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Clustered Cell Segmentation - Based on Iterative Voting and the Level Set Method

In this paper we deal with images in which the cells cluster together and the boundaries of the cells are ambiguous. Combining the outcome of an automatic point detector with the multiphase level set method, the centre of each cell is detected and used as the ”seed”, in other words, the initial condition for level set method. Then by choosing appropriate level set equation, the fronts of the seeds propagate and finally stop near the boundary of the cells. This method solves the cluster problem and can distinguish individual cells properly, therefore it is useful in cell segmentation. By using this method, we can count the number of the cells and calculate the area of each cell. Furthermore, this information can be used to get the histogram of the cell image.