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Proceedings Paper

Automated Detection Of Chromosome Aberration Using Color Information
Author(s): Chung-Ho Chen; Yao Wang; Sanjit K. Mitra; Joe W. Gray
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Paper Abstract

An automated scheme for the detection of chromosome aberrations in color chromosome images is described. The analysis scheme consists of three steps: segmentation, clustering, and scene understanding. First the target chromosome pixels are segmented via thresholding based on a chosen color measure. Then a clustering technique is applied to cluster the target chromosome pixels into groups in such a way that every group corresponds to a unique target chromosome domain. Finally, human chromosome aberrations are detected by calculating the geometrical properties of each detected group and counting the number of the confirmed target chromosomes. Experiments have been carried out to compare the effectiveness of several color measures for the purpose of the segmentation. Moreover, a novel self-tuning thresholding method has been developed to improve the robustness of segmentation. With this method, chromosome aberrations can be idetified even under different background brightness and chrominance distribution.

Paper Details

Date Published: 1 March 1990
PDF: 5 pages
Proc. SPIE 1192, Intelligent Robots and Computer Vision VIII: Algorithms and Techniques, (1 March 1990); doi: 10.1117/12.969746
Show Author Affiliations
Chung-Ho Chen, University of California, Santa Barbara (United States)
Yao Wang, University of California, Santa Barbara (United States)
Sanjit K. Mitra, University of California, Santa Barbara (United States)
Joe W. Gray, University of California (United States)

Published in SPIE Proceedings Vol. 1192:
Intelligent Robots and Computer Vision VIII: Algorithms and Techniques
David P. Casasent, Editor(s)

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