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Applying multiresolution and graph-searching techniques for boundary detection in biomedical images

An edge-based segmentation scheme (i.e. boundary detector) for nuclear medicine images has been developed and consists of a multiresolutional Gaussian-based edge detector working in conjunction with a modified version of Nilsson's A* graph-search algorithm. A multiresolution technique of analyzing the edge-signature plot (edge gradient versus resolution scale) allows the edge detector to match an appropriately sized edge operator to the edge structure in order to measure the full extent of the edge and thus gain the best compromise between noise suppression and edge localization. The graph-search algorithm uses the output from the multiresolution edge detector as the primary component in a cost function which is then minimized to obtain the boundary path. The cost function can be adapted to include global information such as boundary curvature, shape, and similarity to prototype to help guide the boundary detection process in the absence of good edge information.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/277091
Date January 1989
CreatorsMunechika, Stacy Mark, 1961-
ContributorsBarrett, Harrison H.
PublisherThe University of Arizona.
Source SetsUniversity of Arizona
Languageen_US
Detected LanguageEnglish
Typetext, Thesis-Reproduction (electronic)
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.

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