Clustering, an unsupervised learning technique plays a vital role in Medical Image Segmentation. Our research is segmenting liver images with tumour. Clustering algorithms are used to segment the liver tumor images. Cluster Analysis is an important concept of analyzing different liver tumor images by grouping data objects which are related to each other and unrelated to the data objects of another group. There are different types of clustering algorithms available to segment Liver. In this paper we focus on two important clustering algorithms namely Fuzzy C-Means(FCM) and Spacial Fuzzy C-Means(SFCM). A comparative study is done which brings down curtain that SFCM yields better detected tumor image with time complexity compared to FCM.

Keywords- Image Segmentation,Liver Image,Clustering,Time complexity,Fuzzy C-means,Spacial Fuzzy C-means,Unsupervised learning;