Abstract
Image analysis techniques developed for cytology automation are shown to be applicable or adaptable to the analysis of fixed tissue sections in some relatively simple cases. More sophisticated techniques, developed as extensions of the basic methods, are suggested for more complicated cases. Techniques highlighted include: isodensity contour tracing, geometrical boundary repair, heuristic search, regional pre-processing, Hough transforms, and general parallel edge finding algorithms. Applications include: leukocyte analysis (in blood, marrow, and tissue), morphometric analysis of bone tissue, morphometry of muscle and nerve fibers, and the grading of non-Hodgkins lymphomas and of intraductal breast lesions.
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