In this paper we first determine three phases of cell images： background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.
Cell image segmentation is an essential step in cytopathological analysis.Although their execution speed is fast,the results of cell image segmentation by conventional pixel-based,edge-based and continuity-based methods are often coarse.Fine structures in a cell image can be obtained with a method that quickly adjusts the threshold levels.However,the processing time of such a method is usually long and the final results may be sensitive to intensity differences and other factors.In this article,a new energy model is proposed that synthesizes a differential equation from the conventional and level set methods,and utilizes the nonuniformity property of cell images (e.g.cytoplasms are more uneven than the background).The feasibility and robustness of the proposed model was demonstrated by processing relatively complicated background images of both simulated and real cell images.
