Evaluation of diagnostic clues in histopathology through image processing techniques

Persistent Link:
http://hdl.handle.net/10150/277296
Title:
Evaluation of diagnostic clues in histopathology through image processing techniques
Author:
Haddad, Jane Wurster, 1965-
Issue Date:
1990
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:
The primary method for the diagnostic interpretation of histopathologic sections is visual analysis. However, in a small, but significant percentage of cases, histopathologists do not come to a consensus. Therefore, due to the importance of early and accurate detection of tissue changes indicative of pathology, quantitative image analysis techniques have been applied to this problem. The accurate segmentation of image structures such as cells and glands in histopathological sections, as with all "natural scenes", proves challenging. This has led to the development of an additional segmentation technique, the heuristic gradient search. Following the successful segmentation and labeling of scene objects, algorithms evaluating diagnostic clues as to the shape, size and distribution of image components were developed in order to form an overall diagnosis. A description of these diagnostic clues and the image processing techniques residing in the computer vision system used to evaluate them are presented.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Engineering, Biomedical.; Engineering, Electronics and Electrical.; Health Sciences, Pathology.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Schowengerdt, R. A.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleEvaluation of diagnostic clues in histopathology through image processing techniquesen_US
dc.creatorHaddad, Jane Wurster, 1965-en_US
dc.contributor.authorHaddad, Jane Wurster, 1965-en_US
dc.date.issued1990en_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.abstractThe primary method for the diagnostic interpretation of histopathologic sections is visual analysis. However, in a small, but significant percentage of cases, histopathologists do not come to a consensus. Therefore, due to the importance of early and accurate detection of tissue changes indicative of pathology, quantitative image analysis techniques have been applied to this problem. The accurate segmentation of image structures such as cells and glands in histopathological sections, as with all "natural scenes", proves challenging. This has led to the development of an additional segmentation technique, the heuristic gradient search. Following the successful segmentation and labeling of scene objects, algorithms evaluating diagnostic clues as to the shape, size and distribution of image components were developed in order to form an overall diagnosis. A description of these diagnostic clues and the image processing techniques residing in the computer vision system used to evaluate them are presented.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectEngineering, Biomedical.en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectHealth Sciences, Pathology.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSchowengerdt, R. A.en_US
dc.identifier.proquest1340286en_US
dc.identifier.bibrecord.b26251875en_US
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