic B-spline wavelet compressor for astronomical images

ABSTRACT As more advanced and complex survey telescopes are developed, the size and scale of data being captured grows at increasing rates. Across various domains, data compression through wavelets has enabled the reduction of data size and increase in computation efficiency. In this paper, we provide qualitative and quantitative tests of a new wavelet-based image compression method compared against the current standard for astronomical images. The analysis is improved by making use of state-of-the-art object detection systems to accurately measure the impact of the compression. We find that a combination of lossy wavelet-based methods, efficient quantization, and lossless dictionary compressors can preserve up to 98 per cent of astronomical objects at a 10:1 compression ratio. This significant reduction in file size also preserves astronomical object properties better than existing methods. These methods help further reduce future workloads for image-heavy processing pipelines.

Pulido, Jesus↗
DOE OSTI2015

Characterization of the onboard imaging unit for the first clinical magnetic resonance image guided radiation therapy system

Purpose: To characterize the performance of the onboard imaging unit for the first clinical magnetic resonance image guided radiation therapy (MR-IGRT) system. Methods: The imaging performance characterization included four components: ACR (the American College of Radiology) phantom test, spatial integrity, coil signal to noise ratio (SNR) and uniformity, and magnetic field homogeneity. The ACR phantom test was performed in accordance with the ACR phantom test guidance. The spatial integrity test was evaluated using a 40.8 × 40.8 × 40.8 cm{sup 3} spatial integrity phantom. MR and computed tomography (CT) images of the phantom were acquired and coregistered. Objects were identified around the surfaces of 20 and 35 cm diameters of spherical volume (DSVs) on both the MR and CT images. Geometric distortion was quantified using deviation in object location between the MR and CT images. The coil SNR test was performed according to the national electrical manufacturers association (NEMA) standards MS-1 and MS-9. The magnetic field homogeneity test was measured using field camera and spectral peak methods. Results: For the ACR tests, the slice position error was less than 0.10 cm, the slice thickness error was less than 0.05 cm, the resolved high-contrast spatial resolution was 0.09 cm, the resolved low-contrast spokes were more than 25, the image intensity uniformity was above 93%, and the percentage ghosting was less than 0.22%. All were within the ACR recommended specifications. The maximum geometric distortions within the 20 and 35 cm DSVs were 0.10 and 0.18 cm for high spatial resolution three-dimensional images and 0.08 and 0.20 cm for high temporal resolution two dimensional cine images based on the distance-to-phantom-center method. The average SNR was 12.0 for the body coil, 42.9 for the combined torso coil, and 44.0 for the combined head and neck coil. Magnetic field homogeneities at gantry angles of 0°, 30°, 60°, 90°, and 120° were 23.55, 20.43, 18.76, 19.11, and 22.22 ppm, respectively, using the field camera method over the 45 cm DSV. Conclusions: The onboard imaging unit of the first commercial MR-IGRT system meets ACR, NEMA, and vendor specifications.

60 APPLIED LIFE SCIENCES↗