Brain image segmentation base on adapted Fuzzy Clustering method

Automated segmentation of images has been considered an important intermediate processing task to extract semantic meaning from pixels. In general, the fuzzy c-means method (FCM) is highly effective for image segmentation. But for the conventional FCM image segmentation algorithm, cluster assignment is based solely on the distribution of pixel attributes in the feature space, and the spatial distribution of pixels in an image is not taken into consideration. In this paper, we present a novel FCM image segmentation scheme by utilizing global information. Experimental results showed the proposed method achieves competitive segmentation results compared to other FCM-based methods.