Browsing by Author "Beets, Matthew Paul"

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    Distortion Correction in LODOX StatScan X-Ray Images
    (2007) Beets, Matthew Paul
    This thesis presents a background and description of a method of distortion correction in x-ray images produced by the LODOX StatScan machine. The distortion correction of an object's x-ray image is of particular interest in the medical field, particularly for prosthetics, implants, and orthopedic work. It is useful to be able to take accurate measurements directly from x-ray images and that these images should be obtained with a minimum of patient discomfort and exposure to radiation. Current x-ray images contain a non-linear distortion that must be corrected for by hand. This distortion is a result of the imaging process: X-rays from a point source spread out before being captured by a detection device such as a photographic plate or an electronic CCD sensor. Because of this, objects closer to the center of the detector suffer less distortion than those at the edges and makes the correction process a non-trivial task traditionally requiring multiple scans to be taken and stitched together manually to minimize the distortion. The method of distortion correction presented here is a novel approach to the problem using the LODOX StatScan machine. It uses multiple scans from the StatScan Machine to create a single completely distortion free image entirely automatically. This is a software based correction method. It takes multiple fan beam x-ray projections and uses them to create a single virtual parallel beam x-ray image suitable for making accurate measurements with.
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    Open Access
    Distortion correction in LODOX Statscan X-ray images
    (2007) Beets, Matthew Paul
    Word Processed copy. Includes bibliographical references (leaves 55-56).