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A Differential Evolutionary Algorithm for Image Segmentation of White Blood Cells in Acute Lymphoblastic Leukaemia Images

White blood cells play an important role by enabling a protection against any foreign substances or pathogens that enter inside the human immune system. The detection of the white blood cells is done by using the image processing techniques. The lymphoblast images are a slight modification of the white blood cells. It has nucleus, which is often large and lobed, and it helps to distinguish it with the other blood cells. In this paper, the differential evolution algorithm is used for the segmentation of white blood cells from the acute leukemic images. Differential evolution algorithm is an iterative process through which the solution gets improvised as the algorithm proceeds with less number of assumptions. The experimental results showed that DE was able to successfully segment the white blood cells.