Title: A fuzzy segmentation method for Computed Tomography images

Authors: Martin Tabakov

Addresses: Institute of Applied Informatics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

Abstract: 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.

Keywords: fuzzy clustering; medical imaging; computed tomography; CT; fuzzy segmentation; image segmentation; fuzzy similarity relations; data partitional clustering.

DOI: 10.1504/IJIIDS.2007.013286

International Journal of Intelligent Information and Database Systems, 2007 Vol.1 No.1, pp.79 - 89

Published online: 19 Apr 2007 *

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