An image segmentation method for immune cell image analysis

An effective immune cell image segmentation algorithm based on mathematical morphology is presented in this paper. In order to get better segmentation results in addition to the morphology based watershed growth algorithm the histogram potential function is involved, which means, the image spectral information is combined with spacial information. How to get the exact segmentation result is a major issue for immune cell image analysis. Obtaining an effective and credible marker is a crucial step of watershed segmentation. By involving the histogram potential function, the markers suitable for watershed segmentation can be clearly improved and the segmentation result is quite consistent with human vision and also the segmentation speed and repeatability are quite acceptable.