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

Persistent Link:
http://hdl.handle.net/10150/277091
Title:
Applying multiresolution and graph-searching techniques for boundary detection in biomedical images
Author:
Munechika, Stacy Mark, 1961-
Issue Date:
1989
Publisher:
The University of Arizona.
Rights:
Copyright © 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.
Abstract:
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.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Image processing -- Digital techniques.; Imaging systems -- Image quality.; Imaging systems in medicine.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Optical Science
Degree Grantor:
University of Arizona
Advisor:
Barrett, Harrison H.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleApplying multiresolution and graph-searching techniques for boundary detection in biomedical imagesen_US
dc.creatorMunechika, Stacy Mark, 1961-en_US
dc.contributor.authorMunechika, Stacy Mark, 1961-en_US
dc.date.issued1989en_US
dc.publisherThe University of Arizona.en_US
dc.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.en_US
dc.description.abstractAn 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.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectImage processing -- Digital techniques.en_US
dc.subjectImaging systems -- Image quality.en_US
dc.subjectImaging systems in medicine.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineOptical Scienceen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorBarrett, Harrison H.en_US
dc.identifier.proquest1337975en_US
dc.identifier.oclc22918821en_US
dc.identifier.bibrecord.b17534616en_US
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