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Fire scenes for cinematography staged at relatively low cost in method that combines several existing techniques. Nearly realistic scenes, suitable for firefighter training, produced with little specialized equipment. Sequences of scenes set up quickly and easily, without compromising safety because model not burned. Images of fire, steam, and smoke superimposed on image of building to simulate burning of building.
Purpose: Multi-detector computed tomography (MDCT) enables volumetric scans in a single breath hold and is clinically useful for hepatic imaging. For simple tasks, conventional single energy (SE) computed tomography (CT) images acquired at the optimal tube potential are known to have better quality than dual energy (DE) blended images. However, liver imaging is complex and often requires imaging of both structures containing iodinated contrast media, where atomic number differences are the primary contrast mechanism, and other structures, where density differences are the primary contrast mechanism. Hence it is conceivable that the broad spectrum used in a dual energy acquisition may be an advantage. In this work we are interested in comparing these two imaging strategies at equal-dose and more complex settings. Methods: We developed numerical anthropomorphic phantoms to mimic realistic clinical CT scans for medium size and large size patients. MDCT images based on the defined phantoms were simulated using various SE and DE protocols at pre- and post-contrast stages. For SE CT, images from 60 kVp through 140 with 10 kVp steps were considered; for DE CT, both 80/140 and 100/140 kVp scans were simulated and linearly blended at the optimal weights. To make a fair comparison, the mAs of each scan was adjusted to match the reference radiation dose (120 kVp, 200 mAs for medium size patients and 140 kVp, 400 mAs for large size patients). Contrast-to-noise ratio (CNR) of liver against other soft tissues was used to evaluate and compare the SE and DE protocols, and multiple pre- and post-contrasted liver-tissue pairs were used to define a composite CNR. To help validate the simulation results, we conducted a small clinical study. Eighty-five 120 kVp images and 81 blended 80/140 kVp images were collected and compared through both quantitative image quality analysis and an observer study. Results: In the simulation study, we found that the CNR of pre-contrast SE image mostly increased with increasing kVp while for post-contrast imaging 90 kVp or lower yielded higher CNR images, depending on the differential iodine concentration of each tissue. Similar trends were seen in DE blended CNR and those from SE protocols. In the presence of differential iodine concentration (i.e., post-contrast), the CNR curves maximize at lower kVps (80–120), with the peak shifted rightward for larger patients. The combined pre- and post-contrast composite CNR study demonstrated that an optimal SE protocol has better performance than blended DE images, and the optimal tube potential for SE scan is around 90 kVp for a medium size patients and between 90 and 120 kVp for large size patients (although low kVp imaging requires high x-ray tube power to avoid photon starvation). Also, a tin filter added to the high kVp beam is not only beneficial for material decomposition but it improves the CNR of the DE blended images as well. The dose adjusted CNR of the clinical images also showed the same trend and radiologists favored the SE scans over blended DE images. Conclusions: Our simulation showed that an optimized SE protocol produces up to 5% higher CNR for a range of clinical tasks. The clinical study also suggested 120 kVp SE scans have better image quality than blended DE images. Hence, blended DE images do not have a fundamental CNR advantage over optimized SE images.
Purpose: To investigate whether deconvolution methods can improve the scatter estimation under different blurring and noise conditions for blocker-based scatter correction methods for cone-beam X-ray computed tomography (CBCT). Methods: An “ideal” projection image with scatter was first simulated for blocker-based CBCT data acquisition by assuming no blurring effect and no noise. The ideal image was then convolved with long-tail point spread functions (PSF) with different widths to mimic the blurring effect from the finite focal spot and detector response. Different levels of noise were also added. Three deconvolution Methods: 1) inverse filtering; 2) Wiener; and 3) Richardson-Lucy, were used to recover the scatter signal in the blocked region. The root mean square error (RMSE) of estimated scatter serves as a quantitative measure for the performance of different methods under different blurring and noise conditions. Results: Due to the blurring effect, the scatter signal in the blocked region is contaminated by the primary signal in the unblocked region. The direct use of the signal in the blocked region to estimate scatter (“direct method”) leads to large RMSE values, which increase with the increased width of PSF and increased noise. The inverse filtering is very sensitive to noise and practically useless. The Wiener and Richardson-Lucy deconvolution methods significantly improve scatter estimation compared to the direct method. For a typical medium PSF and medium noise condition, both methods (∼20 RMSE) can achieve 4-fold improvement over the direct method (∼80 RMSE). The Wiener method deals better with large noise and Richardson-Lucy works better on wide PSF. Conclusion: We investigated several deconvolution methods to recover the scatter signal in the blocked region for blocker-based scatter correction for CBCT. Our simulation results demonstrate that Wiener and Richardson-Lucy deconvolution can significantly improve the scatter estimation compared to the direct method.
A document describes cryogenic test architecture for the James Webb Space Telescope (JWST) integrated science instrument module (ISIM). The ISIM element primarily consists of a mechanical metering structure, three science instruments, and a fine guidance sensor. One of the critical optomechanical alignments is the co-registration of the optical telescope element (OTE) exit pupil with the entrance pupils of the ISIM instruments. The test architecture has been developed to verify that the ISIM element will be properly aligned with the nominal OTE exit pupil when the two elements come together. The architecture measures three of the most critical pupil degrees-of-freedom during optical testing of the ISIM element. The pupil measurement scheme makes use of specularly reflective pupil alignment references located inside the JWST instruments, ground support equipment that contains a pupil imaging module, an OTE simulator, and pupil viewing channels in two of the JWST flight instruments. Pupil alignment references (PARs) are introduced into the instrument, and their reflections are checked using the instrument's mirrors. After the pupil imaging module (PIM) captures a reflected PAR image, the image will be analyzed to determine the relative alignment offset. The instrument pupil alignment preferences are specularly reflective mirrors with non-reflective fiducials, which makes the test architecture feasible. The instrument channels have fairly large fields of view, allowing PAR tip/tilt tolerances on the order of 0.5deg.
The morphology of the stagnated plasma resulting from magnetized liner inertial fusion is measured by imaging the self-emission x rays coming from the multi-keV plasma. Equivalent diagnostic responses can be generated by integrated radiation-magnetohydrodynamic (rad-MHD) simulations from programs such as HYDRA and GORGON. There have been only limited quantitative ways to compare the image morphology, that is the texture, of simulations and experiments. We have developed a metric of image morphology based on the Mallat scattering transformation (MST), a transformation that has proved to be effective at distinguishing textures, sounds, and written characters. This metric is designed, demonstrated, and refined by classifying ensembles (i.e., classes) of synthetic stagnation images and by regressing an ensemble of synthetic stagnation images to the morphology (i.e., model) parameters used to generate the synthetic images. We use this metric to quantitatively compare simulations to experimental images, experimental images to each other, and to estimate the morphological parameters of the experimental images with uncertainty. This coordinate space has proved to be very adept at doing a sophisticated relative background subtraction in the MST space. This was needed to compare the experimental self-emission images to the rad-MHD simulation images.
Purpose: To compare the CT doses derived from the experiments and GPU-based Monte Carlo (MC) simulations, using a human cadaver and ATOM phantom. Methods: The cadaver of an 88-year old male and the ATOM phantom were scanned by a GE LightSpeed Pro 16 MDCT. For the cadaver study, the Thimble chambers (Model 10×5−0.6CT and 10×6−0.6CT) were used to measure the absorbed dose in different deep and superficial organs. Whole-body scans were first performed to construct a complete image database for MC simulations. Abdomen/pelvis helical scans were then conducted using 120/100 kVps, 300 mAs and a pitch factor of 1.375:1. For the ATOM phantom study, the OSL dosimeters were used and helical scans were performed using 120 kVp and x, y, z tube current modulation (TCM). For the MC simulations, sufficient particles were run in both cases such that the statistical errors of the results by ARCHER-CT were limited to 1%. Results: For the human cadaver scan, the doses to the stomach, liver, colon, left kidney, pancreas and urinary bladder were compared. The difference between experiments and simulations was within 19% for the 120 kVp and 25% for the 100 kVp. For the ATOM phantom scan, the doses to the lung, thyroid, esophagus, heart, stomach, liver, spleen, kidneys and thymus were compared. The difference was 39.2% for the esophagus, and within 16% for all other organs. Conclusion: In this study the experimental and simulated CT doses were compared. Their difference is primarily attributed to the systematic errors of the MC simulations, including the accuracy of the bowtie filter modeling, and the algorithm to generate voxelized phantom from DICOM images. The experimental error is considered small and may arise from the dosimeters. R01 grant (R01EB015478) from National Institute of Biomedical Imaging and Bioengineering.
Predictive reservoir modeling, even if present in the form of only basic hydrogeological model assumptions, is expected to accompany the majority of carbon capture and sequestration monitoring activities. It thus represents a source of prior information about the migration of injected fluids that can benefit geophysical survey planning and ensuing monitoring. Constraining the imaging of geophysical monitoring data with reservoir modeling is preferable over standalone geophysical imaging because of additional complementary hydrogeological information. However, fully coupled hydrogeophysical data inversion for flow-modeling parameters that control saturation predictions is an involved process. Within the context of three-dimensional electromagnetic (EM) inversion of data from borehole-to-surface layouts, we employ a "poor people's" alternative. The approach constrains geophysical inversion parameters through saturation predictions. The coupling is realized through spatially variable lower and upper parameter bounds that scale with gas saturation magnitudes, the latter provided by reservoir modeling. In this work, enhancement of three-dimensional time-lapse plume EM imaging is demonstrated for simulated sequestration into a depleted gas reservoir.
Purpose: An innovative strategy to improve the sensitivity of positron emission tomography (PET)-based treatment verification in ion beam radiotherapy is proposed. Methods: Low counting statistics PET images acquired during or shortly after the treatment (Measured PET) and a Monte Carlo estimate of the same PET images derived from the treatment plan (Expected PET) are considered as two frames of a 4D dataset. A 4D maximum likelihood reconstruction strategy was adapted to iteratively estimate the annihilation events distribution in a reference frame and the deformation motion fields that map it in the Expected PET and Measured PET frames. The outputs generated by the proposed strategy are as follows: (1) an estimate of the Measured PET with an image quality comparable to the Expected PET and (2) an estimate of the motion field mapping Expected PET to Measured PET. The details of the algorithm are presented and the strategy is preliminarily tested on analytically simulated datasets. Results: The algorithm demonstrates (1) robustness against noise, even in the worst conditions where 1.5 × 10{sup 4} true coincidences and a random fraction of 73% are simulated; (2) a proper sensitivity to different kind and grade of mismatches ranging between 1 and 10 mm; (3) robustness against bias due to incorrect washout modeling in the Monte Carlo simulation up to 1/3 of the original signal amplitude; and (4) an ability to describe the mismatch even in presence of complex annihilation distributions such as those induced by two perpendicular superimposed ion fields. Conclusions: The promising results obtained in this work suggest the applicability of the method as a quantification tool for PET-based treatment verification in ion beam radiotherapy. An extensive assessment of the proposed strategy on real treatment verification data is planned.
Purpose: To develop and validate a computational method to simulate craniocaudal respiratory motion in a VMAT treatment plan. Methods: Three 4DCTs of the QUASAR respiratory motion phantom were acquired with a 2cm water-density spherical tumour embedded in cedar to simulate lung. The phantom was oscillating sinusoidally with an amplitude of 2cm and periods of 3, 4, and 5 seconds. An ITV was contoured and 5mm PTV margin was added. High and a low modulation factor VMAT plans were created for each scan. An in-house program was developed to simulate respiratory motion in the treatment plans by shifting the MLC leaf positions relative to the phantom. Each plan was delivered to the phantom and the dose was measured using Gafchromic film. The measured and calculated plans were compared using an absolute dose gamma analysis (3%/3mm). Results: The average gamma pass rate for the low modulation plan and high modulation plans were 91.1% and 51.4% respectively. The difference between the high and low modulation plans gamma pass rates is likely related to the different sampling frequency of the respiratory curve and the higher MLC leaf speeds in the high modulation plan. A high modulation plan has a slower gantry speed and therefore samples the breathing cycle at a coarser frequency leading to inaccuracies between the measured and planned doses. Conclusion: A simple program, including a novel method for increasing sampling frequency beyond the control point frequency, has been developed to simulate respiratory motion in VMAT plans by shifting the MLC leaf positions.
In this LDRD project, we developed a capability for quantitative high - speed imaging measurements of high - pressure fuel injection dynamics to advance understanding of turbulent mixing in transcritical flows, ignition, and flame stabilization mechanisms, and to provide e ssential validation data for developing predictive tools for engine combustion simulations. Advanced, fuel - efficient engine technologies rely on fuel injection into a high - pressure, high - temperature environment for mixture preparation and com bustion. Howe ver, the dynamics of fuel injection are not well understood and pose significant experimental and modeling challenges. To address the need for quantitative high - speed measurements, we developed a Nd:YAG laser that provides a 5ms burst of pulses at 100 kHz o n a robust mobile platform . Using this laser, we demonstrated s patially and temporally resolved Rayleigh scattering imaging and particle image velocimetry measurements of turbulent mixing in high - pressure gas - phase flows and vaporizing sprays . Quantitativ e interpretation of high - pressure measurements was advanced by reducing and correcting interferences and imaging artifacts.
The majority of massive star-forming galaxies at z ~ 2 have velocity gradients suggestive of rotation, in addition to large amounts of disordered motions. In this paper, we demonstrate that it is challenging to distinguish the regular rotation of a disk galaxy from the orbital motions of merging galaxies with seeing-limited data. However, the merger fractions at z ~ 2 are likely too low for this to have a large effect on measurements of disk fractions. To determine how often mergers pass for disks, we look to galaxy formation simulations. We analyze ~24,000 synthetic images and kinematic maps of 31 high-resolution simulations of isolated galaxies and mergers at z ~ 2. Here, we determine if the synthetic observations pass the criteria commonly used to identify disk galaxies and whether the results are consistent with their intrinsic dynamical states. Galaxies that are intrinsically mergers pass the disk criteria for anywhere from 0% to 100% of sightlines. The exact percentage depends strongly on the specific disk criteria adopted and weakly on the separation of the merging galaxies. Therefore, one cannot tell with certainty whether observations of an individual galaxy indicate a merger or a disk. To estimate the fraction of mergers passing as disks in current kinematics samples, we combine the probability that a merger will pass as a disk with theoretical merger fractions from a cosmological simulation. Taking the latter at face value, the observed disk fractions are overestimated by small amounts: at most by 5% at high stellar mass (10 10–11 M ⊙ ) and 15% at low stellar mass (10 9–10 M ⊙ ).
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Purpose: To study different noise-reduction algorithms and to improve the image quality of low dose cone beam CT for patient positioning in radiation therapy. Methods: In low-dose cone-beam CT, the reconstructed image is contaminated with excessive quantum noise. In this study, three well-developed noise reduction algorithms namely, a) penalized weighted least square (PWLS) method, b) split-Bregman total variation (TV) method, and c) compressed sensing (CS) method were studied and applied to the images of a computer–simulated “Shepp-Logan” phantom and a physical CATPHAN phantom. Up to 20% additive Gaussian noise was added to the Shepp-Logan phantom. The CATPHAN phantom was scanned by a Varian OBI system with 100 kVp, 4 ms and 20 mA. For comparing the performance of these algorithms, peak signal-to-noise ratio (PSNR) of the denoised images was computed. Results: The algorithms were shown to have the potential in reducing the noise level for low-dose CBCT images. For Shepp-Logan phantom, an improvement of PSNR of 2 dB, 3.1 dB and 4 dB was observed using PWLS, TV and CS respectively, while for CATPHAN, the improvement was 1.2 dB, 1.8 dB and 2.1 dB, respectively. Conclusion: Penalized weighted least square, total variation and compressed sensing methods were studied and compared for reducing the noise on a simulated phantom and a physical phantom scanned by low-dose CBCT. The techniques have shown promising results for noise reduction in terms of PSNR improvement. However, reducing the noise without compromising the smoothness and resolution of the image needs more extensive research.
Purpose: Correction for intrafraction prostate motion becomes important for hypofraction treatment of prostate cancer. The purpose of this study was to estimate an ideal planning margin to account for intrafraction prostate motion as a function of imaging and repositioning frequency in the absence of continuous prostate motion monitoring. Methods and Materials: For 31 patients receiving intensity modulated radiation therapy treatment, prostate positions sampled at 10 Hz during treatment using the Calypso system were analyzed. Using these data, we simulated multiple, less frequent imaging protocols, including intervals of every 10, 15, 20, 30, 45, 60, 90, 120, 180, and 240 seconds. For each imaging protocol, the prostate displacement at the imaging time was corrected by subtracting prostate shifts from the subsequent displacements in that fraction. Furthermore, we conducted a principal component analysis to quantify the direction of prostate motion. Results: Averaging histograms of every 240 and 60 seconds for all patients, vector displacements of the prostate were, respectively, within 3 and 2 mm for 95% of the treatment time. A vector margin of 1 mm achieved 91.2% coverage of the prostate with 30 second imaging. The principal component analysis for all fractions showed the largest variance in prostate position in the midsagittal plane at 54° from the anterior direction, indicating that anterosuperior to inferoposterior is the direction of greatest motion. The smallest prostate motion is in the left-right direction. Conclusions: The magnitudes of intrafraction prostate motion along the superior-inferior and anterior-posterior directions are comparable, and the smallest motion is in the left-right direction. In the absence of continuous prostate motion monitoring, and under ideal circumstances, 1-, 2-, and 3-mm vector planning margins require a respective imaging frequency of every 15, 60, and 240 to account for intrafraction prostate motion while achieving adequate geometric target coverage for 95% of the time.
Low-enriched uranium alloyed with 10 wt. % molybdenum (U-10Mo) has been identified as a promising alternative to highly enriched uranium fuel for the United States’ high performance research reactors. The monolithic U-10Mo fuel plate consists of a metallic U-10Mo fuel foil with a 25 µm Zr interlayer and a relatively thick cladding of aluminum alloy 6061. The Zr interlayer is typically applied during the hot co-rolling process, and this process dictates the uniformity of the Zr interlayer. Thickness variation observed in the U-10Mo and Zr interlayer has been attributed to several sources: the initial grain size of the U-10Mo castings, can materials, rolling temperature, inhomogeneous molybdenum content, and porosity in the cast U-10Mo. This thickness variation limits the ability to meet the dimensional specification; thus, a better understanding of the factors causing the nonuniform thickness is needed. In this work, we used a novel, microstructure-based finite element method to model the hot rolling process to address these concerns. Grain microstructures in U-10Mo were tessellated and explicitly considered in the finite element model. Each grain was assigned a random material property to mimic the grain strength variations induced by different grain orientations. Simulations were performed using six steel can thicknesses, four grain sizes, and with or without a Zr interlayer to investigate the influences of those variables on the thickness nonuniformity. The simulation results showed that a thinner steel can and finer U-10Mo grain size reduce thickness variations in both the U-10Mo fuel foil and Zr interlayer. The direct findings from the simulations and analysis can be used to optimize the hot rolling schedule, reduce fabrication defects, and meet the dimensional specifications. The proposed microstructure-based finite element model can be also coupled with experimental microstructure characterization data, images, and models to simulate multi-pass hot rolling.