Cell segmentation based on spatial information improved intuitionistic fcm combined with FOPSO

Fuzzy c-means clustering (FCM) algorithm has been proved to be effective for image segmentation. However, it is sensitive to the noises and initialization. FCM could not effectively segment cell images with inhomogeneity and complicate adhesives. Aimed to overcome these disadvantages, this paper proposes a cell image segmentation algorithm using spatial information improved intuitionistic fuzzy c-means clustering (SI-IFCM) combined with fractional-order velocity based particle swarm optimization (FOPSO). SI-IFCM and FOPSO will iterate alternately with different object functions to obtain the clustering result. Experimental results demonstrate the advantages of our algorithm for cell segmentation comparing with state-of-arts algorithms.