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Proceedings Paper

Principle of least commitment in the analysis of chromosome images
Author(s): James M. Keller; Paul D. Gader; Charles W. Caldwell
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Paper Abstract

The automation of chromosome identification and visualization for a complete cell (karyotyping) has been the subject of considerable research. While rather high classification rates are possible on individual chromosomes, the cell level classification rates are still quite low. We describe a system which uses partial confidence values generated by neural and fuzzy classifiers with optimization to increase the cell level recognition rates. This is consistent with Marr's Principle of Least Commitment for the design of intelligent computer vision algorithms.

Paper Details

Date Published: 13 June 1995
PDF: 9 pages
Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); doi: 10.1117/12.211800
Show Author Affiliations
James M. Keller, Univ. of Missouri/Columbia (United States)
Paul D. Gader, Univ. of Missouri/Columbia (United States)
Charles W. Caldwell, Ellis Fischell Cancer Ctr. (United States)

Published in SPIE Proceedings Vol. 2493:
Applications of Fuzzy Logic Technology II
Bruno Bosacchi; James C. Bezdek, Editor(s)

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