Parallel microscopic cell image segmentation and multiple fusions

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%.