Abstract: Based on the analysis of cell contour structure, a sparse contour point model, which can describe the characteristics of the cell contour, is proposed in this paper. In the sparse contour point model, cell contour is divided into 2 parts, namely light contour and dark contour, respectively; and then the cell contour is approximately described as a set of sparse contour points. Based on this model, the color and grayscale image segmentation techniques are combined to locate the basic contour, which lies between the cell and the background. Then, a circular dynamic contour searching method is proposed to search for the dark contour that lies in the overlapping cell region along the basic contour. Contour points located by the searching method are arranged to construct the initial contour of the gradient vector flow (GVF) Snake model. Then the GVF Snake model is performed to obtain the final accurate segmentation result of the cell image. Various cell images containing single cell, overlapping cells of similar colors and overlapping cells of different colors have been tested to show the validity and effectiveness of the proposed method. The proposed techniques are useful for the development of automatic cervical cell image analysis systems.

Key words: medical image processing, overlapping cell images, color image segmentation, sparse contour point model, gradient vector flow (GVF) Snake model