A watershed based segmentation method for multispectral chromosome images classification

M-FISH (Multicolor Fluorescence In Situ Hybridization) is a recently developed cytogenetic technique for cancer diagnosis and research on genetic disorders which uses 5 fluors to label uniquely each chromosome and a fluorescent DNA stain. In this paper, an automated method for chromosome classification in M-FISH images is presented. The chromosome image is initially decomposed into a set of primitive homogeneous regions through the morphological watershed transform applied to the image intensity gradient magnitude. Each segmented area is then classified using a Bayes classifier. We have evaluated our methodology on a commercial available NI-FISH database. The classifier was trained and tested on non-overlapping chromosome images and an overall accuracy of 89% is achieved. By introducing feature averaging on watershed basins, the proposed technique achieves substantially better results than previous methods at a lower computational cost.