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At least 1,315 records · Page 73

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.↗

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↗

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↗

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.↗

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.↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

THE MYSTERIOUS SICKLE OBJECT IN THE CARINA NEBULA: A STELLAR WIND INDUCED BOW SHOCK GRAZING A CLUMP?

Optical and near-infrared images of the Carina Nebula show a peculiar arc-shaped feature, which we call the ''Sickle'', next to the B-type star Trumpler 14 MJ 218. We use multi-wavelength observations to explore and constrain the nature and origin of the nebulosity. Using submillimeter data from APEX/LABOCA as well as Herschel far-infrared maps, we discovered a dense, compact clump with a mass of {approx}40 M{sub Sun} located close to the apex of the Sickle. We investigate how the B star MJ 218, the Sickle, and the clump are related. Our numerical simulations show that, in principle, a B-type star located near the edge of a clump can produce a crescent-shaped wind shock front, similar to the observed morphology. However, the observed proper motion of MJ 218 suggests that the star moves with high velocity ({approx}100 km s{sup -1}) through the ambient interstellar gas. We argue that the star is just about to graze along the surface of the clump, and the Sickle is a bow shock induced by the stellar wind, as the object moves supersonically through the density gradient in the envelope of the clump.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-F-T-205: Effectiveness of Robust Treatment Planning to Account for Inter- Fractional Variation in Intensity Modulated Proton Therapy for Head Neck Cancer

Purpose: To evaluate the potential benefits of robust optimization in intensity modulated proton therapy(IMPT) treatment planning to account for inter-fractional variation for Head Neck Cancer(HNC). Methods: One patient with bilateral HNC previous treated at our institution was used in this study. Ten daily CBCTs were selected. The CT numbers of the CBCTs were corrected by mapping the CT numbers from simulation CT via Deformable Image Registration. The planning target volumes(PTVs) were defined by a 3mm expansion from clinical target volumes(CTVs). The prescription was 70Gy, 54Gy to CTV1, CTV2, and PTV1, PTV2 for robust optimized(RO) and conventionally optimized(CO) plans respectively. Both techniques were generated by RayStation with the same beam angles: two anterior oblique and two posterior oblique angles. The similar dose constraints were used to achieve 99% of CTV1 received 100% prescription dose while kept the hotspots less than 110% of the prescription. In order to evaluate the dosimetric result through the course of treatment, the contours were deformed from simulation CT to daily CBCTs, modified, and approved by a radiation oncologist. The initial plan on the simulation CT was re-replayed on the daily CBCTs followed the bony alignment. The target coverage was evaluated using the daily doses and the cumulative dose. Results: Eight of 10 daily deliveries with using RO plan achieved at least 95% prescription dose to CTV1 and CTV2, while still kept maximum hotspot less than 112% of prescription compared with only one of 10 for the CO plan to achieve the same standards. For the cumulative doses, the target coverage for both RO and CO plans was quite similar, which was due to the compensation of cold and hot spots. Conclusion: Robust optimization can be effectively applied to compensate for target dose deficit caused by inter-fractional target geometric variation in IMPT treatment planning.

60 APPLIED LIFE SCIENCES↗

IFSAR Simulation Using the Shooting and Bouncing Ray Technique

Interferometric Synthetic Aperture Radar (IFSAR) is a technique that allows an automated way to carry out terrain mapping. IFSAR is carried out by first generating a SAR image pair from two antennas that are spatially separated. The phase difference between the SAR image pair is proportional to the topography. After registering the SAR images, the difference in phase in each pixel is extracted to generate an interferogram. Since the phase can only be measured within 2pi radians, phase unwrapping is carried out to extract the absolute phase for each pixel that will be proportional to the local height. While IFSAR algorithm is typically applied to measurement data, it is useful to develop an IFSAR simulator to develop a better understanding of the IFSAR technique. The IFSAR simulator can be used in choosing system parameters, experimenting with processing procedures and mission planning. In this paper we will present an IFSAR simulation methodology to simulate the interferogram based on the shooting and bouncing ray (SBR) technique. SBR is a standard ray-tracing technique used to simulate scattering from large, complex targets. SBR is carried out by shooting rays at the target or scene. At the exit point of each ray, a ray-tube integration is done to find its contribution to the total field. A fast algorithm has been developed for the SBR for simulating SAR images of complex targets. In the IFSAR simulation, we build upon the fast SAR simulation technique. Given the antenna pair configuration, radar system parameters and the geometrical description of the scene, we first simulate two SAR images from each antenna. After post processing the two SAR images, we generate an interferogram. Phase unwrapping is then performed on the interferogram to arrive at the desired terrain map. We will present results from the SBR-based IFSAR simulator. The results will include terrain map reconstruction of urban environments. The reconstruction will be compared to the ground truth to examine the fidelity of the simulation. We will also investigate the effect of multi-bounce scattering in urban environments on phase unwrapping and reconstruction.

Houshmand, Bijan↗

Investigation of Unsteady Flow Behavior in Transonic Compressor Rotors with LES and PIV Measurements

In the present study, unsteady flow behavior in a modern transonic axial compressor rotor is studied in detail with large eddy simulation (LES) and particle image velocimetry (PIV). The main purpose of the study is to advance the current understanding of the flow field near the blade tip in an axial transonic compressor rotor near the stall and peak-efficiency conditions. Flow interaction between the tip leakage vortex and the passage shock is inherently unsteady in a transonic compressor. Casing-mounted unsteady pressure transducers have been widely applied to investigate steady and unsteady flow behavior near the casing. Although many aspects of flow have been revealed, flow structures below the casing cannot be studied with casing-mounted pressure transducers. In the present study, unsteady velocity fields are measured with a PIV system and the measured unsteady flow fields are compared with LES simulations. The currently applied PIV measurements indicate that the flow near the tip region is not steady even at the design condition. This self-induced unsteadiness increases significantly as the compressor rotor operates near the stall condition. Measured data from PIV show that the tip clearance vortex oscillates substantially near stall. The calculated unsteady characteristics of the flow from LES agree well with the PIV measurements. Calculated unsteady flow fields show that the formation of the tip clearance vortex is intermittent and the concept of vortex breakdown from steady flow analysis does not seem to apply in the current flow field. Fluid with low momentum near the pressure side of the blade close to the leading edge periodically spills over into the adjacent blade passage. The present study indicates that stall inception is heavily dependent on unsteady behavior of the flow field near the leading edge of the blade tip section for the present transonic compressor rotor.

Hah, Chunill↗

Estimating nonrigid motion from inconsistent intensity with robust shape features

Purpose: To develop a nonrigid motion estimation method that is robust to heterogeneous intensity inconsistencies amongst the image pairs or image sequence. Methods: Intensity and contrast variations, as in dynamic contrast enhanced magnetic resonance imaging, present a considerable challenge to registration methods based on general discrepancy metrics. In this study, the authors propose and validate a novel method that is robust to such variations by utilizing shape features. The geometry of interest (GOI) is represented with a flexible zero level set, segmented via well-behaved regularized optimization. The optimization energy drives the zero level set to high image gradient regions, and regularizes it with area and curvature priors. The resulting shape exhibits high consistency even in the presence of intensity or contrast variations. Subsequently, a multiscale nonrigid registration is performed to seek a regular deformation field that minimizes shape discrepancy in the vicinity of GOIs. Results: To establish the working principle, realistic 2D and 3D images were subject to simulated nonrigid motion and synthetic intensity variations, so as to enable quantitative evaluation of registration performance. The proposed method was benchmarked against three alternative registration approaches, specifically, optical flow, B-spline based mutual information, and multimodality demons. When intensity consistency was satisfied, all methods had comparable registration accuracy for the GOIs. When intensities among registration pairs were inconsistent, however, the proposed method yielded pronounced improvement in registration accuracy, with an approximate fivefold reduction in mean absolute error (MAE = 2.25 mm, SD = 0.98 mm), compared to optical flow (MAE = 9.23 mm, SD = 5.36 mm), B-spline based mutual information (MAE = 9.57 mm, SD = 8.74 mm) and mutimodality demons (MAE = 10.07 mm, SD = 4.03 mm). Applying the proposed method on a real MR image sequence also provided qualitatively appealing results, demonstrating good feasibility and applicability of the proposed method. Conclusions: The authors have developed a novel method to estimate the nonrigid motion of GOIs in the presence of spatial intensity and contrast variations, taking advantage of robust shape features. Quantitative analysis and qualitative evaluation demonstrated good promise of the proposed method. Further clinical assessment and validation is being performed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗