A Fuzzy Clustering Technique for Medical Image Segmentation

Abstract

The main objective of medical image segmentation is to extract and characterise anatomical structures with respect to some input features or expert knowledge. This paper describes a way of medical image segmentation using an appropriately defined fuzzy clustering method based on a fuzzy similarity relation. The considered relation is defined in terms of the Euclidean metric. A fuzzy similarity relation-based image segmentation algorithm is also introduced. To illustrate the obtained segmentation process some examples of computed tomography imaging are considered. Some results, using the classical fuzzy c-means clustering algorithm are also presented, for a comparison purpose