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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

WE-AB-204-01: Performance Characterization of Regularized-Reconstruction Algorithm for 90Y PET/CT Images

Purpose: {sup 90}Y PET/CT imaging and quantification have recently been suggested as an approach of treatment verification. However, due to low positron yield (32ppm), the {sup 90}Y-PET/CT images are very noisy. Iterative reconstruction techniques that employ regularization, e.g. block sequential regularized expectation maximization (BSREM) algorithm (recently implemented on GE scanners – QClear™), has the potential to increase quantitative accuracy with lower noise penalty compared to OSEM. Our aim is to investigate the performance of RR algorithms in {sup 90}Y PET/CT studies. Methods: A NEMA IEC phantom filled with 3GBq {sup 90}YCl{sub 2} (to simulate patient treatment) was imaged on GE-D690 for 1800s/bed. The sphere-to-background ratio of 7. The data were reconstructed using OSEM and BSREM with PSF modeling and TOF correction while varying the iterations (IT) from 1–6 with fixed 24subsets. For BSREM, the edge-preservation parameter (γ ) was 2 and the penalty-parameters (β) was varied 350–950. In all cases a post-reconstruction filter of 5.2mm (2pixel) transaxial and standard z-axis were used. Sphere average activity concentration (AC) and background standard deviation (SD) were then calculated from VOIs drawn in the spheres and background. Results: Increasing IT from 1to6, the %SD in OSEM increased from 30% to 80%, whereas %SD in BSREM images increased by <5% for all βs. BSREM with β=350 didn’t offer any improvement over OSEM (convergence of mean achieved at 2 IT, in this study). Increasing β from 350 to 950 reduced the AC accuracy of small spheres (<20mm) by 10% and noise from 40% to 20%, which resulted in CNR increase from 11 to 17. Conclusion: In count-limited studies such as {sup 90}Y PET/CT, BSREM can be used to suppress image noise and increase CNR at the expense of a relatively small decrease of quantitative accuracy. The BSREM parameters need to be optimized for each study depending on the radionuclides and count densities. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number R01CA13898 and was also partly supported by General Electric.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-J-226: Propagation of Pancreas Target Contours On Respiratory Correlated CT Images Using Deformable Image Registration

Purpose: Respiratory Correlated CT (RCCT) scans to assess intra-fraction motion among pancreatic cancer patients undergoing radiotherapy allow for dose sparing of normal tissues, in particular for the duodenum. Contour propagation of the gross tumor volume (GTV) from one reference respiratory phase to 9 other phases is time consuming. Deformable image registration (DIR) has been successfully used for high contrast disease sites but lower contrast for pancreatic tumors may compromise accuracy. This study evaluates the accuracy of Fast Free Form (FFF) registration-based contour propagation of the GTV on RCCT scans of pancreas cancer patients. Methods: Twenty-four pancreatic cancer patients were retrospectively studied; 20 had tumors in the pancreatic head/neck, 4 in the body/tail. Patients were simulated with RCCT and images were sorted into 10 respiratory phases. A radiation oncologist manually delineated the GTV for 5 phases (0%, 30%, 50%, 70% and 90%). The FFF algorithm was used to map deformations between the EE (50%) phase and each of the other 4 phases. The resultant deformation fields served to propagate GTV contours from EE to the other phases. The Dice Similarity Coefficient (DSC), which measures agreement between the DIR-propagated and manually-delineated GTVs, was used to quantitatively examine DIR accuracy. Results: Average DSC over all scans and patients is 0.82 and standard deviation is 0.09 (DSC range 0.97–0.57). For GTV volumes above and below the median volume of 20.2 cc, a Wilcoxon rank-sum test shows significantly different DSC (p=0.0000002). For the GTVs above the median volume, average +/− SD is 0.85 +/− 0.07; and for the GTVs below, the average +/− SD is 0.75 +/−0.08. Conclusion: For pancreatic tumors, the FFF DIR algorithm accurately propagated the GTV between the images in different phases of RCCT, with improved performance for larger tumors.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2010

Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

King, Michael D.↗
DOE OSTI2021

Hybrid Large Eddy Simulation/Reynolds-Averaged Navier–Stokes Analysis of a Premixed Ethylene-Fueled Dual-Mode Scramjet Combustor

Hydrocarbon fuels offer optimal high energy per volume for scramjet applications for sustained hypersonic flight but require additional residence time due to slower ignition delays (compared with hydrogen fuel). The injection of ethylene at the start of the isolator of a dual-mode scramjet combustor, operating in ramjet mode, allows sufficient mixing to achieve efficient premixed turbulent combustion. A cavity flameholder anchors the flame, supplying sufficient radicals to sustain a stable flame in the high-speed environment. This work investigates flame structure and stabilization limits of a new configuration with a scaled-down cavity embedded in the flow path of the combustor with a strut and insert. The cavity is reduced in size by one-third to enable eventual direct numerical simulations of the flame stabilization process. This work, however, focuses on modeling the full isolator/combustor geometry using a hybrid large eddy simulation/Reynolds-averaged Navier–Stokes simulation strategy. Additionally, particle image velocimetry, planar laser-induced fluorescence, coherent anti-Stokes Raman spectroscopy, and pressure measurements are compared with numerical predictions to analyze and characterize the conditions within the combustor, including flame structure, flow velocities, species composition, and wall pressure. An adjustable air throttle in the extender is able to control the placement of the shock train in the isolator and maintain a stable flame at various equivalence ratios. The simulations show reasonably good agreement with the experimental scalar and velocity data and predict a flame angle consistent with premixed turbulent flame-speed correlations.

42 ENGINEERING↗
NASA NTRS1992

The simulated space proton environment for radiation effects on Space Telescope Imaging Spectrograph (STIS)

The space telescope imaging spectrograph (STIS) is a second generation instrument planned for the Hubble Space Telescope (HST) which is currently in orbit. Candidate glasses and other transmitting materials are being considered for order sorters, in-flight calibration filters, detector windows, and calibration lamps. The glasses for in-flight calibration filters showed significant drop in UV transmission, but can probably still be used on STIS. The addressed topics include the Hubble radiation environment, simulation of orbital exposure at Harvard Cyclotron Laboratory, measurement of spectral transmission, and comments on individual samples.

Becher, Jacob↗
NASA NTRS2004

Comparison of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Earth Observing One (EO-1) Advanced Land Imager

We compare images from the Enhanced Thematic Mapper Plus (ETM+) sensor on Landsat-7 and the Advanced Land Imager (ALI) instrument on Earth Observing One (EO-1) over a test site in Rochester, New York. The site contains a variety of features, ranging from water of varying depths, deciduous/coniferous forest, and grass fields, to urban areas. Nearly coincident cloud-free images were collected one minute apart on 25 August 2001. We also compare images of a forest site near Howland, Maine, that were collected on 7 September, 2001. We atmospherically corrected each pair of images with the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmosphere model, using aerosol optical thickness and water vapor column density measured by in situ Cimel sun photometers within the Aerosol Robotic Network (AERONET), along with ozone density derived from the Total Ozone Mapping Spectrometer (TOMS) on the Earth Probe satellite. We present true-color composites from each instrument that show excellent qualitative agreement between the multispectral sensors, along with grey-scale images that demonstrate a significantly improved ALI panchromatic band. We quantitatively compare ALI and ETM+ reflectance spectra of a grassy field in Rochester and find < or equal to 6% differences in the visible/near infrared and approx. 2% differences in the short wave infrared. Spectral comparisons of forest sites in Rochester and Howland yield similar percentage agreement except for band 1, which has very low reflectance. Principal component analyses and comparison of normalized difference vegetation index histograms for each sensor indicate that the ALI is able to reproduce the information content in the ETM+ but with superior signal-to-noise performance due to its increased 12-bit quantization.

Pedelty, Jeffrey A.↗
DOE OSTI2025

Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction

X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.

X-ray tomography↗
NASA NTRS1989

Confusion-limited galaxy fields. II - Classical analyses

Chokshi and Wright presented a detailed model for simulating angular distribution of galaxy images in fields that extended to very high redshifts. Standard tools are used to analyze these simulated galaxy fields for the Omega(O) = 0 and the Omega(O) = 1 cases in order to test the discriminatory power of these tools. Classical number-magnitude diagrams and surface brightness-color-color diagrams are employed to study crowded galaxy fields. An attempt is made to separate the effects due to stellar evolution in galaxies from those due to the space time geometry. The results show that this discrimination is maximized at near-infrared wavelengths where the stellar photospheres are still visible but stellar evolution effects are less severe than those observed at optical wavelenghts. Rapid evolution of the stars on the asymptotic giant branch is easily recognized in the simulated data for both cosmologies and serves to discriminate between the two extreme values of Omega(O). Measurements of total magnitudes of individual galaxies are not essential for studying light distribution in galaxies as a function of redshift. Calculations for the extragalactic background radiation are carried out using the simulated data, and compared to integrals over the evolutionary models used.

Chokshi, Arati↗
NASA NTRS2010

Validation of Supersonic Film Cooling Modeling for Liquid Rocket Engine Applications

Topics include: upper stage engine key requirements and design drivers; Calspan "stage 1" results, He slot injection into hypersonic flow (air); test articles for shock generator diagram, slot injector details, and instrumentation positions; test conditions; modeling approach; 2-d grid used for film cooling simulations of test article; heat flux profiles from 2-d flat plate simulations (run #4); heat flux profiles from 2-d backward facing step simulations (run #43); isometric sketch of single coolant nozzle, and x-z grid of half-nozzle domain; comparison of 2-d and 3-d simulations of coolant nozzles (run #45); flowfield properties along coolant nozzle centerline (run #45); comparison of 3-d CFD nozzle flow calculations with experimental data; nozzle exit plane reduced to linear profile for use in 2-d film-cooling simulations (run #45); synthetic Schlieren image of coolant injection region (run #45); axial velocity profiles from 2-d film-cooling simulation (run #45); coolant mass fraction profiles from 2-d film-cooling simulation (run #45); heat flux profiles from 2-d film cooling simulations (run #45); heat flux profiles from 2-d film cooling simulations (runs #47, #45, and #47); 3-d grid used for film cooling simulations of test article; heat flux contours from 3-d film-cooling simulation (run #45); and heat flux profiles from 3-d and 2-d film cooling simulations (runs #44, #46, and #47).

Morris, Christopher I.↗
NASA NTRS2011

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Ballard, Jerrell R., Jr.↗
NASA NTRS1999

Hyperspectral Thermal Fabry-Perot Modeling

Fabry-Perot interferometer are simple elegant, tunable filters that can be used to make compact hyperspectral thermal imaging system. To foster the development of these sensors, software tools for the design and simulation of tunable Fabry-Perot infrared imagers have been developed. The tools are provided at three levels: basic, design, and system. Basic tools describe a nearly ideal Fabry-Perot filter with perfectly flat and parallel mirrors in collimated space. Design tools that take into account non-ideal behavior such as mirror and collimation defects calculate free spectral range, finesse, and spectral width of the interferometer. System tools help analyze an integration of the Fabry-Perot filter into a camera system. They include spectral convolution, first-order optical layout, and an estimation of signal-to-noise ratio. The complete set of tools allows for simulations of system operation and performance with various illumination sources. Spectral images generated in such simulations were used to examine applicability of Fabry-Perot system in remote sensing of atmospheric gases including detection of environmental pollutants and hazardous gases. Different operating conditions and system configurations are presented.

Ryan, Robert↗
DOE OSTI2014

Revisiting the adsorption of copper-phthalocyanine on Au(111) including van der Waals corrections

We have studied the adsorption of copper-phthalocyanine on Au(111) by means of van der Waals corrected density functional theory using the Tkatchenko-Scheffler method. We have compared the element and site resolved adsorption distances to recent experimental normal-incident X-ray standing wave measurements. The measured adsorption distances could be reproduced within a deviation of 1% for the Cu atom, 1% for the C atoms, and 2% for the N atoms. The molecule was found to have a magnetic moment of 1 μ{sub B} distributed over the Cu and the N atoms of the pyrrole ring. Simulated scanning tunnel microscopy images based on the total and on the spin-resolved differential charge densities are provided for bias voltages of −1.45 and 1.45 eV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Amplitude- and frequency-dependent activation of layer II/III neurons by intracortical microstimulation

Intracortical microstimulation (ICMS) has been used for the development of brain machine interfaces. However, further understanding about the spatiotemporal responses of neurons to different electrical stimulation parameters is necessary to inform the design of optimal therapies. In this study, we employed in vivo electrophysiological recording, two-photon calcium imaging, and electric field simulation to evaluate the acute effect of ICMS on layer II/III neurons. Our results show that stimulation frequency non-linearly modulates neuronal responses, whereas the magnitude of responses is linearly correlated to the electric field strength and stimulation amplitude before reaching a steady state. Temporal dynamics of neurons’ responses depends more on stimulation frequency and their distance to the stimulation electrode. In addition, amplitude-dependent post-stimulation suppression was observed within ~500 μm of the stimulation electrode, as evidenced by both calcium imaging and local field potentials. These findings provide insights for selecting stimulation parameters to achieve desirable spatiotemporal specificity of ICMS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images

Understanding the spatial interactions between the elements of the tumor microenvironment -i.e. tumor cells. fibroblasts, immune cells- and how these interactions relate to the diagnosis or prognosis of a tumor is one of the goals of computational pathology. We present NaroNet, a deep learning framework that models the multi-scale tumor microenvironment from multiplex-stained cancer tissue images and provides patient-level interpretable predictions using a seamless end-to-end learning pipeline. Trained only with multiplex-stained tissue images and their corresponding patient-level clinical labels, NaroNet unsupervisedly learns which cell phenotypes, cell neighborhoods, and neighborhood interactions have the highest influence to predict the correct label. To this end, NaroNet incorporates several novel and state-of-the-art deep learning techniques, such as patch-level contrastive learning, multi-level graph embeddings, a novel max-sum pooling operation, or a metric that quantifies the relevance that each microenvironment element has in the individual predictions. We validate NaroNet using synthetic data simulating multiplex-immunostained images where a patient label is artificially associated to the -adjustable- probabilistic incidence of different microenvironment elements. We then apply our model to two sets of images of human cancer tissues: 336 seven-color multiplex-immunostained images from 12 high-grade endometrial cancer patients; and 382 35-plex mass cytometry images from 215 breast cancer patients. In both synthetic and real datasets, NaroNet provides outstanding predictions of relevant clinical information while associating those predictions to the presence of specific microenvironment elements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Deep Learning Identifies High-$z$ Galaxies in a Central Blue Nugget Phase in a Characteristic Mass Range

We use machine learning to identify in color images of high-redshift galaxies an astrophysical phenomenon predicted by cosmological simulations. This phenomenon, called the blue nugget (BN) phase, is the compact star-forming phase in the central regions of many growing galaxies that follows an earlier phase of gas compaction and is followed by a central quenching phase. We train a convolutional neural network (CNN) with mock "observed" images of simulated galaxies at three phases of evolution— pre-BN, BN, and post-BN—and demonstrate that the CNN successfully retrieves the three phases in other simulated galaxies. We show that BNs are identified by the CNN within a time window of ~0.15 Hubble times. When the trained CNN is applied to observed galaxies from the CANDELS survey at $z$ = 1–3, it successfully identifies galaxies at the three phases. We find that the observed BNs are preferentially found in galaxies at a characteristic stellar mass range, 10 9.2–10.3 $M_⊙$ at all redshifts. This is consistent with the characteristic galaxy mass for BNs as detected in the simulations and is meaningful because it is revealed in the observations when the direct information concerning the total galaxy luminosity has been eliminated from the training set. This technique can be applied to the classification of other astrophysical phenomena for improved comparison of theory and observations in the era of large imaging surveys and cosmological simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Multimodal Nanoscale Tomographic Imaging for Battery Electrodes

Accurate representations of the 3D structure within a lithium-ion battery are key to understanding performance limitations. However, obtaining exact reconstructions of electrodes, where the active particles, the carbon black and polymeric binder domain, and the pore space are visualized is challenging. In this work, it is shown that multimodal imaging can be used to overcome this challenge. High-resolution ptychographic X-ray computed tomography are combined with lower resolution but higher contrast transmission X-ray tomographic microscopy to obtain 3D reconstructions of pristine and cycled graphite-silicon composite electrodes. This cross-correlation enables quantitative analysis of the surface of active particles, including the heterogeneity of carbon-black and binder domain and solid-electrolyte interphase coverage. Capturing the active particles as well as the carbon black-binder domain allows using these segmented structures for electrochemical simulations to highlight the influence of the particle embedding on local state of charge heterogeneities.

25 ENERGY STORAGE↗
DOE OSTI2016

STOCHASTIC PARTICLE ACCELERATION IN TURBULENCE GENERATED BY MAGNETOROTATIONAL INSTABILITY

We investigate stochastic particle acceleration in accretion flows. It is believed that magnetorotational instability (MRI) generates turbulence inside accretion flows and that cosmic rays (CRs) are accelerated by the turbulence. We calculate equations of motion for CRs in the turbulent fields generated by MRI with the shearing box approximation and without back reaction to the field. Our results show that the CRs randomly gain or lose their energy through interaction with the turbulent fields. The CRs diffuse in the configuration space anisotropically: the diffusion coefficient in the direction of the unperturbed flow is about 20 times higher than the Bohm coefficient, while those in the other directions are only a few times higher than the Bohm. The momentum distribution is isotropic and its evolution can be described by the diffusion equation in momentum space where the diffusion coefficient is a power-law function of the CR momentum. We show that the shear acceleration works efficiently for energetic particles. We also cautiously note that in the shearing box approximation, particles that cross the simulation box many times along the radial direction undergo unphysical runaway acceleration by the Lorentz transformation, which needs to be taken into account with special care.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Comprehensive characterization of ball-milled powders simulating a tribofilm system

A model system was used to simulate the properties of tribofilms which form during automotive braking. The model system was prepared by ball milling of a blend of 70 vol.% iron oxides, 15 vol.% molybdenum disulfide and 15 vol.% graphite. The resulting mixture was characterized by X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and various transmission electron microscopic (TEM) methods, including energy dispersive X-ray spectroscopy (EDXS), high resolution investigations (HRTEM) with corresponding simulation of the HRTEM images, diffraction methods such as scanning nano-beam electron diffraction (SNBED) and selected area electron diffraction (SAED). It could be shown that the ball milling caused a reduction of the grain size of the initial components to the nanometer range. Sometimes even amorphization or partial break-down of the crystal structure was observed for MoS{sub 2} and graphite. Moreover, chemical reactions lead to a formation of surface coverings of the nanoparticles by amorphous material, molybdenum oxides, and iron sulfates as derived from XPS. - Highlights: • Ball milling of iron oxides, MoS{sub 2}, and graphite to simulate a tribofilm • Increasing coefficient of friction after ball milling of the model blend • Drastically change of the diffraction pattern of the powder mixture • TEM & XPS showed the components of the milled mixture and the process during milling. • MoS{sub 2} and graphite suffered a loss in translation symmetry or became amorphous.

36 MATERIALS SCIENCE↗