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Proceedings Paper

Evaluation of prostate tumor grades by content-based image retrieval
Author(s): Arthur W. Wetzel; R. Crowley; Sujin Kim; R. Dawson; Lei Zheng; Y. M. Joo; Yukako Yagi; John Gilbertson; C. Gadd; D. W. Deerfield; Michael J. Becich
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Paper Abstract

As part of collaboration between the Pittsburgh Supercomputing Center and the University of Pittsburgh Medical Center we are developing methods for content based image retrieval to assist pathology diagnosis. We have been using Gleason grading of prostate tumor samples as an initial domain for evaluating the effectiveness of the method for specific tasks. In this application, the system does not attempt to directly reproduce pathologists' visual analysis. Rather, it relies on the comparison of image features from a sample image to key the retrieval of similar but previously graded images from a database. Appropriate features should be highly selective to architecture differences of the Gleason system so the grades of the retrieved images can be applied to the unknown sample. We have been investigating the usefulness of computational geometry structures, such as spanning trees, as components of feature sets providing accurate retrieval of matching grades.

Paper Details

Date Published: 29 January 1999
PDF: 9 pages
Proc. SPIE 3584, 27th AIPR Workshop: Advances in Computer-Assisted Recognition, (29 January 1999); doi: 10.1117/12.339826
Show Author Affiliations
Arthur W. Wetzel, Pittsburgh Supercomputing Ctr. (United States)
R. Crowley, Univ. of Pittsburgh (United States)
Sujin Kim, Univ. of Pittsburgh (United States)
R. Dawson, Univ. of Pittsburgh (United States)
Lei Zheng, Univ. of Pittsburgh (United States)
Y. M. Joo, Univ. of Pittsburgh (United States)
Yukako Yagi, Univ. of Pittsburgh (United States)
John Gilbertson, Univ. of Pittsburgh (United States)
C. Gadd, Univ. of Pittsburgh (United States)
D. W. Deerfield, Pittsburgh Supercomputing Ctr. (United States)
Michael J. Becich, Univ. of Pittsburgh (United States)

Published in SPIE Proceedings Vol. 3584:
27th AIPR Workshop: Advances in Computer-Assisted Recognition
Robert J. Mericsko, Editor(s)

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