Title: Parallel microscopic cell image segmentation and multiple fusions

Authors: Eric Dahai Cheng, Subhash Challa, Rajib Chakravorty

Addresses: Victoria Research Laboratory, National Information and Communication Technologies, Australia (NICTA), Department of Electrical and Electronic Engineering, University of Melbourne, Level 2, Building 193, Victoria 3010, Australia. ' Victoria Research Laboratory, National Information and Communication Technologies, Australia (NICTA), Department of Electrical and Electronic Engineering, University of Melbourne, Level 2, Building 193, Victoria 3010, Australia. ' Victoria Research Laboratory, National Information and Communication Technologies, Australia (NICTA), Department of Electrical and Electronic Engineering, University of Melbourne, Level 2, Building 193, Victoria 3010, Australia

Abstract: Segmenting cells reliably and correctly in a microscopic image is a pretty difficult task. We have developed a set of cell segmentation algorithms in parallel and a decision fusion algorithm to make the detection more robust. The distance and watershed transforms have also been used to separate the connected cells. Experimental results have proved that these algorithms are pretty robust to variable microscopy image data, and variable cell densities, and with the proposed fusion and false removal algorithms, the cell detection rate has increased significantly to above 97% with the false detection rate about 7%.

Keywords: cell segmentation; microscopy images; decision fusion; edge detection; distance transform; watershed transform; image segmentation; cell images; imaging systems; cell detection rate.

DOI: 10.1504/IJSISE.2011.041603

International Journal of Signal and Imaging Systems Engineering, 2011 Vol.4 No.2, pp.96 - 114

Received: 06 May 2010
Accepted: 28 Feb 2011
Published online: 13 Mar 2015 *

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