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 M-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.
Karvelis
Petros S
PS
Dept. of Comput. Sci., Ioannina Univ., Ioannina, Greece. pkarvel@cs.uoi.gr
Fotiadis
Dimitrios I
DI
Georgiou
Ioannis
I
Syrrou
Marika
M
D001698:Biomedical Engineering; D002877:Chromosomes, Human / Q000145:classification* / Q000235:genetics / Q000648:ultrastructure; D016208:Databases, Factual; D005260:Female; D005456:Fluorescent Dyes; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D017404:In Situ Hybridization, Fluorescence / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male
D005456:Fluorescent Dyes