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A RiG may simulate visual conditions of a real world environment, and generate the necessary amount of pixels in a visual simulation at rates up to 120 frames per second. RiG may also include a database generation system capable of producing visual databases suitable to drive the visual fidelity required by the RiG.
Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images), image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.
A simulation suite, cueMAP, has been developed to facilitate the design of inspection processes and sparse 2D array configurations. At the core of cueMAP is a Total Focusing Method (TFM) imaging algorithm that enables computer assisted design of ultrasonic inspection scenarios, including the design of bespoke array configurations to match the inspection criteria. This in-house developed TFM code allows for interactive evaluation of image quality indicators of ultrasonic imaging performance when utilizing a 2D phased array working in FMC/TFM mode. The cueMAP software uses a series of TFM images to build a map of resolution, contrast and sensitivity of imaging performance of a simulated reflector, swept across the inspection volume. The software takes into account probe properties, wedge or water standoff, and effects of specimen curvature. In the validation process of this new software package, two 2D arrays have been evaluated on 304n stainless steel samples, typical of the primary circuit in nuclear plants. Thick section samples have been inspected using a 1MHz 2D matrix array. Due to the processing efficiency of the software, the data collected from these array configurations has been used to investigate the influence sub-aperture operation on inspection performance.
A significant body of current research is aimed at developing methods for numerical simulation of flow and transport in porous media that explicitly resolve complex pore and solid geometries, and at utilizing such models to study the relationships between fundamental pore-scale processes and macroscopic manifestations at larger (i.e., Darcy) scales. A number of different numerical methods for pore-scale simulation have been developed, and have been extensively tested and validated for simplified geometries. However, validation of pore-scale simulations of fluid velocity for complex, three-dimensional (3D) pore geometries that are representative of natural porous media is challenging due to our limited ability to measure pore-scale velocity in such systems. Recent advances in magnetic resonance imaging (MRI) offer the opportunity to measure not only the pore geometry, but also local fluid velocities under steady-state flow conditions in 3D and with high spatial resolution. In this paper, we present a 3D velocity field measured at sub-pore resolution (tens of micrometers) over a centimeter-scale 3D domain using MRI methods. We have utilized the measured pore geometry to perform 3D simulations of Navier-Stokes flow over the same domain using direct numerical simulation techniques. We present a comparison of the numerical simulation results with the measured velocity field. It is shown that the numerical results match the observed velocity patterns well overall except for a variance and small systematic scaling which can be attributed to the known experimental error in the MRI measurements. The comparisons presented here provide strong validation of the pore-scale simulation methods and new insights for interpretation of uncertainty in MRI measurements of pore-scale velocity. This study also provides a potential benchmark for future comparison of other pore-scale simulation methods.
Purpose: The purpose of this study was to assess the dosimetric accuracy of synthetic CT (MRCT) volumes generated from magnetic resonance imaging (MRI) data for focal brain radiation therapy. Methods and Materials: A study was conducted in 12 patients with gliomas who underwent both MR and CT imaging as part of their simulation for external beam treatment planning. MRCT volumes were generated from MR images. Patients' clinical treatment planning directives were used to create 12 individual volumetric modulated arc therapy (VMAT) plans, which were then optimized 10 times on each of their respective CT and MRCT-derived electron density maps. Dose metrics derived from optimization criteria, as well as monitor units and gamma analyses, were evaluated to quantify differences between the imaging modalities. Results: Mean differences between planning target volume (PTV) doses on MRCT and CT plans across all patients were 0.0% (range: −0.1 to 0.2%) for D{sub 95%}; 0.0% (−0.7 to 0.6%) for D{sub 5%}; and −0.2% (−1.0 to 0.2%) for D{sub max}. MRCT plans showed no significant changes in monitor units (−0.4%) compared to CT plans. Organs at risk (OARs) had average D{sub max} differences of 0.0 Gy (−2.2 to 1.9 Gy) over 85 structures across all 12 patients, with no significant differences when calculated doses approached planning constraints. Conclusions: Focal brain VMAT plans optimized on MRCT images show excellent dosimetric agreement with standard CT-optimized plans. PTVs show equivalent coverage, and OARs do not show any overdose. These results indicate that MRI-derived synthetic CT volumes can be used to support treatment planning of most patients treated for intracranial lesions.
Purpose: To evaluate the potential impact of several setup error correction strategies on a proposed image-guided adaptive radiotherapy strategy for locally advanced lung cancer. Methods: Daily 4D cone-beam CT and weekly 4D fan-beam CT images were acquired from 9 lung cancer patients undergoing concurrent chemoradiation therapy. Initial planning CT was deformably registered to daily CBCT images to generate synthetic treatment courses. An adaptive radiation therapy course was simulated using the weekly CT images with replanning twice and a hypofractionated, simultaneous integrated boost to a total dose of 66 Gy to the original PTV and either a 66 Gy (no boost) or 82 Gy (boost) dose to the boost PTV (ITV + 3mm) in 33 fractions with IMRT or VMAT. Lymph nodes (LN) were not boosted (prescribed to 66 Gy in both plans). Synthetic images were rigidly, bony (BN) or tumor and carina (TC), registered to the corresponding plan CT, dose was computed on these from adaptive replans (PLAN) and deformably accumulated back to the original planning CT. Cumulative D98% of CTV of PT (ITV for 82Gy) and LN, and normal tissue dose changes were analyzed. Results: Two patients were removed from the study due to large registration errors. For the remaining 7 patients, D98% for CTV-PT (ITV-PT for 82 Gy) and CTV-LN was within 1 Gy of PLAN for both 66 Gy and 82 Gy plans with both setup techniques. Overall, TC based setup provided better results, especially for LN coverage (p = 0.1 for 66Gy plan and p = 0.2 for 82 Gy plan, comparison of BN and TC), though not significant. Normal tissue dose constraints violated for some patients if constraint was barely achieved in PLAN. Conclusion: The hypofractionated adaptive strategy appears to be deliverable with soft tissue alignment for the evaluated margins and planning parameters. Research was supported by NIH P01CA116602.
Purpose: To investigate the feasibility of quantifying the cross-sectional area (CSA) of coronary arteries using integrated density in a physics-based model with a phantom study. Methods: In this technique the total integrated density of the object as compared with its local background is measured so it is possible to account for the partial volume effect. The proposed method was compared to manual segmentation using CT scans of a 10 cm diameter Lucite cylinder placed inside a chest phantom. Holes with cross-sectional areas from 1.4 to 12.3 mm{sup 2} were drilled into the Lucite and filled with iodine solution, producing a contrast-to-noise ratio of approximately 26. Lucite rods 1.6 mm in diameter were used to simulate plaques. The phantom was imaged with and without the Lucite rods placed in the holes to simulate diseased and normal arteries, respectively. Linear regression analysis was used, and the root-mean-square deviations (RMSD) and errors (RMSE) were computed to assess the precision and accuracy of the measurements. In the case of manual segmentation, two readers independently delineated the lumen in order to quantify the inter-reader variability. Results: The precision and accuracy for the normal vessels using the integrated density technique were 0.32 mm{sup 2} and 0.32 mm{sup 2}, respectively. The corresponding results for the manual segmentation were 0.51 mm{sup 2} and 0.56 mm{sup 2}. In the case of diseased vessels, the precision and accuracy of the integrated density technique were 0.46 mm{sup 2} and 0.55 mm{sup 2}, respectively. The corresponding results for the manual segmentation were 0.75 mm{sup 2} and 0.98 mm{sup 2}. The mean percent difference for the two readers was found to be 8.4%. Conclusion: The CSA based on integrated density had improved precision and accuracy as compared with manual segmentation in a Lucite phantom. The results indicate the potential for using integrated density to improve CSA measurements in CT angiography.
Purpose: To reduce radiation dose to the patients, tube current modulation (TCM) method has been actively used in diagnostic CT systems. However, TCM method has not yet been applied to a kV-CBCT system on a LINAC machine. The purpose of this study is to investigate whether the use of TCM method is desirable in kV-CBCT system for IGRT. We have developed an attenuation-based tube current modulation (a-TCM) method using the prior knowledge of treatment CT image of a patient. Methods: Patients go through a diagnostic CT scan for RT planning; therefore, using this prior information of CT images, one can estimate the total attenuation of an x-ray through the patient body in a CBCT setting for radiation therapy. We performed a numerical study incorporating major factors into account such as polychromatic x-ray, scatter, noise, and bow-tie filter to demonstrate that a-TCM method can produce equivalent quality of images at reduced imaging radiation doses. Using the CT projector program, 680 projection images of the pediatric XCAT phantom were obtained both in conventional scanning condition, i.e., without modulating the tube current, and in the proposed a-TCM scanning condition. FDK reconstruction algorithm was used for image reconstruction, and the organ dose due to imaging radiation has been calculated in both cases and compared using GATE/Geant4 simulation toolkit. Results: Reconstructed CT images in the a-TCM method showed similar SSIM values and noise properties to the reference images acquired by the conventional CBCT. In addition, reduction of organ doses ranged from 12% to 27%. Conclusion: We have successfully demonstrated the feasibility and dosimetric merit of the a-TCM method for kV-CBCT, and envision that it can be a useful option of CBCT scanning that provides patient dose reduction without degrading image quality.
A complete documentation of the software developed in the Communication and Signal Processing Laboratory (CSPL) during the period of July 1985 to March 1986 is provided. Utility programs and subroutines that were developed for a user-friendly image and speech processing environment are described. Additional programs for data compression of image and speech type signals are included. Also, programs for the zero-memory and block transform quantization in the presence of channel noise are described. Finally, several routines for simulating the perfromance of image compression algorithms are included.
Newtonian simulations have demonstrated that accretion onto binary black holes produces accretion disks around each black hole (“minidisks”), fed by gas streams flowing through the circumbinary cavity from the surrounding circumbinary disk. We study the dynamics and radiation of an individual black hole minidisk using 2D hydrodynamical simulations performed with a new general relativistic version of the moving-mesh code Disco. We introduce a comoving energy variable that enables highly accurate integration of these high Mach number flows. Tidally induced spiral shock waves are excited in the disk and propagate through the innermost stable circular orbit, providing a Reynolds stress that causes efficient accretion by purely hydrodynamic means and producing a radiative signature brighter in hard X-rays than the Novikov–Thorne model. Disk cooling is provided by a local blackbody prescription that allows the disk to evolve self-consistently to a temperature profile where hydrodynamic heating is balanced by radiative cooling. We find that the spiral shock structure is in agreement with the relativistic dispersion relation for tightly wound linear waves. We measure the shock-induced dissipation and find outward angular momentum transport corresponding to an effective alpha parameter of order 0.01. We perform ray-tracing image calculations from the simulations to produce theoretical minidisk spectra and viewing-angle-dependent images for comparison with observations.
We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.
Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.
Purpose: Finding the optimal energy threshold setting for an energy-resolved photon-counting detector has an important impact on the maximization of contrast-to-noise-ratio (CNR). We introduce a noise reduction method to enhance CNR by reducing the noise in each energy bin without altering the average gray levels in the projection and image domains. Methods: We simulated a four bin energy-resolved photon-counting detector based on Si with a 10 mm depth of interaction. TASMIP algorithm was used to simulate a spectrum of 65 kVp with 2.7 mm Al filter. A 13 mm PMMA phantom with hydroxyapatite and iodine at different concentrations (100, 200 and 300 mg/ml for HA, and 2, 4, and 8 mg/ml for Iodine) was used. Projection-based and Image-based energy weighting methods were used to generate weighted images. A reference low noise image was used for noise reduction purposes. A Gaussian-like weighting function which computes the similarity between pixels of interest was calculated from the reference image and implemented on a pixel by pixel basis for the noisy images. Results: CNR improvement compared to different methods (Charge-Integrated, Photon-Counting and Energy-Weighting) and after noise reduction was highly task-dependent. The CNR improvement with respect to the Charge-Integrated CNR for hydroxyapatite and iodine were 1.8 and 1.5, respectively. In each of the energy bins, the noise was reduced by approximately factor of two without altering their respective average gray levels. Conclusion: The proposed noise reduction technique for energy-resolved photon-counting detectors can significantly reduce image noise. This technique can be used as a compliment to the current energy-weighting methods in CNR optimization.
Purpose: To develop a robust planning paradigm which incorporates a tumor regression model into the optimization process to ensure tumor coverage in head and neck radiotherapy. Methods: Simulation and weekly MR images were acquired for a group of head and neck patients to characterize tumor regression during radiotherapy. For each patient, the tumor and parotid glands were segmented on the MR images and the weekly changes were formulated with an affine transformation, where morphological shrinkage and positional changes are modeled by a scaling factor, and centroid shifts, respectively. The tumor and parotid contours were also transferred to the planning CT via rigid registration. To perform the robust planning, weekly predicted PTV and parotid structures were created by transforming the corresponding simulation structures according to the weekly affine transformation matrix averaged over patients other than him/herself. Next, robust PTV and parotid structures were generated as the union of the simulation and weekly prediction contours. In the subsequent robust optimization process, attainment of the clinical dose objectives was required for the robust PTV and parotids, as well as other organs at risk (OAR). The resulting robust plans were evaluated by looking at the weekly and total accumulated dose to the actual weekly PTV and parotid structures. The robust plan was compared with the original plan based on the planning CT to determine its potential clinical benefit. Results: For four patients, the average weekly change to tumor volume and position was −4% and 1.2 mm laterally-posteriorly. Due to these temporal changes, the robust plans resulted in an accumulated PTV D95 that was, on average, 2.7 Gy higher than the plan created from the planning CT. OAR doses were similar. Conclusion: Integration of a tumor regression model into target delineation and plan robust optimization is feasible and may yield improved tumor coverage. Part of this research is supported by Varian Medical System.
Purpose: To design a comprehensive open-source, publicly available, graphical user interface (GUI) to facilitate the configuration, generation, processing and use of the 4D Extended Cardiac-Torso (XCAT) phantom. Methods: The XCAT phantom includes over 9000 anatomical objects as well as respiratory, cardiac and tumor motion. It is widely used for research studies in medical imaging and radiotherapy. The phantom generation process involves the configuration of a text script to parameterize the geometry, motion, and composition of the whole body and objects within it, and to generate simulated PET or CT images. To avoid the need for manual editing or script writing, our MATLAB-based GUI uses slider controls, drop-down lists, buttons and graphical text input to parameterize and process the phantom. Results: Our GUI can be used to: a) generate parameter files; b) generate the voxelized phantom; c) combine the phantom with a lesion; d) display the phantom; e) produce average and maximum intensity images from the phantom output files; f) incorporate irregular patient breathing patterns; and f) generate DICOM files containing phantom images. The GUI provides local help information using tool-tip strings on the currently selected phantom, minimizing the need for external documentation. The DICOM generation feature is intended to simplify the process of importing the phantom images into radiotherapy treatment planning systems or other clinical software. Conclusion: The GUI simplifies and automates the use of the XCAT phantom for imaging-based research projects in medical imaging or radiotherapy. This has the potential to accelerate research conducted with the XCAT phantom, or to ease the learning curve for new users. This tool does not include the XCAT phantom software itself. We would like to acknowledge funding from MRA, Varian Medical Systems Inc.
Purpose: Recent advances in cancer treatments have greatly increased the likelihood of post-treatment patient survival. Secondary malignancies, however, have become a growing concern. Epidemiological studies determining secondary effects in radiotherapy patients require assessment of organ-specific dose both inside and outside the treatment field. An essential input for Monte Carlo modeling of particle transport is radiological images showing full patient anatomy. However, in retrospective studies it is typical to only have partial anatomy from CT scans used during treatment planning. In this study, we developed a multi-step method to extend such limited patient anatomy to full body anatomy for estimating dose to normal tissues located outside the CT scan coverage. Methods: The first step identified a phantom from a library of body size-dependent computational human phantoms by matching the height and weight of patients. Second, a Python algorithm matched the patient CT coverage location in relation to the whole body phantom. Third, an algorithm cut the whole body phantom and scaled them to match the size of the patient. Then, merged the two anatomies into one whole body. We entitled this new approach, Anatomically Predictive Extension (APE). Results: The APE method was examined by comparing the original chest-abdomen-pelvis CT images of the five patients with the APE phantoms developed from only the chest part of the CAP images and whole body phantoms. We achieved average percent differences of tissue volumes of 25.7%, 34.2%, 16.5%, 26.8%, and 31.6% with an average of 27% across all patients. Conclusion: Our APE method extends the limited CT patient anatomy to whole body anatomy by using image processing and computational human phantoms. Our ongoing work includes evaluating the accuracy of these APE phantoms by comparing normal tissue doses in the APE phantoms and doses calculated for the original full CAP images under generic radiotherapy simulations. This research was supported by the NIH Intramural Research Program.
The Exoplanet Spectroscopy (ExoSpec) project links four different tasks at Goddard Space Flight Center (GSFC) to facilitate efficient imaging and characterization of exoplanets. One of the tasks is the development of parabolic deformable mirrors to improve on the current state-of-the-art wavefront sensing and control implementations that are baselined to have two high-actuator count flat deformable mirrors (DMs). The current baseline has two DMs at a considerable separation distance to effectively control both amplitude and phase aberrations. This significant separation poses packaging challenges to the direct imaging missions. We can mitigate this issue by making the off-axis imaging elements in the optical train controllable. Besides addressing the packaging challenges, this technique reduces the risk of having the entire coronagraph instrument’s performance depend on two high-actuator count DMs. Simulations show that making imaging elements deformable increases the overall controllable bandwidth - it would be possible to control wavefront aberrations up to 35% bandwidth over a 5 - 12 λ/D. GSFC has worked with a commercial vendor to produce a first-generation parabolic DM and built a testbed in an environmentally controlled cleanroom to experimentally demonstrate the use of a parabolic DM in a coronagraph instrument. This versatile testbed is designed to test different DM architectures and various low-order wavefront schemes. This provides us with a basis for comparison with different DM configurations —1) flat DM, 2) parabolic DMs, and 3) flat DM and parabolic DMs. In this paper, we will provide an update on our parabolic DM work.
Highlights: • Grains with sub-boundaries grew abnormally in the MC simulation with realistic grain boundary energy. • The experimental 3-D morphology of Goss grain was reconstructed from serially sectioned images. • 2-D sectioned microstructures of the MC simulation and experiment have highly irregular shape. • Both simulated and experimental 3-D morphologies of AGG have similar complicated shapes. - Abstract: Three-dimensional (3-D) Monte Carlo simulations of grain growth with sub-boundaries in the presence of precipitates were performed based on the distribution of realistic grain boundary energy data. The simulated grains with sub-boundaries grew abnormally. The simulated and experimental morphologies of the abnormally growing grains in Fe-3%Si steel were compared. The experimental 3-D morphology was reconstructed from serially sectioned images. Both the simulated and experimental 3-D morphologies of abnormally growing grains have highly irregular and complicated shapes whereas both the simulated and experimental 3-D morphologies of normally growing grains have relatively regular and simple shapes. Growth by wetting is responsible for the highly irregular shape of the experimental abnormally growing grains of Fe-3%Si steel as well as for the highly irregular shape of the simulated abnormally growing grains.