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Analytical Cellular Pathology
Volume 18 (1999), Issue 4, Pages 211-225
http://dx.doi.org/10.1155/1999/350317

Deformable Models for Segmentation of CLSM Tissue Images and Its Application in FISH Signal Analysis

P. S. Umesh Adiga and B. B. Chaudhuri

Indian Statistical Institute, Calcutta 700035, India

Received 27 February 1998; Accepted 2 July 1999

Copyright © 1999 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In this paper we present an application of deformable models for the segmentation of volumetric tissue images. The three‐dimensional images are obtained using confocal microscope. The segmented images have been used for the quantitative analysis of the Fluorescence In Situ Hybridization (FISH) signals. An ellipsoidal surface initialized around the cell of interest acts as a deformable model. The deformable model surface voxels are subjected to various internal and external forces derived from underlying image features as well as externally imposed constraints. The deformable model converges to the optimum cell shape when the vector sum of all the forces acting on the model is zero. The result of segmentation is used to confirm the cell membership of the FISH signals and to reject all the signals that lie outside the cell nuclei. Three‐dimensional region isolation and labeling technique is used to label and count the FISH signals per cell nucleus. A simple study on the effect of different segmentation methods over a quantitative analysis of FISH signals is also presented.