Medical image segmentation demands an efficient and robust segmentation
algorithm against noise. The conventional fuzzy c-means algorithm is an
efficient clustering algorithm that is used in medical image segmentation. But
FCM is highly vulnerable to noise since it uses only intensity values for
clustering the images. This paper aims to develop a novel and efficient fuzzy
spatial c-means clustering algorithm which is robust to noise. The proposed
clustering algorithm uses fuzzy spatial information to calculate membership
value. The input image is clustered using proposed ISFCM algorithm.