2001 IEEE Conf. on Image Processing, Oct. 7-10, 2001, vol. II, pp. 865-868.

Minimum Entropy Segmentation Applied to Multi-Spectral Chromosome Images

Wade Schwartzkopf, Brian L. Evans, and Alan C. Bovik

Department of Electrical and Computer Engineering, Engineering Science Building, The University of Texas at Austin, Austin, TX 78712-1084
bevans@ece.utexas.edu - bovik@ece.utexas.edu

Paper - Software - MFISH Database

In the early 1990s, the state-of-the-art in commercial chromosome image acquisition was grayscale. Automated chromosome classification was based on the grayscale image and boundary information obtained during segmentation. Multi-spectral image acquisition was developed in 1990 and commercialized in the mid-1990s. One acquisition method, multiplex fluorescence in-situ hybridization (M-FISH), uses five color dyes. We propose a segmentation algorithm for M-FISH images that minimizes the entropy of classified pixels within possible chromosomes. This method is shown to correctly decompose even difficult clusters of touching and overlapping chromosomes. Finally, an example image is given to illustrate the algorithm.

COPYRIGHT NOTICE: All the documents on this server have been submitted by their authors to scholarly journals or conferences as indicated, for the purpose of non-commercial dissemination of scientific work. The manuscripts are put on-line to facilitate this purpose. These manuscripts are copyrighted by the authors or the journals in which they were published. You may copy a manuscript for scholarly, non-commercial purposes, such as research or instruction, provided that you agree to respect these copyrights.

Last Updated 05/27/05.