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A fuzzy segmentation method for Computed Tomography images

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 Minkowski metric. A fuzzy similarity relation based image segmentation algorithm is also introduced. Next, a method for formal comparison between different data clusterings, based on a new distance model is proposed. To illustrate the obtained segmentation process some examples of computed tomography imaging are considered. For comparison purpose and also to access the clustering quality, corresponding results with using the classical fuzzy c means algorithm are also presented.