1. A medical image segmentation method, which comprises the following processing steps: step 1 , initialize the number of clusters and determine the initial values of cluster centroids; step 2 , calculate a Pseudo-Hausdorff distance between each cluster centroid and each pixel in an image; step 3 , calculate a membership function of each pixel being a member of a cluster based on the Pseudo-Hausdorff distance and an Euclid distance between each cluster centroid and said each pixel; step 4 , calculate an objective function, cluster the pixels of the image based on the membership function, and update the values of the cluster centroids; and repeat step 2 - 4 , until a difference between the objective function values of two consecutive iterations is less than a threshold value, and then the membership function from the last iteration is a final segmentation.