title: Segmentation and counting of FISH signals in confocal microscopy images.
abstract: In this paper we have presented a semi-automatic method for segmenting and counting the Fluorescence In Situ Hybridization (FISH) signals per cell nucleus in a 3D tissue image. The number of FISH signals indicate the gain (trisomy) or loss (monosomy) of certain base-sequences in deoxyribonucleic acid (DNA). The quantitative evaluation of the loss or gain in DNA is necessary in qualitative diagnostic molecular pathology. Multispectral volumetric images are obtained using the Confocal Microscope. Each consists of a red channel depicting the 3D morphology of the tissue and green channel containing the FISH signals. The red channel tissue image is segmented first to determine the membership of the FISH signal to a particular nuclei. Various segmentation methods starting from simple local thresholding to volume growing and active volumes are used for segmentation. A brief comparative study of the visual signal count by pathologist and our automatic count is also presented.
authors.affiliation: Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Calcutta, India.
authors.forename: P S
authors.initials: PS
authors.lastname: Umest Adiga
authors.forename: B B
authors.initials: BB
authors.lastname: Chaudhuri
mesh_terms: D002467:Cell Nucleus / Q000648:ultrastructure; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D017404:In Situ Hybridization, Fluorescence / Q000379:methods*; D008297:Male; D018613:Microscopy, Confocal; D009369:Neoplasms / Q000648:ultrastructure; D011471:Prostatic Neoplasms / Q000648:ultrastructure