A fuzzy segmentation method for Computed Tomography images. (20th April 2007)

• Record Type: Journal Article
• Authors: Tabakov, Martin
• Is Part Of: International journal of intelligent information and database systems. Volume 1:Number 1(2007)
• Page Start: 79
• Page End: 89
• Publication Date: 2007-04-20
• Subjects: fuzzy clustering -- medical imaging -- computed tomography -- CT -- fuzzy segmentation -- image segmentation -- fuzzy similarity relations -- data partitional clustering; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

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.