{"title":"用多光谱融合方法分割磁共振图像:研究与评价","authors":"Lamiche Chaabane, Moussaoui Abdelouahab","doi":"10.1109/ICEELI.2012.6360567","DOIUrl":null,"url":null,"abstract":"The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some possibility theory concepts. Information provided by different sources of MR images is extracted and modeled separately in each one using MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm, extracted data obtained are combined with an operator which can managing the uncertainty and ambiguity in the images and the final segmented image is constructed in decision step. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR Images.","PeriodicalId":398065,"journal":{"name":"International Conference on Education and e-Learning Innovations","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Segmentation of MR images using multispectral fusion approach : A study and an evaluation\",\"authors\":\"Lamiche Chaabane, Moussaoui Abdelouahab\",\"doi\":\"10.1109/ICEELI.2012.6360567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some possibility theory concepts. Information provided by different sources of MR images is extracted and modeled separately in each one using MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm, extracted data obtained are combined with an operator which can managing the uncertainty and ambiguity in the images and the final segmented image is constructed in decision step. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR Images.\",\"PeriodicalId\":398065,\"journal\":{\"name\":\"International Conference on Education and e-Learning Innovations\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Education and e-Learning Innovations\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEELI.2012.6360567\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Education and e-Learning Innovations","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEELI.2012.6360567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation of MR images using multispectral fusion approach : A study and an evaluation
The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some possibility theory concepts. Information provided by different sources of MR images is extracted and modeled separately in each one using MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm, extracted data obtained are combined with an operator which can managing the uncertainty and ambiguity in the images and the final segmented image is constructed in decision step. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR Images.