Biomedical image processing II: 25-27 February 1991, San Jose, California
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SEGMENTATION AND FEATURE DETECTION IN BIOMEDICAL IMAGE
ANALYSIS CLASSIFICATION AND RECOGNITION OF BIOMEDICAL
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applied approach approximation arcs autoradiograph bifurcation points Biomedical Image blood vessels boundary capillary cell classification clustering algorithm components computed Computer Vision confocal confocal microscope contours curvature defined deformation detector developed dimensional E-filters edge detection ellipsoid enhancement equation equivalent tree error estimate extraction FMH filters Fourier frames function Gaussian Gaussian curvature global motion graph Q gray level hierarchical histogram equalization homogeneous homothetic homothetic motion IEEE Trans image analysis image processing image segmentation intensity interpolation iterations left ventricle lesion lung mathematical morphology maximum flow median filter Medical Imaging method microscope minimum cut morphological noise obtained operator optical optimal original image output pair of vertices parameters pattern recognition performance phantom feature pixels point correspondences problem projection regions represents sample sequence shape shows somatotyping spatial stretching structure subgraphs surface techniques texture three-dimensional threshold tissue trajectories transform two-dimensional vertex visual voxels window