Title: Automatic fuzzy-neural based segmentation of microscopic cell images

Authors: Sara Colantonio, Igor B. Gurevich, Ovidio Salvetti

Addresses: Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy. ' Dorodnicyn Computing Centre of the Russian Academy of Sciences 40, Vavilov Str., Moscow GSP-1 119991, Russian Federation. ' Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR), Via G. Moruzzi 1, 56124 Pisa, Italy

Abstract: In this paper, we propose a novel, completely automated method for the segmentation of lymphatic cell nuclei represented in microscopic specimen images. Actually, segmenting cell nuclei is the first, necessary step for developing an automated application for the early diagnostics of lymphatic system tumours. The proposed method follows a two-step approach to, firstly, find the nuclei and then, to refine the segmentation by means of a neural model, capable of localising the borders of each nucleus. Experimental results have shown the feasibility of the method.

Keywords: microscopic cell images; colour image segmentation; fuzzy clustering; artificial neural networks; ANNs; lymphatic cell nuclei; lymphatic tumours.

DOI: 10.1504/IJSISE.2008.017769

International Journal of Signal and Imaging Systems Engineering, 2008 Vol.1 No.1, pp.18 - 24

Published online: 12 Apr 2008 *

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