Zoom-invariant vision of figural shape: the mathematics of cores
Computer Vision and Image Understanding
Zoom-invariant vision of figural shape: effects on cores of image disturbances
Computer Vision and Image Understanding
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Variable scale statistics for cardiac segmentation and shape analysis
Variable scale statistics for cardiac segmentation and shape analysis
Medial Representations: Mathematics, Algorithms and Applications
Medial Representations: Mathematics, Algorithms and Applications
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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We have developed a method for extracting anatomical shape models from n-dimensional images using an image analysis framework we call Shells and Spheres. This framework utilizes a set of spherical operators centered at each image pixel, grown to reach, but not cross, the nearest object boundary by incorporating "shells" of pixel intensity values while analyzing intensity mean, variance, and first-order moment. Pairs of spheres on opposite sides of putative boundaries are then analyzed to determine boundary reflectance which is used to further constrain sphere size, establishing a consensus as to boundary location. The centers of a subset of spheres identified as medial (touching at least two boundaries) are connected to identify the interior of a particular anatomical structure. For the automated 3D algorithm, the only manual interaction consists of tracing a single contour on a 2D slice to optimize parameters, and identifying an initial point within the target structure.