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Results for “cell imaging”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Spatial quantification of maps or images - Cell size or pixel size implications

The paper discusses spatial quantification of maps or images. Spatial accuracies evaluated by mapping and inventory measures were observed with a range of cell sizes for a 10.36 sq km soil survey segment. The distribution of interboundary distances in a map was evaluated as unique, characterizing information; experimentally observed relationships between accuracy and cell size and interboundary distance distribution parameters and cell size led to a model of the process of spatial quantization. Grid positioning effects were evaluated and were significant only at the level of individual mapping units; two generations of 'universal' process models were derived, implemented, and evaluated.

Wehde, M. E.↗
NASA NTRS1989

Improved defect analysis of Gallium Arsenide solar cells using image enhancement

A new technique has been developed to capture, digitize, and enhance the image of light emission from a forward biased direct bandgap solar cell. Since the forward biased light emission from a direct bandgap solar cell has been shown to display both qualitative and quantitative information about the solar cell's performance and its defects, signal processing techniques can be applied to the light emission images to identify and analyze shunt diodes. Shunt diodes are of particular importance because they have been found to be the type of defect which is likely to cause failure in a GaAs solar cell. The presence of a shunt diode can be detected from the light emission by using a photodetector to measure the quantity of light emitted at various current densities. However, to analyze how the shunt diodes affect the quality of the solar cell the pattern of the light emission must be studied. With the use of image enhancement routines, the light emission can be studied at low light emission levels where shunt diode effects are dominant.

Kilmer, Louis C.↗
NASA NTRS2008

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

wave-front sensing and control↗
NASA NTRS1999

Model system for plant cell biology: GFP imaging in living onion epidermal cells

The ability to visualize organelle localization and dynamics is very useful in studying cellular physiological events. Until recently, this has been accomplished using a variety of staining methods. However, staining can give inaccurate information due to nonspecific staining, diffusion of the stain or through toxic effects. The ability to target green fluorescent protein (GFP) to various organelles allows for specific labeling of organelles in vivo. The disadvantages of GFP thus far have been the time and money involved in developing stable transformants or maintaining cell cultures for transient expression. In this paper, we present a rapid transient expression system using onion epidermal peels. We have localized GFP to various cellular compartments (including the cell wall) to illustrate the utility of this method and to visualize dynamics of these compartments. The onion epidermis has large, living, transparent cells in a monolayer, making them ideal for visualizing GFP. This method is easy and inexpensive, and it allows for testing of new GFP fusion proteins in a living tissue to determine deleterious effects and the ability to express before stable transformants are attempted.

NASA Discipline Plant Biology↗
NASA NTRS1981

Improved cell for water-vapor electrolysis

Continuous-flow electrolytic cells decompose water vapor in steam and room air into hydrogen and oxygen. Sintered iridium oxide catalytic anode coating yields dissociation rates hundredfold greater than those obtained using platinum black. Cell consists of two mirror-image cells, with dual cathode sandwiched between two anodes. Gas traverses serpentine channels within cell and is dissociated at anode. Oxygen mingles with gas stream, while hydrogen migrates through porous matrix and is liberated as gas at cathode.

Aylward, J. R.↗
NASA NTRS1987

Recombination imaging of III-V solar cells

An imaging technique based on the radiative recombination of minority carriers in forward-biased solar cells has been developed for characterization of III-V solar cells. When used in mapping whole wafers, it has helped identify three independent loss mechanisms (broken grid lines, shorting defects, and direct-to-indirect bandgap transitions), all of which resulted in lower efficiencies. The imaging has also led to improvements in processing techniques to reduce the occurrence of broken gridlines as well as surface defects. The ability to visualize current mechanisms in solar cells is an intuitive tool which is powerful in its simplicity.

Virshup, G. F.↗
NASA NTRS2002

Overexpression of neurofilament H disrupts normal cell structure and function

Studying exogenously expressed tagged proteins in live cells has become a standard technique for evaluating protein distribution and function. Typically, expression levels of experimentally introduced proteins are not regulated, and high levels are often preferred to facilitate detection. However, overexpression of many proteins leads to mislocalization and pathologies. Therefore, for normative studies, moderate levels of expression may be more suitable. To understand better the dynamics of intermediate filament formation, transport, and stability in a healthy, living cell, we inserted neurofilament heavy chain (NFH)-green fluorescent protein (GFP) fusion constructs in adenoviral vectors with tetracycline (tet)-regulated promoters. This system allows for turning on or off the synthesis of NFH-GFP at a selected time, for a defined period, in a dose-dependent manner. We used this inducible system for live cell imaging of changes in filament structure and cell shape, motility, and transport associated with increasing NFH-GFP expression. Cells with low to intermediate levels of NFH-GFP were structurally and functionally similar to neighboring, nonexpressing cells. In contrast, overexpression led to pathological alterations in both filament organization and cell function. Copyright 2002 Wiley-Liss, Inc.

Non-NASA Center↗
NASA NTRS2007

Adaptive Cross-correlation Algorithm and Experiment of Extended Scene Shack-Hartmann Wavefront Sensing

We have developed a new, adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels in two extended-scene images captured by a Shack-Hartmann wavefront sensor (SH-WFS). It determines the positions of all of the extended-scene image cells relative to a reference cell using an FFT-based iterative image shifting algorithm. It works with both point-source spot images as well as extended scene images. We have also set up a testbed for extended0scene SH-WFS, and tested the ACC algorithm with the measured data of both point-source and extended-scene images. In this paper we describe our algorithm and present out experimental results.

Shack - Hartmann sensor↗
NASA NTRS1993

Bayesian image reconstruction - The pixon and optimal image modeling

In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

Pina, R. K.↗
NASA NTRS1974

Automated thematic mapping and change detection of ERTS-1 images

Results of an automated thematic mapping investigation using ERTS-1 MSS images are presented. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas, and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains and urban areas. To eliminate the need for training data, a new clustering algorithm has also been developed.

Gramenopoulos, N.↗
NASA NTRS1984

High speed quantitative digital microscopy

Modern digital image processing hardware makes possible quantitative analysis of microscope images at high speed. This paper describes an application to automatic screening for cervical cancer. The system uses twelve MC6809 microprocessors arranged in a pipeline multiprocessor configuration. Each processor executes one part of the algorithm on each cell image as it passes through the pipeline. Each processor communicates with its upstream and downstream neighbors via shared two-port memory. Thus no time is devoted to input-output operations as such. This configuration is expected to be at least ten times faster than previous systems.

Castleman, K. R.↗
NASA NTRS2003

Biological Visualization, Imaging and Simulation(Bio-VIS) at NASA Ames Research Center: Developing New Software and Technology for Astronaut Training and Biology Research in Space

The Bio- Visualization, Imaging and Simulation (BioVIS) Technology Center at NASA's Ames Research Center is dedicated to developing and applying advanced visualization, computation and simulation technologies to support NASA Space Life Sciences research and the objectives of the Fundamental Biology Program. Research ranges from high resolution 3D cell imaging and structure analysis, virtual environment simulation of fine sensory-motor tasks, computational neuroscience and biophysics to biomedical/clinical applications. Computer simulation research focuses on the development of advanced computational tools for astronaut training and education. Virtual Reality (VR) and Virtual Environment (VE) simulation systems have become important training tools in many fields from flight simulation to, more recently, surgical simulation. The type and quality of training provided by these computer-based tools ranges widely, but the value of real-time VE computer simulation as a method of preparing individuals for real-world tasks is well established. Astronauts routinely use VE systems for various training tasks, including Space Shuttle landings, robot arm manipulations and extravehicular activities (space walks). Currently, there are no VE systems to train astronauts for basic and applied research experiments which are an important part of many missions. The Virtual Glovebox (VGX) is a prototype VE system for real-time physically-based simulation of the Life Sciences Glovebox where astronauts will perform many complex tasks supporting research experiments aboard the International Space Station. The VGX consists of a physical display system utilizing duel LCD projectors and circular polarization to produce a desktop-sized 3D virtual workspace. Physically-based modeling tools (Arachi Inc.) provide real-time collision detection, rigid body dynamics, physical properties and force-based controls for objects. The human-computer interface consists of two magnetic tracking devices (Ascention Inc.) attached to instrumented gloves (Immersion Inc.) which co-locate the user's hands with hand/forearm representations in the virtual workspace. Force-feedback is possible in a work volume defined by a Phantom Desktop device (SensAble inc.). Graphics are written in OpenGL. The system runs on a 2.2 GHz Pentium 4 PC. The prototype VGX provides astronauts and support personnel with a real-time physically-based VE system to simulate basic research tasks both on Earth and in the microgravity of Space. The immersive virtual environment of the VGX also makes it a useful tool for virtual engineering applications including CAD development, procedure design and simulation of human-system systems in a desktop-sized work volume.

Smith, Jeffrey↗
NASA NTRS2017

Field Exploration and Life Detection Sampling Through Planetary Analogue Sampling (FELDSPAR).

Exploration missions to Mars rely on rovers to perform analyses over small sampling areas; however, landing sites for these missions are selected based on large-scale, low-resolution remote data. The use of Earth analogue environments to estimate the multi-scale spatial distributions of key signatures of habitability can help ensure mission science goals are met. A main goal of FELDSPAR is to conduct field operations analogous to Mars sample return in its science, operations, and technology from landing site selection, to in-field sampling location selection, remote or stand-off analysis, in situ analysis, and home laboratory analysis. Lava fields and volcanic regions are relevant analogues to Martian landscapes due to desiccation, low nutrient availability, and temperature extremes. Operationally, many Icelandic lava fields are remote enough to require that field expeditions address several sampling constraints that are experienced in robotic exploration, including in situ and sample return missions. The Fimmvruhls lava field was formed by a basaltic effusive eruption associated with the 2010 Eyjafjallajkull eruption. Mlifellssandur is a recently deglaciated plain to the north of the Myrdalsjkull glacier. Holuhraun was formed by a 2014 fissure eruptions just north of the large Vatnajkull glacier. Dyngjusandur is an alluvial plain apparently kept barren by repeated mechanical weathering. Informed by our 2013 expedition, we collected samples in nested triangular grids every decade from the 10 cm scale to the 1 km scale (as permitted by the size of the site). Satellite imagery is available for older sites, and for Mlifellssandur, Holuhraun, and Dyngjusandur we obtained overhead imagery at 1 m to 200 m elevation. PanCam-style photographs were taken in the field by sampling personnel. In-field reflectance spectroscopy was also obtained with an ASD spectrometer in Dyngjusandur. All sites chosen were 'homogeneous' in apparent color, morphology, moisture, grain size, and reflectance spectra at all scales greater than 10 cm. Field lab assays were conducted to monitor microbial habitation, including ATP quantification, qPCR for fungal, bacterial, and archaeal DNA, and direct cell imaging using fluorescence microscopy. Home laboratory analyses include Raman spectroscopy and community sequencing. ATP appeared to be significantly more sensitive to small changes in sampling location than qPCR or fluorescence microscopy. Bacterial and archaeal DNA content were more consistent at the smaller scales, but similarly variable across more distant sites. Conversely, cell counts and fungal DNA content have significant local variation but appear relatively homogeneous over scales of 1 km. ATP, bacterial DNA, and archaeal DNA content were relatively well correlated at many spatial scales. While we have observed spatial variation at various scales and are beginning to observe how that variation fluctuates over time as biodiversity recovers after an eruption, we do not yet fully understand what parameters lead to the observed spatial variation. Home laboratory analyses will help us further understand the elemental and structural composition of the basaltic matrices, but further field analyses are vital for the understanding how temperature, moisture, incident radiation, and so forth influence the habitability of a microclimate.

Field↗
NASA NTRS1974

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. A diffraction pattern analysis of MSS images led to the development of spatial signatures for farm land, urban areas and mountains. Four spatial features are employed to describe the spatial characteristics of image cells in the digital data. Three spectral features are combined with the spatial features to form a seven dimensional vector describing each cell. Then, the classification of the feature vectors is accomplished by using the maximum likelihood criterion. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month, but vary substantially between seasons. Three ERTS-1 images from the Phoenix, Arizona area were processed, and recognition rates between 85% and 100% were obtained for the terrain classes of desert, farms, mountains, and urban areas. To eliminate the need for training data, a new clustering algorithm has been developed. Seven ERTS-1 images from four test sites have been processed through the clustering algorithm, and high recognition rates have been achieved for all terrain classes.

Gramenopoulos, N.↗
NASA NTRS1973

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. For the recognition of terrain types, spatial signatures are developed from the diffraction patterns of small areas of ERTS-1 images. This knowledge is exploited for the measurements of a small number of meaningful spatial features from the digital Fourier transforms of ERTS-1 image cells containing 32 x 32 picture elements. Using these spatial features and a heuristic algorithm, the terrain types in the vicinity of Phoenix, Arizona were recognized by the computer with a high accuracy. Then, the spatial features were combined with spectral features and using the maximum likelihood criterion the recognition accuracy of terrain types increased substantially. It was determined that the recognition accuracy with the maximum likelihood criterion depends on the statistics of the feature vectors. Nonlinear transformations of the feature vectors are required so that the terrain class statistics become approximately Gaussian. It was also determined that for a given geographic area the statistics of the classes remain invariable for a period of a month but vary substantially between seasons.

Gramenopoulos, N.↗
NASA NTRS2007

Biochemical Kinetics Model of DSB Repair and GammaH2AX FOCI by Non-homologous End Joining

We developed a biochemical kinetics approach to describe the repair of double strand breaks (DSB) produced by low LET radiation by modeling molecular events associated with the mechanisms of non-homologous end-joining (NHEJ). A system of coupled non-linear ordinary differential equations describes the induction of DSB and activation pathways for major NHEJ components including Ku(sub 70/80), DNA-PK(sub cs), and the Ligase IV-XRCC4 hetero-dimer. The autophosphorylation of DNA-PK(sub cs and subsequent induction of gamma-H2AX foci observed after ionizing radiation exposure were modeled. A two-step model of DNA-PK(sub cs) regulation of repair was developed with the initial step allowing access of other NHEJ components to breaks, and a second step limiting access to Ligase IV-XRCC4. Our model assumes that the transition from the first to second-step depends on DSB complexity, with a much slower-rate for complex DSB. The model faithfully reproduced several experimental data sets, including DSB rejoining as measured by pulsed-field electrophoresis (PFGE), quantification of the induction of gamma-H2AX foci, and live cell imaging of the induction of Ku(sub 70/80). Predictions are made for the behaviors of NHEJ components at low doses and dose-rates, where a steady-state is found at dose-rates of 0.1 Gy/hr or lower.

Cucinotta, Francis, A.↗
NASA NTRSDate not supplied

Characterization and Modeling of Cell Wall Imperfections in Aluminum Honeycomb Cores using X-ray CT Imaging

Honeycomb cell imperfections may significantly affect the failure of sandwich composites in core crushing and shear modes. Identification and quantification of the different types of imperfections and evaluation of their effects on the mechanical response of honeycomb cores in flatwise compression is presented. X-Ray computed tomography (CT) scans of honeycomb cores in co-cured composite sandwich panels were performed. Image analysis methods are applied to characterize and quantify core cell geometry and cell wall waviness. An approach is developed for extracting cell wall mid surface planes and waviness for constructing finite element models using shell elements. Analysis results from models with the as-manufactured imperfections are compared to results from models with idealized geometries to evaluate the effect of the as-manufactured imperfections on the initiation of cell wall buckling and subsequent core crushing.

aluminum honeycomb↗
NASA NTRSDate not supplied

Electroluminescence Imaging: A Quantitative Characterization Technique to Measure Dust Occlusion of Solar Cells

Electroluminescence (EL) imaging is a qualitative characterization technique that is typically used to identify cracks, corrosion, and other defects in solar cells. It consists of imaging a cell under forward bias, where the solar cell emits photons due to radiative electron-hole pair recombination. Over the past few years, our team has expanded this into a quantitative technique with the help of image processing. We have primarily used this method to investigate lunar dust occlusion of solar cells and arrays. Lunar dust accumulation on solar cells is a major concern because it directly limits light accessible to the cell, decreasing power output. Many teams are working to develop dust mitigation technology to protect these arrays on the surface of the Moon, but thoroughly characterizing their efficacy is important to ensure their success prior to launch. Here, we present EL as a quantitative characterization technique to observe dust coverage on solar cells that, when coupled with IV performance measurements, can offer unique insights into how dust coverage impacts power output. Quantitative electroluminescence imaging works by running EL images through an image processing script that first grayscales the image then plots a histogram of the brightness of each pixel. On its own, it does not offer much insight into a solar cell’s performance. However, when comparing images to a baseline pristine, undamaged, or uncoated solar cell, it can quickly provide information about the impacts of surface contaminants or damage to the cell. Here, we present a case study where quantitative EL is used to measure the efficacy of dust mitigation technology for flexible solar arrays and discuss the lessons learned about dust mitigation, testing with lunar simulant, and this characterization technique.

photovoltaics↗