Intuitionistic Fuzzy C means algorithm in medical image segmentation

Autor:	Chaira T., De S., Salvetti O.
Jazyk:	angličtina
Rok vydání:	2007
Předmět:	ComputingMethodologies_PATTERNRECOGNITION Mathematics::General Mathematics Fuzzy clustering Intuitionistic fuzzy set Hesitation degree
Zdroj:	International Conference on Advances in Pattern Recognition-I CAPR 2007, Kolkata, India, 2-4 January 2007 info:cnr-pdr/source/autori:Chaira T.; De S.; Salvetti O./congresso_nome:International Conference on Advances in Pattern Recognition-I CAPR 2007/congresso_luogo:Kolkata, India/congresso_data:2-4 January 2007/anno:2007/pagina_da:/pagina_a:/intervallo_pagine
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::65630a3a85c54a678e7717031c169776 https://openportal.isti.cnr.it/doc?id=people______::65630a3a85c54a678e7717031c169776 Zobrazit plný text záznamu