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At least 1,315 records · Page 73

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NASA NTRS1977

Multiple loop activations and continuous energy release in the solar flare of June 15, 1973

The spatial and temporal evolution of the high-temperature plasma in the solar flare of June 15, 1973, is studied using XUV spectroheliograms and X-ray filtergrams obtained from Skylab. The analysis focuses on the changing forms and brightness of Fe XXIII 263-A and Fe XXIV 255-A images. Temperatures and emission measures computed for different times during the flare are compared with those derived from Solrad-9 flux data, the electron temperature in the bright compact core of the Fe XXIV image is determined, and a coronal origin is suggested for this bright core. The observational evidence shows that the overall flare event involved a number of different preexisting loops and arches which were activated in succession. The activation and heating are found to have persisted well past the end of the burst phase, implying that the energy release did not end when the impulsive phase was over. The overall development of the flare is summarized on the basis of the observed order of appearance of the loops.

Widing, K. G.↗

NASA NTRS1985

Voyager Cartography

The Jovian and Saturnian satellites are being mapped at several scales from Voyager 1 and 2 data. The maps include specially formatted color mosaics, controlled photomosaics, and airbrush maps. More than 500 Voyager images of the Jovian and Saturnian satellites were radiometrically processed in preparation for cartographic processing. Of these images, 235 were geometrically transformed to map projections for base mosaic compilations. Special techniques for producing hybrid photomosaic/airbrush maps of Callisto are under investigation. The techniques involve making controlled computer mosaics of all available images with highest resolution images superimposed on lowest resolution images. The mosaics are then improved by airbrushing: seams and artifacts are removed, and image details enhanced that had been lost by saturation in some images. A controlled mosaic of the northern hemisphere of Rhea is complete, as is all processing for a similar mosaic of the equatorial region. Current plans and status of the various series are shown in a table.

Batson, R. M.↗

DOE OSTI2022

Model-Based Reconstruction for Collimated Beam Ultrasound Systems

Collimated beam ultrasound systems are a novel technology for imaging inside multi-layered structures such as geothermal wells. Such systems include a transmitter and multiple receivers to capture reflected signals. Common algorithms for ultrasound reconstruction use delay-and-sum (DAS) approaches; these have low computational complexity but produce inaccurate images in the presence of complex structures and specialized geometries such as collimated beams.In this paper, we propose a multi-layer, ultrasonic, model-based iterative reconstruction algorithm designed for collimated beam systems. We introduce a physics-based forward model to accurately ac-count for the propagation of a collimated ultrasonic beam in multi-layer media and describe an efficient implementation using binary search. We model direct arrival signals, detector noise, and a spatially varying image prior, then cast the reconstruction as a maximum a posteriori estimation problem. Using simulated and experimental data we obtain significantly fewer artifacts relative to DAS while running in near real time using commodity compute resources.

Alanazi, Abdulrahman M.↗

DOE OSTI2022

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

Ptychography is a popular microscopic imaging modality for many scientific discoveries and sets the record for highest image resolution. Unfortunately, the high image resolution for ptychographic reconstruction requires significant amount of memory and computations, forcing many applications to compromise their image resolution in exchange for a smaller memory footprint and a shorter reconstruction time. In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles. In addition, we propose a parallel image gradient decomposition method that enables asynchronous point-to-point communications and parallel pipelining with minimal overhead on a large number of GPUs. Our experiments on a Titanate material dataset (PbTiO3) with 16632 probe locations show that our Gradient Decomposition algorithm reduces memory footprint by 51 times. In addition, it achieves time-to-solution within 2.2 minutes by scaling to 4158 GPUs with a super-linear strong scaling efficiency at 364% compared to runtimes at 6 GPUs. This performance is 2.7 times more memory efficient, 9 times more scalable and 86 times faster than the state-of-the-art algorithm.

Wang, Xiao↗

NASA NTRS1986

1985 Nuclear Science Symposium, 32nd, and 1985 Symposium on Nuclear Power Systems, 17th, San Francisco, CA, October 23-25, 1985, Proceedings

The present conference ranges over topics in high energy physics instrumentation, detectors, nuclear medical applications, health physics and environmental monitoring, reactor instrumentation, nuclear spacecraft instrumentation, the 'Fastbus' data acquisition system, circuits and systems for nuclear research facilities, and the development status of nuclear power systems. Specific attention is given to CCD high precision detectors, a drift chamber preamplifier, a Cerenkov ring imaging detector, novel scintillation glasses and scintillating fibers, a modular multidrift vertex detector, radial wire drift chambers, liquid argon polarimeters, a multianode photomultiplier, the reliability of planar silicon detectors, the design and manufacture of wedge and strip anodes, ultrafast triode photodetectors, photomultiplier tubes, a barium fluoride plastic scintillator, a fine grained neutron hodoscope, the stability of low leakage silicon photodiodes for crystal calorimeters, and X-ray proportional counters. Also considered are positron emission tomography, single photon emission computed tomography, nuclear magnetic resonance imaging, Geiger-Muller detectors, nuclear plant safeguards, a 32-bit Fastbus computer, an advanced light water reactor, and nuclear plant maintenance.

Source record↗

DOE OSTI2022

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1990

Learning receptor positions from imperfectly known motions

An algorithm is described for learning image interpolation functions for sensor arrays whose sensor positions are somewhat disordered. The learning is based on failures of translation invariance, so it does not require knowledge of the images being presented to the visual system. Previously reported implementations of the method assumed the visual system to have precise knowledge of the translations. It is demonstrated that translation estimates computed from the imperfectly interpolated images can have enough accuracy to allow the learning process to converge to a correct interpolation.

Ahumada, Albert J., Jr.↗

NASA NTRS1992

The rotation period, direction of the north pole, and geodetic control network of Venus

Three related activities that use Magellan data to derive improved estimates of the rotation period and direction of the spin axis of Venus are discussed. These are the computation of the Magellan geodetic control network, the use of measurement landmarks identified in overlapping image strips to improve the spacecraft ephemeris, and the use of common points identified on both the Venera 15/16 and the Magellan images. Since seven years separate the acquisition of the Magellan and Venera images, it should be possible to compute an accurate rotation period and possibly the spin vector of Venus.

Davies, M. E.↗

NASA NTRS1997

The Galileo Tape Recorder Rewind Operation Anomaly

On October 11, 1995, the Galileo spacecraft executed a sequence to record three approach images of Jupiter on the spacecraft's tape recorder, rewind the tape, and play back the images at the appropriate data rate consistent with the downlink performance. The recording of the images was performed and the spacecraft computer commanded the tape recorder to rewind the tape to the beginning of the first image. The rewind command was started at the proper time but the tape never got to the beginning of the image data. The analyses and tests that followed allowed a conclusive determination of the failure mechanism and indicated a strategy that could be used to prevent the untimely demise of the mission.

Johnson, Michael R.↗

NASA NTRS2017

Automated Mapping of Flood Events in the Mississippi River Basin Utilizing NASA Earth Observations

The Mississippi River Basin is the fourth largest drainage basin in the world, and is susceptible to multi-level flood events caused by heavy precipitation, snow melt, and changes in water table levels. Conducting flood analysis during periods of disaster is a challenging endeavor for NASA's Short-term Prediction Research and Transition Center (SPoRT), Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey's Hazards Data Distribution Systems (USGS HDDS) due to heavily-involved research and lack of manpower. During this project, an automated script was generated that performs high-level flood analysis to relieve the workload for end-users. The script incorporated Landsat 8 Operational Land Imager (OLI) tiles and utilized computer-learning techniques to generate accurate water extent maps. The script referenced the Moderate Resolution Imaging Spectroradiometer (MODIS) land-water mask to isolate areas of flood induced waters. These areas were overlaid onto the National Land Cover Database's (NLCD) land cover data, the Oak Ridge National Laboratory's LandScan data, and Homeland Infrastructure Foundation-Level Data (HIFLD) to determine the classification of areas impacted and the population density affected by flooding. The automated algorithm was initially tested on the September 2016 flood event that occurred in Upper Mississippi River Basin, and was then further tested on multiple flood events within the Mississippi River Basin. This script allows end users to create their own flood probability and impact maps for disaster mitigation and recovery efforts.

Bartkovich, Mercedes↗

NASA NTRS1975

Low-cost data analysis systems for processing multispectral scanner data

A research-oriented data analysis system was developed which is used for evaluating complex remote sensor systems and for development of techniques for application of remotely sensed data. Some modular hardware components were developed which may be added to one's existing facilities to establish a low-cost data analysis system for processing multispectral scanner data. Software modules which are compatible with small general purpose digital computers process and analyze remote sensor data, and convert it to information needed by users. The software modules are written in FORTRAN IV language for ease of transfer to other computer systems. The basic hardware and software system requirements are defined for some low-cost data analysis systems consisting of an image display system, a small general purpose digital computer, and an output recording device. The hardware modules consist of: a LANDSAT MSS data reformatting program; a series of spectral pattern recognition programs required to generate surface classification maps and tabular information; programs to convert computer generated maps from image space to a geographically referenced base; programs to extract data and irregularly shaped areas and to produce thematic maps of the designated areas; and programs to tabulate acreages of selected classification categories. Some off-the-shelf, inexpensive digital image display systems are described.

Whitley, S. L.↗

NASA NTRS1990

Hypermedia = hypercommunication

New hardware and software technology gave application designers the freedom to use new realism in human computer interaction. High-quality images, motion video, stereo sound and music, speech, touch, gesture provide richer data channels between the person and the machine. Ultimately, this will lead to richer communication between people with the computer as an intermediary. The whole point of hyper-books, hyper-newspapers, virtual worlds, is to transfer the concept and relationships, the 'data structure', from the mind of creator to that of user. Some of the characteristics of this rich information channel are discussed, and some examples are presented.

Laff, Mark R.↗

NASA NTRS1994

Determining Directional Emittance With An Infrared Imager

Directional emittances of flat specimen of smooth-surfaced, electrically nonconductive material at various temperatures computed from measurements taken by infrared radiometric imager operating in conjunction with simple ancillary equipment. Directional emittances useful in extracting detailed variations of surface temperatures from infrared images of curved, complexly shaped other specimens of same material. Advantages: simplification of measurement procedure and reduction of cost.

Daryabeigi, Kamran↗

NASA NTRS1995

Software to model AXAF-I image quality

A modular user-friendly computer program for the modeling of grazing-incidence type x-ray optical systems has been developed. This comprehensive computer software GRAZTRACE covers the manipulation of input data, ray tracing with reflectivity and surface deformation effects, convolution with x-ray source shape, and x-ray scattering. The program also includes the capabilities for image analysis, detector scan modeling, and graphical presentation of the results. A number of utilities have been developed to interface the predicted Advanced X-ray Astrophysics Facility-Imaging (AXAF-I) mirror structural and thermal distortions with the ray-trace. This software is written in FORTRAN 77 and runs on a SUN/SPARC station. An interactive command mode version and a batch mode version of the software have been developed.

Ahmad, Anees↗

DOE OSTI2023

Predicting wind-driven spatial deposition through simulated color images using deep autoencoders

Abstract For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to explain relationships in data. Powerful new algorithms can enable computers to learn physics by observing images and videos. Inspired by this idea, instead of training machine learning models using physical quantities, we used images, that is, pixel information. For this work, and as a proof of concept, the physics of interest are wind-driven spatial patterns. These phenomena include features in Aeolian dunes and volcanic ash deposition, wildfire smoke, and air pollution plumes. We use computer model simulations of spatial deposition patterns to approximate images from a hypothetical imaging device whose outputs are red, green, and blue (RGB) color images with channel values ranging from 0 to 255. In this paper, we explore deep convolutional neural network-based autoencoders to exploit relationships in wind-driven spatial patterns, which commonly occur in geosciences, and reduce their dimensionality. Reducing the data dimension size with an encoder enables training deep, fully connected neural network models linking geographic and meteorological scalar input quantities to the encoded space. Once this is achieved, full spatial patterns are reconstructed using the decoder. We demonstrate this approach on images of spatial deposition from a pollution source, where the encoder compresses the dimensionality to 0.02% of the original size, and the full predictive model performance on test data achieves a normalized root mean squared error of 8%, a figure of merit in space of 94% and a precision-recall area under the curve of 0.93.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

The use of computer graphic techniques for the determination of ventricular function.

Description of computer techniques employed to increase the speed, accuracy, reliability, and scope of angiocardiographic analyses determining human heart dimensions. Chamber margins are traced with a Calma 303 digitizer from projections of the angiographic films. The digitized margins of the ventricular images are filed in a computer for subsequent analysis. The margins can be displayed on the television screen of a graphics unit for individual study or they can be viewed in real time (or at any selected speed) to study dynamic changes in the chamber outline. The construction of three dimensional images of the ventricle is described.

Sandler, H.↗

DOE OSTI2024

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗

NASA NTRS1974

Automated analysis of video data

A software/hardware system designed and developed to perform automated video imagery analysis is described. Major elements included in the analysis system are: (1) sampling oscilloscope; (2) programmable trigger unit; (3) central computer; and (4) software processing library. The function of the scope and trigger unit, in conjunction with the control computer, is to digitize the selected portion of the video image and store as amplitude and time data in computer memory. Evaluation of the video data, analogus to interpretation of a visual image, is accomplished by the processing software. It is indicated that this technique of video image analysis is applicable to a wide variety of nonaerospace applications involving video data and image analysis.

Hafner, D. J.↗