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At least 955 records · Page 53

SU-D-BRF-03: Improvement of TomoTherapy Megavoltage Topogram Image Quality for Automatic Registration During Patient Localization

Purpose: To improve the quality of mega-voltage orthogonal scout images (MV topograms) for a fast and low-dose alternative technique for patient localization on the TomoTherapy HiART system. Methods: Digitally reconstructed radiographs (DRR) of anthropomorphic head and pelvis phantoms were synthesized from kVCT under TomoTherapy geometry (kV-DRR). Lateral (LAT) and anterior-posterior (AP) aligned topograms were acquired with couch speeds of 1cm/s, 2cm/s, and 3cm/s. The phantoms were rigidly translated in all spatial directions with known offsets in increments of 5mm, 10mm, and 15mm to simulate daily positioning errors. The contrast of the MV topograms was automatically adjusted based on the image intensity characteristics. A low-pass fast Fourier transform filter removed high-frequency noise and a Weiner filter reduced stochastic noise caused by scattered radiation to the detector array. An intensity-based image registration algorithm was used to register the MV topograms to a corresponding kV-DRR by minimizing the mean square error between corresponding pixel intensities. The registration accuracy was assessed by comparing the normalized cross correlation coefficients (NCC) between the registered topograms and the kV-DRR. The applied phantom offsets were determined by registering the MV topograms with the kV-DRR and recovering the spatial translation of the MV topograms. Results: The automatic registration technique provided millimeter accuracy and was robust for the deformed MV topograms for three tested couch speeds. The lowest average NCC for all AP and LAT MV topograms was 0.96 for the head phantom and 0.93 for the pelvis phantom. The offsets were recovered to within 1.6mm and 6.5mm for the processed and the original MV topograms respectively. Conclusion: Automatic registration of the processed MV topograms to a corresponding kV-DRR recovered simulated daily positioning errors that were accurate to the order of a millimeter. These results suggest the clinical use of MV topograms as a promising alternative to MVCT patient alignment.

60 APPLIED LIFE SCIENCES↗

Analysis of upper mantle structure using wave field continuation of P waves

Wave field continuation theory, which allows transformation of the seismic record section data directly into velocity-depth space, is tested for upper mantle analysis using a large array-recorded data set obtained at the 200-station Caltech-USGS Southern California Seismic Network that is representative of the structure beneath the gulf of California. The method's resolution capability is illustrated by the comparison of the slant stacks and downward continuation of both synthetic and data record sections. It is stressed that when high-quality, densely sampled digital data are available, the technique is easy to implement, provides an inversion which contains all the data in the global format, and produces an objective estimate of depth resolution as a function of ray parameter.

Walck, M. C.↗

Strain Localization during Diametral Compression of ZrO{sub 2}(Y{sub 2}O{sub 3}) Ceramics

Deformation behavior of ZrO{sub 2}−Y{sub 2}O{sub 3} ceramics under conditions of diametral compression has been studied by method of digital image correlation. Spatiotemporal patterns of strain localization along the axis of a deformed sample (ε{sub xx}(x)) and across this axis (ε{sub yy}(y)) were obtained. It is established that the ε{sub xx} and ε{sub yy} deformations accumulated during the diametral compression test are inhomogeneously distributed over the sample. This is manifested by variation of the microstructure characteristics such as the size of the coherently diffracting domains of a tetragonal phase and microstresses and leads to the tetragonal–monoclinic phase transformation. This pattern of strain localization is correlated with the observed inhomogeneity of microstresses arising in the material volume.

36 MATERIALS SCIENCE↗

Image processing via VLSI: A concept paper

Implementing specific image processing algorithms via very large scale integrated systems offers a potent solution to the problem of handling high data rates. Two algorithms stand out as being particularly critical -- geometric map transformation and filtering or correlation. These two functions form the basis for data calibration, registration and mosaicking. VLSI presents itself as an inexpensive ancillary function to be added to almost any general purpose computer and if the geometry and filter algorithms are implemented in VLSI, the processing rate bottleneck would be significantly relieved. A set of image processing functions that limit present systems to deal with future throughput needs, translates these functions to algorithms, implements via VLSI technology and interfaces the hardware to a general purpose digital computer is developed.

Nathan, R.↗

Correcting the distortion of images taken with the ultraviolet imaging telescope

The Ultraviolet Imaging Telescope (UIT) cameras include two-stage magnetically focused image intensifiers that introduce small but significant geometrical distortions into the data. These distortions, which create positional offsets as large as 25 arcsec at the field edges, are corrected by the procedure described here to 2-3 arcsec, approximately the resolution of the images. The distortion is measured by comparing and correcting UIT images to digitized Guidestar survey plates of the same fields. Two-dimensional third-order polynomials are used to model the distortion. The models assume that the distortion is an instrumental effect, independent of mission elapsed time and target, and that the effect of distortion is an instrumental effect, independent of mission elapsed time and target, and that the effect of distortion in the center of each field is minimal. The models are used to improve computed astrometric plate solutions and to remove the geometric distortion while transforming the image to a standard north-up, ease-left orientation.

Greason, M. R.↗

A Risk-Informed Approach to Trustworthiness Assessment in Digital Twins-Based Autonomous Control

In autonomous control systems, digital twins (DTs) are used to perform diagnostic and prognostic functions. The trustworthiness of these DTs is dependent on quality and coverage of the training data, model accuracy and integrity of sensor data. This work introduces a methodology to determine the trustworthiness of a DT system given faulty sensor data using a risk informed approach. Bayesian Belief Networks (BBNs) are used to propagate uncertainties and determine the probability of trustable recommendations. The decision to trust the control action provided by the DT is based on the DT output, expert opinion, and severity of problems. The performance of DTs is reliant on the data they are trained on. When they encounter out of distribution data, the trustworthiness of the recommendations decreases. To address this issue, we include an expert component that provides input on sensor degradation. For this, we utilize a generative artificial intelligence (AI) model, such as Generative Pretrained Transformer (GPT). The GPT functions as an expert with broad knowledge. The GPT is fine-tuned to understand and discriminate sensor degradation scenarios using manufactured data. This methodology is demonstrated through a case study on a Nearly Autonomous Management and Control System (NAMAC) during a steady state scenario. Various sensor degradation types with different severity levels are considered. Degraded sensor data is processed by the DT system and the fine-tuned GPT. Finally, using the BBN, we combine the GPT information and the DT output with its sources of uncertainty. This provides an output regarding the trustworthiness of the DT recommendation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Design and implementation of a multichannel millimeter wave interferometer for the Compact Toroidal Hybrid experiment

A three-channel 1 mm wave interferometer has been designed, assembled, and installed on the Compact Toroidal Hybrid torsatron (CTH). The interferometer design makes novel use of a subharmonic mixer for detection, which simplifies alignment. It employs a single electronically tunable source that is repetitively chirped using a sawtooth waveform of frequency up to 1 MHz. The 15.25 GHz drive oscillator is multiplied in two stages to 122 GHz before a final doubler stage brings it to 244 GHz. Local oscillator (LO) power at 122 GHz is directed through waveguide to the LO input of the subharmonic mixer of each viewing chord, simplifying alignment. Phase detection is performed by directly digitizing the amplified mixer outputs at 50 MHz and processing them with a software algorithm. Initial measurements made with the central chord of the new interferometer agree with those from the existing 4 mm system at low densities. The 1 mm system performs well in current-driven discharges reaching densities over 10{sup 19} m{sup -3}, whereas the lower frequency interferometer is found to be less reliable due to loss of fringes. This is a critical improvement for experiments studying the onset, avoidance, and vacuum magnetic transform dependence of disruptions in the CTH device.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DataXray

Lab experiments involving digital signal processing tend to capture heterogeneous data that is binned into individual files. The structure of the whole experiment tends to get lost in this process, generating a "mess" of data that is difficult to summarize, and even more difficult to analyze in a consistent way. DataXray is a set of python routines that wraps publicly available open-source codes to create a consistent workflow for data and experiments, involving imaging, spectral and hyperspectral data. Routines are provided for data translation, slicing, visualization, multivariate statistics, integral transforms, feature extraction and reporting in the form of publication-grade figures.

Maksymovych, Petro↗

Morpho-Hawk

Morpho-Hawk applies projectional mathematical morphology in a fundamentally new way. Morpho-Hawk extracts object information from digital images by filtering with simple geometrical figures such as rectangles or simple curves. Two core algorithms are used to accomplish this: 1) Object Detection and Feature Extraction from Images: Using projectional morphology, Morpho-Hawk finds features of interest within an image, such as contours, shapes, colors, infrared spectra, and more. Because Morpho-Hawk identifies features based on shape or form, the method can uniquely handle different image or object conditions and directions. MorphoHawk can evaluate all possible images of the analyzed scene using the same transformations that are applied just to one image of that scene. Hence, recognizing a defect within an image or part of an image provides information to assist in recognizing other objects in the image. In addition, known background image information can be morphologically subtracted out in order to focus on the appearance or disappearance of the features of interest. 2) Object Analysis: Upon detection of an object of interest, Morpho-Hawk can analyze the object based learned information from prior images or end-user defined criteria for certain object of special interest by selecting feature (e.g., color, size, shape, apparent volume) and/or symbol (e.g., letter, number). The novel algorithm can analyze targeted objects, even as conditions of such as illumination, shadows, and spectral regions change strongly in following images as compared to the original image. This enables robust recognition, interpolation and prediction. As the analysis shows the presence of these features in the optical signal, the algorithm can make a determination based on user defined probability. The object information can be stored for later analysis using simple morphological data compression methods and/or retention of the original optical images.

Glazoff, MichaelV.↗

Laboratory time series moisture manipulative experiment from sediment across the contiguous US: time series aerobic respiration and geochemistry (v2)

This dataset supports a broader study examining the effects of wetting and drying on hyporheic zone respiration across the contiguous United States (CONUS). The dataset provides data generated from a laboratory moisture manipulation experiment. The contents include time series aerobic respiration and moisture; dissolved oxygen; sediment geochemistry data; and field metadata (including qualitative information on instream and river corridor characteristics). Samples were collected as part of the WHONDRS CONUS-Scale Model-Sample Study (CM). This study was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. The data package associated with the CM study is available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689. CM sampling began in April 2022 and ended in October 2023. This study uses subsamples from a subset of CM samples collected between June 2022 and June 2023. The original field samples were labeled as CM_###. Subsequent subsamples for this study were labeled as EC_###. The labels from the field samples and the EC subsamples can be mapped directly based on the digits following the prefix and underscore (i.e., EC_001 is a subsample from CM_001). See the critical details section below for more details on sample naming. This data package was originally published in August 2024. It was updated in February 2026 (v2; new and modified files). See the change history section in the readme for more details. For details on how to navigate this data package, see this infographic from the River Corridor SFA https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) field protocol; and a (6) a subfolder with sediment sample data from the incubation experiment. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC); (2) total nitrogen (TN); (3) adenosine triphosphate (ATP); (4) percent carbon and nitrogen; (5) effect size; (6) iron (II); (7) gravimetric moisture; (8) respiration rates and raw dissolved oxygen values; (9) specific conductance; (10) pH; (11) temperature; (12) a summary containing median values of each data type for each treatment (wet and dry); (13) methods codes; (14) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla FTICR-MS data. This folder contains three subfolders, one containing the sediment .xml data files, one containing the sediment CoreMS output files, the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗

Adaptive flutter suppression, analysis and test

Methods of adaptive control have been applied to suppress a potentially violent flutter condition of a half-span model of a lightweight figher aircraft. This marked the confluence of several technologies with active flutter suppression, digital control and adaptive control theory the primary contributors. The control algorithm was required to adapt both to slowly varying changes, corresponding to changes in the flight condition or fuel loading and to rapid changes, corresponding to a store release or the transition from a stable to an unstable flight condition. The development of the adaptive control methods was followed by a simulation and checkout of the complete system and a wind tunnel demonstration. As part of the test, a store was released from the model wing tip, transforming the model abruptly from a stable configuration to a violent flutter condition. The adaptive algorithm recognized the unstable nature of the resulting configuration and implemented a stabilizing control law in a fraction of a second. The algorithm was also shown to provide system stability over a range of wind tunnel Mach numbers and dynamic pressures.

Johnson, E. H.↗

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗

Photometric redshifts for the S-PLUS Survey: Is machine learning up to the task?

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning models made with TensorFlow) and compare them with the currently used template-fitting method in the S-PLUS DR1 to address whether machine learning methods can take advantage of the twelve filter system for photometric redshift prediction. Using tests for accuracy for both single-point estimates such as the calculation of the scatter, bias, and outlier fraction, and probability distribution functions (PDFs) such as the Probability Integral Transform (PIT), the Continuous Ranked Probability Score (CRPS) and the Odds distribution, we conclude that a deep-learning method using a combination of a Bayesian Neural Network and a Mixture Density Network offers the most accurate photometric redshifts for the current test sample. In conclusion, it achieves single-point photometric redshifts with scatter (σ NMAD ) of 0.023, normalized bias of -0.001, and outlier fraction of 0.64% for galaxies with r_auto magnitudes between 16 and 21.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of the spline reconstruction technique for PET

Purpose: The spline reconstruction technique (SRT), based on the analytic formula for the inverse Radon transform, has been presented earlier in the literature. In this study, the authors present an improved formulation and numerical implementation of this algorithm and evaluate it in comparison to filtered backprojection (FBP). Methods: The SRT is based on the numerical evaluation of the Hilbert transform of the sinogram via an approximation in terms of “custom made” cubic splines. By restricting reconstruction only within object pixels and by utilizing certain mathematical symmetries, the authors achieve a reconstruction time comparable to that of FBP. The authors have implemented SRT in STIR and have evaluated this technique using simulated data from a clinical positron emission tomography (PET) system, as well as real data obtained from clinical and preclinical PET scanners. For the simulation studies, the authors have simulated sinograms of a point-source and three digital phantoms. Using these sinograms, the authors have created realizations of Poisson noise at five noise levels. In addition to visual comparisons of the reconstructed images, the authors have determined contrast and bias for different regions of the phantoms as a function of noise level. For the real-data studies, sinograms of an{sup 18}F-FDG injected mouse, a NEMA NU 4-2008 image quality phantom, and a Derenzo phantom have been acquired from a commercial PET system. The authors have determined: (a) coefficient of variations (COV) and contrast from the NEMA phantom, (b) contrast for the various sections of the Derenzo phantom, and (c) line profiles for the Derenzo phantom. Furthermore, the authors have acquired sinograms from a whole-body PET scan of an {sup 18}F-FDG injected cancer patient, using the GE Discovery ST PET/CT system. SRT and FBP reconstructions of the thorax have been visually evaluated. Results: The results indicate an improvement in FWHM and FWTM in both simulated and real point-source studies. In all simulated phantoms, the SRT exhibits higher contrast and lower bias than FBP at all noise levels, by increasing the COV in the reconstructed images. Finally, in real studies, whereas the contrast of the cold chambers are similar for both algorithms, the SRT reconstructed images of the NEMA phantom exhibit slightly higher COV values than those of FBP. In the Derenzo phantom, SRT resolves the 2-mm separated holes slightly better than FBP. The small-animal and human reconstructions via SRT exhibit slightly higher resolution and contrast than the FBP reconstructions. Conclusions: The SRT provides images of higher resolution, higher contrast, and lower bias than FBP, by increasing slightly the noise in the reconstructed images. Furthermore, it eliminates streak artifacts outside the object boundary. Unlike other analytic algorithms, the reconstruction time of SRT is comparable with that of FBP. The source code for SRT will become available in a future release of STIR.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

TCR Data Management Plan

The Oak Ridge National Laboratory (ORNL) Transformation Challenge Reactor (TCR) program is developing additive manufacturing and artificial intelligence (AI) to deliver enabling technologies for advanced reactors. Through the application of these advanced technologies, the program targets delivering solutions to the high costs and lengthy deployment timelines that threaten the future of nuclear energy—the country’s largest source of carbon-free energy. This document describes the plan for integrating and managing TCR data from multiple sources throughout ORNL and external sources, including novel data sources associated with advanced manufacturing, characterization systems, and the TCR Digital Platform that incorporates various levels of AI and data analytics.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Local structure effects of carbon-doping on the phase change material Ge 2 Sb 2 Te 5

Ge 2 Sb 2 Te 5 is used in phase change memory, a nonvolatile memory technology, due to its phase change properties. The primary advantage of phase change memory over the state-of-the-art (flash memory) is its simple and small device geometry, which allows for denser nodes and lower power consumption. In phase change memory, resistive heating induces fast switching between the high resistance amorphous and low resistance crystalline phases, corresponding to storage of low and high digital states, respectively. However, the instability of the amorphous phase of Ge 2 Sb 2 Te 5 presents issues with processing and long-term data storage; such issues can be resolved by C doping, which stabilizes the amorphous phase and raises the crystallization temperature. To better understand the local structural effects of C doping on Ge 2 Sb 2 Te 5 , in situ Ge K-edge X-ray absorption spectroscopy measurements were taken during heating of films with various C doping concentrations. Here, the range of structural transformation temperatures derived from X-ray absorption near-edge structure analysis across the C doping series proved narrower than crystallization temperatures reported in similar in situ X-ray diffraction experiments, which may reflect changes in local structure that precede long-range ordering during crystallization. In addition, rigorous extended X-ray absorption fine structure fitting across and between temperature series revealed effects of C doping on the rigidity of Ge–Te bonds at low (2 at% and 4 at%) C concentrations.

Langhout, John D.↗

Use of Multi-Resolution Wavelet Feature Pyramids for Automatic Registration of Multi-Sensor Imagery

The problem of image registration, or alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times, and that would provide sub-pixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the band-pass wavelets obtained from the Steerable Pyramid due to Simoncelli perform better than two types of low-pass pyramids when the images being registered have relatively small amount of nonlinear radiometric variations between them. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Zavorin, Ilya↗

Multiscale additive manufacturing of polymers using 3D photo-printable self-assembling ionic liquid monomers

3D photoprinting of a self-assembled ionic liquid (IL) monomer based liquid-crystalline mesophase introduces high-resolution nanoscale features (2–5 nm) into otherwise low-resolution (microscale features) polymer builds. A wide variety of geometric builds possessing internal hexagonal perforated lamellar (HPL) nanostructure containing ~2.4 nm diameter pores are fabricated by the digital light processing 3D printing of an aqueous mixture (61(w/w%)) of an ionic liquid monomer, 1-decyl-3-vinylimidazolium chloride, a co-monomer, polyethylene diacrylate (PEGDA, M n 575), and a visible light photo-initiator (eosin Y and triethanolamine). Vibrational spectroscopy and thermal analysis proves acrylate moiety polymerization occurs during printing but incomplete consumption of the IL vinyl groups. Post-printing exposure to UV light (λ 350 nm) completes vinyl polymerization serving to further improve nanostructure ordering as determined by SAXS. Solvent swelling (ethanol) induces a structural transformation to a body center cubic architecture accompanied by slight pore expansion (to 3.2 nm). The introduction of nanoscale features into low-resolution photo-printed polymers establishes a low-cost strategy for the additive manufacturing of multi-scale, structured nanoporous polymer membranes.

36 MATERIALS SCIENCE↗