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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-359: Incorporating Dose Volume Histogram Prediction Into Auto-Planning for Volumetric-Modulated Arc Therapy in Rectal Cancer

Purpose: To incorporate dose volume histogram (DVH) prediction into Auto-Planning for volumetric-modulated arc therapy (VMAT) treatment planning and investigate the benefit of this new technique for rectal cancer. Methods: Ninety clinically accepted VMAT plans for patients with rectal cancer were selected and trained in the RapidPlan for DVH prediction. Both internal and external validations were performed before implementing the prediction model. A new VMAT planning method (hybrid-VMAT) was created with combining the DVH prediction and Auto-Planning. For each new patient, the DVH will be predicted and individual DVH constrains will be obtained and were exported as the original optimization parameters to the Auto-Planning (Pinnacle3 treatment planning system, v9.10) for planning. A total of 20 rectal cancer patients previously treated with manual VMAT (manual-VMAT) plans were replanned using this new method. Dosimetric comparisons were performed between manual VMAT and new method plans. Results: Hybrid-VMAT shows similar PTV coverage to manual-VMAT in D2%, D98% and HI (p>0.05) and superior coverage in CI (p=0.000). For the bladder, the means of V40 and mean dose are 36.0% and 35.6Gy for hybrid-VMAT and 42% and 38.0Gy for the manual-VMAT. For the left (right) femur, the means of V30 and mean dose are 10.6% (11.6%) and 17.9Gy (19.2Gy) for the hybrid-VMAT and 25.6% (24.1%) and 27.3Gy (26.2Gy) for the manual-VMAT. The hybrid-VMAT has significantly improved the organs at risk sparing. Conclusion: The integration of DVH prediction and Auto-Planning significantly improve the VMAT plan quality in the rectal cancer radiotherapy. Our results show the benefit of the new method and will be further investigated in other tumor sites.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-454: Dose-Mass-Histogram Sensitivity to Anatomical Changes During Radiotherapy for HNSCC

Purpose: To determine the sensitivity of dose-mass-histogram (DMH) due to anatomical changes of head-and-neck squamous cell carcinoma (HNSCC) radiotherapy (RT). Methods: Eight patients undergoing RT treatment for HNSCC were scanned during the third and sixth week of RT. These second (CT2) and third (CT3) CTs were co-registered to the planning CT (CT1). Contours were propagated via deformable registration from CT1 and doses were re-calculated. DMHs were extracted for each CT set. DMH sensitivity was assessed by dose-mass indices (DMIs), which represent the dose delivered to a certain mass of and anatomical structure. DMIs included: dose to 98%, 95% and 2% of the target masses (PTV1, PTV2, and PTV3) and organs-at-risk (OARs): cord DMI2%, brainstem DMI2%, left- and right-parotid DMI2% and DMI50%, and mandible DMI2%. A two-tailed paired t-test was used to compare changes to DMIs in CT2 and CT3 with respect to CT1 (CT2/CT1 and CT3/CT1). Results: Changes to DMHs were found for all OARs and PTVs, but they were significant only for the PTVs. Maximum dose to PTVs increased significantly for CT2/CT1 in all three PTVs, but CT3/CT1 changes were only significantly different for PTV1 and PTV2. Dose coverage to the three PTVs was also significantly different, DMI98% was lower for both CT2/CT1 and CT3/CT1. DMI95% was significantly lower for PTV1 for CT2/CT1, PTV2 for CT2/CT1 and CT3/CT1, and PTV3 for CT3/CT1. Conclusion: Changes in anatomy significantly change dose-mass coverage for the planning targets, making it necessary to re-plan in order to maintain the therapeutic goals. Maximum dose to the PTVs increase significantly as RT progresses, which may not be problematic as long as the high dose remains in the gross tumor volume. Doses to OARs were minimally affected and the differences were not significant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-FG-202-04: Decomposition of FDG-PET Based Differential Uptake Volume Histograms in Rectal Cancer Patients

Purpose: The goal of this study is to test the possible use of the analytical decomposition of differential uptake volume histograms (dUVHs) obtained from FDG-PET/CT data to isolate sub-volumes within a tumor known as biological target volumes (BTVs). Methods: : A retrospective study was conducted on a cohort of 20 histo-pathologically confirmed rectal adenocarcinoma patients having PET/CT scans for staging. All patients (T3N0) underwent pre-operative endorectal brachytherapy. After surgery, patients were restaged: 10 patients were T0N0 and 10 were restaged as remaining T3N0. The extent of the disease was sampled in order to create dUVHs; subsequently decomposed into the fewest number of analytical Gaussian functions. Results: With the assumption that each function fit corresponded to a single sub-volume within the tumor, six sub-volumes were found to consistently emerge. The first two sub-volumes were influenced by contouring and were not considered in the analysis. For the T3N0 population, abundances for volumes V3-V6 were 63.6%±11.3%, 25.7%±8.4%, 6.1%±4.9%, and 4.7%±2.6%. For the T0N0 population, they were 50.2%±6.8%, 33.4%±4.3%, 11.8%±7.6%, and 4.7%±2.4%. The two populations were compared using two tailed T-tests: volumes 3 and 4 were statistically different with p values of 0.021 and 0.056 respectively. V6 was located at 8.63 ± 2.2 for T0N0 and 6.14 ± 0.78 for T3N0 group (p=0.016). Conclusion: We described a method for dUVH decomposition using FDG-PET images of rectal adenocarcinoma patients that subsequently went for pre-operative brachytherapy. In addition to extracting different sub-volumes corresponding to different FDG uptake levels, we observed different abundances of two sub-volumes as well as positions of the maximum uptake between the two patient groups. In addition to opening the door to further investigation into underlying physiological phenotypes of segmented subvolumes and their use for biological radiotherapy treatment planning, this method may also provide parameters that could correlate to clinical outcomes in radiotherapy patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A Histogram-Free Multicanonical Monte Carlo Algorithm for the Basis Expansion of Density of States

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A copula-based rank histogram ensemble filter

Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems. The univariate inference problems are solved by sampling posterior probability densities obtained by combining constructed prior densities with observational likelihoods according to Bayes' rule. Many serial filters in the literature focus on representing the marginal posterior densities of each state. However, rigorously capturing the conditional dependencies between the different univariate inferences is crucial to correctly sampling multidimensional posteriors. This work proposes a new serial ensemble filter, called the copula rank histogram filter (CoRHF), that seeks to capture the conditional dependency structure between variables via empirical copula estimates; these estimates are used to rigorously implement the triangular (state-by-state univariate) Bayesian inference. The success of the CoRHF is demonstrated on two-dimensional examples and the Lorenz'63 problem. A practical extension to the high-dimensional setting is developed by localizing the empirical copula estimation, and is demonstrated on the Lorenz'96 problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Dynamic color mapping with a multi-scale histogram: A design study with physical scientists

Many research and development activities for scientific data analysis have focused on scalability challenges and data-driven features. Conversely, data visualization that focus on models requiring human interaction rarely involve practical and largescale scientific data analysis. Therefore, a gap exists between interactive data visualization and scientific data analysis applications. In this paper, we present a design study of interactive data visualization to support scientists who visually analyze data from neutron scattering experiments. This study was conducted in multiple phases: 1) problem characterization; 2) initial design and formative evaluation; and 3) iterative design. We characterize the problems and the design requirements for the analysis of the specific physical science data. We discuss the design, development, evaluation of our visual analytics tool and as well as our iterative developments with physical scientists. We show how to bridge the gap between the two disciplines uncovering new potential to solve their challenges in this design study. We focus on a specific challenge, finding an optimal color mapping, which plays a critical role in neutron scattering science and is broadly applicable to other scientific domains. To address the challenge, we propose two interactive visualization techniques: a dynamic color scale bar (DCSB) and a multi-scale histogram (MSH).

Chae, Junghoon↗
NASA NTRS1979

Multidimensional histograms

Program computes four dimensional histogram of Landsat multispectral image data. System enhances image handling and significantly reduces reprocessing costs.

Jayroe, R. R., Jr.↗
NASA NTRS2010

Landmark Detection in Orbital Images Using Salience Histograms

NASA's planetary missions have collected, and continue to collect, massive volumes of orbital imagery. The volume is such that it is difficult to manually review all of the data and determine its significance. As a result, images are indexed and searchable by location and date but generally not by their content. A new automated method analyzes images and identifies "landmarks," or visually salient features such as gullies, craters, dust devil tracks, and the like. This technique uses a statistical measure of salience derived from information theory, so it is not associated with any specific landmark type. It identifies regions that are unusual or that stand out from their surroundings, so the resulting landmarks are context-sensitive areas that can be used to recognize the same area when it is encountered again. A machine learning classifier is used to identify the type of each discovered landmark. Using a specified window size, an intensity histogram is computed for each such window within the larger image (sliding the window across the image). Next, a salience map is computed that specifies, for each pixel, the salience of the window centered at that pixel. The salience map is thresholded to identify landmark contours (polygons) using the upper quartile of salience values. Descriptive attributes are extracted for each landmark polygon: size, perimeter, mean intensity, standard deviation of intensity, and shape features derived from an ellipse fit.

Wagstaff, Kiri L.↗
NASA NTRS2018

Utilizing Brightness Temperature Histograms for Microwave Radiometer High Frequency (150-183 Ghz) Calibration

Spaceborne microwave radiometers with high frequency channels (150-183 GHz) are important for retrieving many geophysical parameters such as snowfall, ice water path, and atmospheric water vapor profiles. In order to obtain accurate retrievals from the brightness temperature measurements, the radiometers must be properly calibrated. Several methods have been developed to analyze the on-orbit calibration, including comparisons with radiative transfer models, comparisons with radiosonde profiles, and cross-calibration with similar radiometers. This paper introduces a new method to calibrate high frequency channels that utilizes TB histograms. This new method gives an independent approach that can be used by itself to analyze radiometer calibration or in conjunction with other methods to corroborate results.

microwave radiometry↗
DOE OSTI2017

A histogram-free multicanonical Monte Carlo algorithm for the construction of analytical density of states

We report a new multicanonical Monte Carlo (MC) algorithm to obtain the density of states (DOS) for physical systems with continuous state variables in statistical mechanics. Our algorithm is able to obtain an analytical form for the DOS expressed in a chosen basis set, instead of a numerical array of finite resolution as in previous variants of this class of MC methods such as the multicanonical (MUCA) sampling and Wang-Landau (WL) sampling. This is enabled by storing the visited states directly in a data set and avoiding the explicit collection of a histogram. This practice also has the advantage of avoiding undesirable artificial errors caused by the discretization and binning of continuous state variables. Our results show that this scheme is capable of obtaining converged results with a much reduced number of Monte Carlo steps, leading to a significant speedup over existing algorithms.

Li, Ying Wai↗
DOE OSTI2022

Method for determining a histogram of variable sample rate waveforms

A computer-implemented method comprises receiving a plurality of sampled data points, each data point including a y value and a t value; defining a plurality of bins; defining an array of elements; dividing the sampled data points into a plurality of sections; assigning a plurality of polynomial equations, one polynomial equation to each section, each polynomial equation having a waveform that fits the data points of the associated section; determining a plurality of section bin times, one section bin time for each bin in each section, each section bin time determined using the polynomial equation and indicating an amount of time that the waveform has values in the range of one of the bins; and adding the section bin time for each bin in each section to the histogram data in the array element pointed to by the number of the bin.

Tohlen, Michael Aaron↗
DOE OSTI2022

Register-Like Storage Block Used as Histograms, Cluster Buffers, and Hough Transform Accumulators for HEP Trigger Systems

In high energy physics experiment trigger systems, block memories are utilized for various purposes, especially in binned searching algorithms. In these algorithms, the storages are demanded to perform like a large set of registers. The writing and reading operation must be performed in single clock cycle and once an event is processed, the memory must be globally reset. These demands can be fulfilled with registers but the cost of using registers for large memory is unaffordable. Another common requirement is the boundary coverage feature during reading process. Additionally, when a memory bin is addressed, the stored contents in the addressed bin and its neighboring bin must be output simultaneously. In this paper, a register-like block storage design scheme is described, which allows updating memory locations in single clock cycle, reading two adjacent bins, and effectively refreshing entire memory within a single clock. The implementation and test results are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Method of predicting the mean lung dose based on a patient's anatomy and dose-volume histograms

The aim of this study was to propose a method to predict the minimum achievable mean lung dose (MLD) and corresponding dosimetric parameters for organs-at-risk (OAR) based on individual patient anatomy. For each patient, the dose for 36 equidistant individual multileaf collimator shaped fields in the treatment planning system (TPS) was calculated. Based on these dose matrices, the MLD for each patient was predicted by the homemade DosePredictor software in which the solution of linear equations was implemented. The software prediction results were validated based on 3D conformal radiotherapy (3D-CRT) and volumetric modulated arc therapy (VMAT) plans previously prepared for 16 patients with stage III non–small-cell lung cancer (NSCLC). For each patient, dosimetric parameters derived from plans and the results calculated by DosePredictor were compared. The MLD, the maximum dose to the spinal cord (D{sub max} {sub cord}) and the mean esophageal dose (MED) were analyzed. There was a strong correlation between the MLD calculated by the DosePredictor and those obtained in treatment plans regardless of the technique used. The correlation coefficient was 0.96 for both 3D-CRT and VMAT techniques. In a similar manner, MED correlations of 0.98 and 0.96 were obtained for 3D-CRT and VMAT plans, respectively. The maximum dose to the spinal cord was not predicted very well. The correlation coefficient was 0.30 and 0.61 for 3D-CRT and VMAT, respectively. The presented method allows us to predict the minimum MLD and corresponding dosimetric parameters to OARs without the necessity of plan preparation. The method can serve as a guide during the treatment planning process, for example, as initial constraints in VMAT optimization. It allows the probability of lung pneumonitis to be predicted.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Structure–property relationships in atomic-scale junctions: Histograms and beyond

Over the past 10 years, there has been tremendous progress in the measurement, modeling and understanding of structure–function relationships in single molecule junctions. Numerous research groups have addressed significant scientific questions, directed both to conductance phenomena at the single molecule level and to the fundamental chemistry that controls junction functionality. Many different functionalities have been demonstrated, including single-molecule diodes, optically and mechanically activated switches, and, significantly, physical phenomena with no classical analogues, such as those based on quantum interference effects. Experimental techniques for reliable and reproducible single molecule junction formation and characterization have led to this progress. In particular, the scanning tunneling microscope based break-junction (STM-BJ) technique has enabled rapid, sequential measurement of large numbers of nanoscale junctions allowing a statistical analysis to readily distinguish reproducible characteristics. Furthermore, harnessing fundamental link chemistry has provided the necessary chemical control over junction formation, enabling measurements that revealed clear relationships between molecular structure and conductance characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Flat-histogram extrapolation as a useful tool in the age of big data

In this work, we review recent work by the authors to revisit the concept of extrapolating thermodynamic properties of classical systems using statistical mechanical principles. Specifically, we discuss how the combination of these principles with biased sampling techniques enables the prediction of free energy landscapes and other detailed information, such as structural properties, of the system in question. Remarkably accurate estimates of physical properties across a broad range of conditions have been achieved using this approach, greatly reducing the number of simulations needed to explore a given system's behaviour. While approximate, these extrapolations significantly amplify the amount of reasonably accurate information that can be extracted from simulations enabling a small set of them to feed data-intensive regression algorithms such as neural networks. Thus, this extrapolation methodology represents a useful tool for performing tasks such as high-throughput screening of physical properties, optimising force field parameters, exploring equilibrium phase behaviour, and enabling theory-guided data science for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗