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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Representation of Modes of Variability in 6 U.S. Climate Models

We compare the performance of several modes of variability across six US climate modeling groups, with a focus on identifying robust improvements in recent models (including those participating in the Coupled Model Intercomparison Project (CMIP) Phase 6) compared to previous versions. In particular, we examine the representation of the Madden-Julian Oscillation (MJO), the El Ni˜no/Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Quasi-Biennial Oscillation (QBO) in the tropical stratosphere and the dominant modes of extra-tropical variability, including the Southern Annular Mode (SAM), the Northern Annular Mode (NAM) (and the closely related North Atlantic Oscillation (NAO)), and the Pacific-North American Pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g. the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

Modes of variability↗
NASA NTRS2022

Megadroughts in the Common Era and the Anthropocene

Megadroughts, often lasting multiple decades, have caused major ecological and societal disturbances in the past. While most research has focused on megadroughts in North America, the concept has gained increased international attention in recent years. In this Review, we discuss shared causes and features of Common Era and future megadroughts. Paleoclimate reconstructions spanning the last 2,000 years document the occurrence of megadroughts on every continent, save Antarctica. Megadroughts are often linked to decadal variations in sea surface temperatures, with radiative forcing and land-atmosphere interactions acting as secondary factors. Anthropogenic climate change has already contributed to recent megadroughts in southwestern North America and Chile-Argentina and will likely increase future megadrought risk and severity in many regions. Notably, future megadroughts will be differentiated from past events through higher temperatures, which act as the main driver of increased risk, severity, and impacts. Major deficiencies in our understanding of natural and anthropogenic megadrought processes remain, however. These include 1) sparse high-resolution paleoclimate information over some regions, 2) incomplete representations of internal variability and land-surface processes in climate models, and 3) the undetermined capacity of water-resource management systems to manage megadrought impacts. Resolving these key uncertainties will be necessary to increase confidence in projections of future megadrought risk and resiliency planning.

Droughts↗
DOE OSTI2020

24.1.3.1.1 - Frisch Grid CZT Spectrometer

Brookhaven National Laboratory (BNL) worked with FLIR System Inc., the manufacturer of the nanoRAIDER, to develop a handheld field deployable detector based on the novel position-sensitive virtual Frisch-grid (VFG) Cadmium-Zinc-Telluride (CdZnTe or CZT) detectors (with 1% FWHM at 662 keV or better energy resolution). The detector called nanoRAIDER-VFG would be an improvement to the current nanoRAIDER, which is a compact gamma-ray detection instrument manufactured by FLIR Systems Inc. that employs relatively lower-performing CZT hemispheric detectors (i.e., 3%-FWHM CZT detectors). The nanoRAIDER-VFG would have significantly improved accuracy of measurements while maintaining similar efficiency, as compared to the nanoRAIDER, for in-field analysis of nuclear materials and detection of undeclared activities during inspections conducted by the International Atomic Energy Agency (IAEA). Since the nanoRAIDER is currently used by the IAEA as part of its Complementary Access toolkit, a relatively quick acceptance of the nanoRAIDER-VFG for safeguards was anticipated. The nanoRAIDER-VFG project was undertaken to address the following items in the IAEA's Long-Term R&D Plan, 2012-2023: 2.2 (elemental and isotopic signatures of fuel cycle processes); 2.3 (detect signatures of undeclared activity and improve analysis); and 2.6 (detect process emanations). The high energy-resolution of the nanoRAIDER-VFG would also have had applicability to 3.2 (fissile content of metal mixtures containing actinides Np, Am, etc.). The project was not completed due to a change in priorities within FLIR.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Holistic digital gamma-ray spectroscopy methods and instrumentation for high-throughput high-resolution applications

Method of real-time adaptive digital pulse signal processing for high count rate gamma-ray spectroscopy applications includes receiving a preamplifier signal at a pulse deconvolver, the preamplifier signal including resolution deterioration resulting from pulse pile-up. The method further includes generating a deconvoluted signal, by the pulse deconvolver, from the preamplifier signal, the deconvoluted signal having less resolution deterioration as compared to the received preamplifier signal. The method furthermore includes shaping of the deconvoluted signal by a trapezoid filter, the shaping comprising adjusting a shaping parameter of the trapezoid filter for an incoming signal based on a time separation from a subsequent incoming signal.

Hawari, Ayman I.↗
DOE OSTI2021

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

The wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical–meteorological interactions that drive high-pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in western U.S. basins. Approximately 120 people participated, representing 50 institutions and five countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological–chemical linkages outlined here, nor to validate complex processes within coupled atmosphere–chemistry models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

High Resolution Camera for Mapping Titan Surface

Titan, Saturn's largest moon, has a dense atmosphere and is the only object besides Earth to have stable liquids at its surface. The Cassini/Huygens mission has revealed the extraordinary breadth of geological processes shaping its surface. Further study requires high resolution imaging of the surface, which is restrained by light absorption by methane and scattering from aerosols. The Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft has demonstrated that Titan's surface can be observed within several windows in the near infrared, allowing us to process several regions in order to create a geological map and to determine the morphology. Specular reflections monitored on the lakes of the North Pole show little scattering at 5 microns, which, combined with the present study of Titan's northern pole area, refutes the paradigm that only radar can achieve high resolution mapping of the surface. The present data allowed us to monitor the evolution of lakes, to identify additional lakes at the Northern Pole, to examine Titan's hypothesis of non-synchronous rotation and to analyze the albedo of the North Pole surface. Future missions to Titan could carry a camera with 5 micron detectors and a carbon fiber radiator for weight reduction.

Cassini↗
DOE OSTI2026

Engineering Assembly Kinetics and Line Roughness in Solvent Vapor-Annealed Block Copolymer/Homopolymer Blends

Block copolymer (BCP) directed self-assembly (DSA) is a promising route to enhance lithography resolution by multiplying nanopattern density and reducing feature roughness. Eliminating kinetically trapped self-assembly defects requires fast self-assembly. However, acceleration strategies like solvent vapor annealing or homopolymer blending broaden domain interfaces, implying a trade-off in increased feature roughness. In this work, we experimentally investigate this apparent dilemma between self-assembly kinetics and line roughness for solvent vapor-annealed thin films of a lamellar poly(styrene-block-2-vinylpyridine) (PS-b-P2VP) BCP blended with PS and P2VP homopolymers. Binary blends with PS or P2VP homopolymers and ternary blends incorporating both in equal weight fractions were solvent vapor annealed using acetone, a near-neutral solvent for PS and P2VP, followed by P2VP-selective vapor-phase infiltration with alumina (AlOx) and polymer etching. Binary blends with P2VP exhibit a modest kinetic enhancement but also higher line-edge and -width roughness due to the increased frequency of P2VP protrusions and bridge defects in the alumina line patterns. In contrast, binary blends with PS self-assemble noticeably faster, while domain asymmetry from the added PS homopolymer reduces roughness by curbing the number of alumina protrusions and bridge defects. Ternary blends maintain DSA line patterns across a wider composition window and, at higher homopolymer loadings, reduce roughness at length scales near the lamellar period, consistent with a reduced impact of intradomain compositional fluctuations. These findings provide important insights for codesigning blend compositions and process flows to achieve high-resolution, defect free patterns with minimal roughness through BCP DSA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2007

Production and Distribution of NASA MODIS Remote Sensing Products

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Wolfe, Robert↗
NASA NTRSDate not supplied

Geometric Assessment of PlanetScope Imagery

Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.

Alana G. Semple↗
NASA NTRS1977

High-resolution electron microscope

Employing scanning transmission electron microscope as interferometer, relative phases of diffraction maximums can be determined by analysis of dark field images. Synthetic aperture technique and Fourier-transform computer processing of amplitude and phase information provide high resolution images at approximately one angstrom.

Nathan, R.↗
DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗
NASA NTRS1990

Spatial analysis of IRAS observations of nearby spirals

The unbiased survey of the infrared sky carried out by the Infrared Astronomy Satellite (IRAS) satellite has greatly accelerated advances in understanding the dust component of our own and external galaxies. However, most extragalactic studies to date have been based on the IRAS Point Source Catalog (PSC), which has two serious limitations. First, in sources where a significant fraction of the flux is extended, significant errors may result from using PSC fluxes in comparative studies, and these errors could be systematic if the tendency to be non-pointlike depends on physical properties of the galaxy. Additionally, use of PSC fluxes rules out any direct investigation of the spatial distribution of the IRAS emission from disks in external galaxies. Since work on the Galactic IRAS results has shown that very different physical processes can make varying contributions to the observed flux, it is important to look at a wide sample of galaxies with some spatial resolution to study the relative dominance of these processes under a variety of conditions. Here, researchers report on work they are doing to carry out this program for many nearby spirals, using an analysis package that was developed for this purpose. Researchers carried out analysis for a sample of 121 nearby spirals. The fraction of the flux contained in a point source varies from 0 to 1 across the sample, all of which are well resolved at their nominal optical diameters. There is no evidence that the galaxies of smaller angular size are less likely to be resolved by IRAS at this level. The program gives results which are quite repeatable from scan to scan; the fraction f (point source flux over total flux) at 60 microns has typical errors of 0.03 when different scans are combined. Approximately two-thirds of the sample have more flux in the extended than in the nuclear component. There is a tendency for earlier-type spirals to be less centrally concentrated, but this effect is slight and the degree of variation is large for all types. Barred spirals are also found across the spectrum of f, but are much more likely to have little or no nuclear emission.

Ball, Roger↗
NASA NTRS1991

High resolution ultrasonic spectroscopy system for nondestructive evaluation

With increased demand for high resolution ultrasonic evaluation, computer based systems or work stations become essential. The ultrasonic spectroscopy method of nondestructive evaluation (NDE) was used to develop a high resolution ultrasonic inspection system supported by modern signal processing, pattern recognition, and neural network technologies. The basic system which was completed consists of a 386/20 MHz PC (IBM AT compatible), a pulser/receiver, a digital oscilloscope with serial and parallel communications to the computer, an immersion tank with motor control of X-Y axis movement, and the supporting software package, IUNDE, for interactive ultrasonic evaluation. Although the hardware components are commercially available, the software development is entirely original. By integrating signal processing, pattern recognition, maximum entropy spectral analysis, and artificial neural network functions into the system, many NDE tasks can be performed. The high resolution graphics capability provides visualization of complex NDE problems. The phase 3 efforts involve intensive marketing of the software package and collaborative work with industrial sectors.

Chen, C. H.↗
NASA NTRS1982

An information theory characterization of radar images and a new definition for radiometric resolution

The noise properties of the radar image formation process are used in the present modeling of a communication channel in which the desired target properties are the information transmitted, and the final image represents the received signal. The average information rate over this communication channel is calculated together with appropriate bounds and approximations, and is found to be small on a per-sample basis. As a result, many samples must be averaged to allow for the discrimination, or classification, of several levels of target reflectivity. These information rate properties are consistent with known results concerning target detection and image quality in speckle, and the rate is applicable to the definition of radar image radiometric resolution. Radiometric resolution is functionally related to the degree of noncoherent averaging performed by the sensor.

Frost, V. S.↗
NASA NTRS2004

High Resolution Digital Elevation Models of Pristine Explosion Craters

In order to effectively capture a realistic terrain applicable to studies of cratering processes and landing hazards on Mars, we have obtained high resolution digital elevation models of several pristine explosion craters at the Nevada Test Site. We used the Airborne Terrain Mapper (ATM), operated by NASA's Wallops Flight Facility to obtain DEMs with 1 m spacing and 10 cm vertical errors of 4 main craters and many other craters and collapse pits. The main craters that were mapped are Sedan, Scooter, Schooner, and Danny Boy. The 370 m diameter Sedan crater, located on Yucca Flat, is the largest and freshest explosion crater on Earth that was formed under conditions similar to hypervelocity impact cratering. As such, it is effectively pristine, having been formed in 1962 as a result of a controlled detonation of a 100 kiloton thermonuclear device, buried at the appropriate equivalent depth of burst required to make a simple crater. Sedan was formed in alluvium of mixed lithology and subsequently studied using a variety of field-based methods. Nearby secondary craters were also formed at the time and were also mapped by ATM. Adjacent to Sedan and also in alluvium is Scooter, about 90 m in diameter and formed by a high-explosive event. Schooner (240 m) and Danny Boy (80 m) craters were also important targets for ATM as they were excavated in hard basalt and therefore have much rougher ejecta. This will allow study of ejecta patterns in hard rock as well as engineering tests of crater and rock avoidance and rover trafficability. In addition to the high resolution DEMs, crater geometric characteristics, RMS roughness maps, and other higher-order derived data products will be generated using these data. These will provide constraints for models of landing hazards on Mars and for rover trafficability. Other planned studies will include ejecta size-frequency distribution at the resolution of the DEM and at finer resolution through air photography and field measurements, correlation of ejecta size and composition with radar and visible-thermal IR remote sensing signatures, and comparison of these results with similar measurements of Mars. The final DEMs, ancillary data sets, and derived data products will be made available to the community.

T G Farr↗
DOE OSTI2022

Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Abstract Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Debunking common myths in coastal circulation modeling

Despite tremendous progress in algorithm development, computational efficiency and transition into operations over the past two decades, coastal modeling still lacks scientific rigor due to proliferation of many ‘gray’ areas related to various modeling choices made by modelers. Here, in this paper, we propose some guiding principles for the modeling community to improve performance, and we also debunk commonly held myths that make the coastal modeling lack rigor. Using our own experience in developing seamless cross-scale unstructured-grid based models for the past two decades, we describe in unprecedented detail the end-to-end modeling process (i.e., from digital elevation models (DEMs) to mesh generation to post analysis), and demonstrate that defensible modeling is within reach for any end user by following three guiding principles: (1) Bathymetry is a first order forcing in coastal domains and thus should be respected in all aspects of modeling; (2) Oceanographic processes are driven across multiple spatial scales and so models should enable appropriate resolution as needed; and (3) Model assessment should focus on physical processes. Through qualitative and quantitative model assessments, we demonstrate the fundamental role played by bathymetry/topography as embedded in DEMs in making the results defensible, which is unfortunately glossed over in many modeling studies. Focusing on process-based assessment simplifies the calibration process. A major conclusion of this work is that model developers and operators should maximize the scientific rigor for in silico oceanography by avoiding some common pitfalls that rely on error compensation at the expense of representation of physical system processes. We present some best practice procedures for defensive and trustworthy numerical modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Knasel, T. Michael↗