Abstract: The single-cell analysis, achieved on the microfluidic chip, is able to grasp more accurate and comprehensive cells information, has important scientific significance for the prevention and early disease diagnosis. Based on the theories that the deformability of the early cancer cells are different from normal cells when they go around a curve in the microfluidic chip. So a new cell segmentation algorithm, which fuses classical grabcut algorithm with snake algorithm, is proposed to accurately extract a single cell outline, and achieve the deformation analysis of a single cell. Firstly, the morphological operators are used to eliminate small bright spot noise. Secondly, canny and snake algorithm are utilized to get the position of one cell, which can be regarded as the initialization of the grabcut algorithm. Finally, accurate cell contour are extracted by grabcut algorithm. Experimental results show that the proposed algorithm combines the advantages of snake algorithm and grabcut algorithm. In the absence of human interaction, the average correct segmentation rate is up to 93.7%, can meet the medical requirements of single cell analysis.

Key words: unicellular, contour localization and extraction, Grabcut algorithm, Snake algorithm, fuse