Automated detection of chromosome aberration using color information

Chung Ho Chen, Yao Wang, Sanjit K. Mitra, Joe W. Gray

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)339-343
Number of pages5
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - Mar 1 1990

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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