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  • 2005-2009  (2)
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  • 1
    Publication Date: 2019-07-13
    Description: A priority of NASA is to identify and study possible risks to astronauts health during prolonged space missions [l]. The goal is to develop a procedure for a preflight evaluation of the cardiovascular system of an astronaut and to forecast how it will be affected during the mission. To predict these changes, a computational cardiovascular model must be constructed. Although physiology data can be used to make a general model, a more desirable subject-specific model requires anatomical, functional, and flow data from the specific astronaut. MRI has the unique advantage of providing images with all of the above information, including three-directional velocity data which can be used as boundary conditions in a computational fluid dynamics (CFD) program [2,3]. MRI-based CFD is very promising for reproduction of the flow patterns of a specific subject and prediction of changes in the absence of gravity. The aim of this study was to test the feasibility of this approach by reconstructing the geometry of MRI-scanned arterial models and reproducing the MRI-measured velocities using CFD simulations on these geometries.
    Keywords: Life Sciences (General)
    Type: 13th Annual Meeting and Exposition; May 07, 2005 - May 13, 2005; Southbeach, FL; United States
    Format: text
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  • 2
    Publication Date: 2019-07-19
    Description: We report on the results of a comparison study of different techniques for compressing FITS images that have floating-point (real*4) pixel values. Standard file compression methods like GZIP are generally ineffective in this case (with compression ratios only in the range 1.2 - 1.6), so instead we use a technique of converting the floating-point values into quantized scaled integers which are compressed using the Rice algorithm. The compressed data stream is stored in FITS format using the tiled-image compression convention. This is technically a lossy compression method, since the pixel values are not exactly reproduced, however all the significant photometric and astrometric information content of the image can be preserved while still achieving file compression ratios in the range of 4 to 8. We also show that introducing dithering, or randomization, when assigning the quantized pixel-values can significantly improve the photometric and astrometric precision in the stellar images in the compressed file without adding additional noise. We quantify our results by comparing the stellar magnitudes and positions as measured in the original uncompressed image to those derived from the same image after applying successively greater amounts of compression.
    Keywords: Astronomy
    Type: Astronomical Data Analysis Software and Systems XIX (ADASS 2009); Oct 04, 2009 - Oct 08, 2009; Sapporo; Japan
    Format: text
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