This paper presents a novel intuitionistic fuzzy C means clustering method using intuitionistic fuzzy set theory. This clustering method has also been used for identification of mammogram cysts. In this method, the hesitation degree has been taken into account along with the membership degree, where the cluster centers may converge to a desirable location than the cluster centers obtained by fuzzy C means algorithm. Experimental results on mammogram images show the effectiveness of the proposed method in contrast to existing fuzzy C means algorithms.

Intuitionistic Fuzzy C means algorithm in medical image segmentation

Salvetti O
2007

Abstract

This paper presents a novel intuitionistic fuzzy C means clustering method using intuitionistic fuzzy set theory. This clustering method has also been used for identification of mammogram cysts. In this method, the hesitation degree has been taken into account along with the membership degree, where the cluster centers may converge to a desirable location than the cluster centers obtained by fuzzy C means algorithm. Experimental results on mammogram images show the effectiveness of the proposed method in contrast to existing fuzzy C means algorithms.
2007
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Intuitionistic fuzzy set
Fuzzy clustering
Hesitation degree
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/102602
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