Magnetic Resonance Image Segmentation Algorithm Based on Fuzzy Clustering

Standard fuzzy c-means algorithm only considers gray information and noise tolerance ability is poor. In order to overcome the drawbacks of traditional fuzzy c-means algorithm, a kind of improved ant colony algorithm is used to optimize fuzzy c-means. Then a new kind of image segmentation algorithm is put forward based on improved fuzzy c-means method. The experiment results show that the proposed algorithm has better noise tolerance ability than traditional fuzzy c-means method.