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Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering : Application to Medical Image MRI
Joint Authors
Ouadou, Mohamed
Hammouch, Ahmed
Ait Kerroum, Mounir
Aboutajdine, Driss
El Harchaoui, Nour-Eddine
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-12-29
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The analysis and processing of large data are a challenge for researchers.
Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories.
In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome the problems of uncertain data in complex systems.
We used the membership function of fuzzy c-means (FCM) to initialize the parameters of possibilistic c-means (PCM), in order to solve the problem of coinciding clusters that are generated by PCM and also overcome the weakness of FCM to noise.
To validate our approach, we used several validity indexes and we compared them with other conventional classification algorithms: fuzzy c-means, possibilistic c-means, and possibilistic fuzzy c-means.
The experiments were realized on different synthetics data sets and real brain MR images.
American Psychological Association (APA)
El Harchaoui, Nour-Eddine& Ait Kerroum, Mounir& Hammouch, Ahmed& Ouadou, Mohamed& Aboutajdine, Driss. 2013. Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering : Application to Medical Image MRI. Computational Intelligence and Neuroscience،Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-472038
Modern Language Association (MLA)
El Harchaoui, Nour-Eddine…[et al.]. Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering : Application to Medical Image MRI. Computational Intelligence and Neuroscience No. 2013 (2013), pp.1-12.
https://search.emarefa.net/detail/BIM-472038
American Medical Association (AMA)
El Harchaoui, Nour-Eddine& Ait Kerroum, Mounir& Hammouch, Ahmed& Ouadou, Mohamed& Aboutajdine, Driss. Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering : Application to Medical Image MRI. Computational Intelligence and Neuroscience. 2013. Vol. 2013, no. 2013, pp.1-12.
https://search.emarefa.net/detail/BIM-472038
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-472038