N. Harchaoui, S. Bara, M. A. Kerroum, A. Hammouch, M. Ouadou, D. Aboutajdine
{"title":"An improved fuzzy clustering approach using possibilist c-means algorithm: Application to medical image MRI","authors":"N. Harchaoui, S. Bara, M. A. Kerroum, A. Hammouch, M. Ouadou, D. Aboutajdine","doi":"10.1109/CIST.2012.6388074","DOIUrl":null,"url":null,"abstract":"Currently, the MRI brain image processing is a vast area of research, several methods and approaches have been used to segment these images (thresholding, region, contour, clustering). In this work, we propose a novel segmentation approach, which is based on fuzzy c-means clustering and using possibilist c-means approach. To validate our approach, we have tested successfully on several datasets of real images MRI. Thus, to show the performance of our method, we compared our results with different segmentation algorithms: k-means, fuzzy c-means, and possibilist c-means.","PeriodicalId":120664,"journal":{"name":"2012 Colloquium in Information Science and Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Colloquium in Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIST.2012.6388074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Currently, the MRI brain image processing is a vast area of research, several methods and approaches have been used to segment these images (thresholding, region, contour, clustering). In this work, we propose a novel segmentation approach, which is based on fuzzy c-means clustering and using possibilist c-means approach. To validate our approach, we have tested successfully on several datasets of real images MRI. Thus, to show the performance of our method, we compared our results with different segmentation algorithms: k-means, fuzzy c-means, and possibilist c-means.