Automated cervical cell image segmentation using level set based active contour model

In this paper, we propose a method based on level set active contour model to sever the nucleus and cytoplast from the cervical smear image. The region of interest (ROI) which contained a main connected cell region has been separated from the smear image after the coarse segmentation by auto dual-threshold segmentation. In the process of fine segmentation, two independent level set functions based on the Chan-Vese model with intra-region similarity and inter-region diversity have been constructed to approximate the cytoplast and nucleus contours. While there may be more than one connected cell regions in the ROI, a method of main cell body and main cell nucleus contour curve extraction has been proposed. We validate the proposed models by numerical experiment and the results show that by means of the adjustment of weight coefficient λ₁ and λ₂, most cervical cell image with weak edges can be segmented precisely.