{"title":"基于对称信息的改进模糊c均值算法在脑磁共振图像分割中的应用","authors":"S. A. Jayasuriya, Alan Wee-Chung Liew","doi":"10.1109/ICICS.2013.6782786","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel modified Fuzzy C-means algorithm with symmetry information to reduce the effect of noise in brain tissue segmentation in magnetic resonance image (MRI). We integrate brain's bilateral symmetry into the conventional Fuzzy C-means (FCM) as an additional term. In experiments, some synthetic images, and both simulated and real brain images were used to investigate the robustness of the method against noise. Finally, the method was compared with the conventional FCM algorithm. Results show the viability of the approach and the preliminary investigation appears promising.","PeriodicalId":184544,"journal":{"name":"2013 9th International Conference on Information, Communications & Signal Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A modified Fuzzy C-means algorithm with symmetry information for MR brain image segmentation\",\"authors\":\"S. A. Jayasuriya, Alan Wee-Chung Liew\",\"doi\":\"10.1109/ICICS.2013.6782786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a novel modified Fuzzy C-means algorithm with symmetry information to reduce the effect of noise in brain tissue segmentation in magnetic resonance image (MRI). We integrate brain's bilateral symmetry into the conventional Fuzzy C-means (FCM) as an additional term. In experiments, some synthetic images, and both simulated and real brain images were used to investigate the robustness of the method against noise. Finally, the method was compared with the conventional FCM algorithm. Results show the viability of the approach and the preliminary investigation appears promising.\",\"PeriodicalId\":184544,\"journal\":{\"name\":\"2013 9th International Conference on Information, Communications & Signal Processing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 9th International Conference on Information, Communications & Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICS.2013.6782786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th International Conference on Information, Communications & Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICS.2013.6782786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A modified Fuzzy C-means algorithm with symmetry information for MR brain image segmentation
In this paper, we present a novel modified Fuzzy C-means algorithm with symmetry information to reduce the effect of noise in brain tissue segmentation in magnetic resonance image (MRI). We integrate brain's bilateral symmetry into the conventional Fuzzy C-means (FCM) as an additional term. In experiments, some synthetic images, and both simulated and real brain images were used to investigate the robustness of the method against noise. Finally, the method was compared with the conventional FCM algorithm. Results show the viability of the approach and the preliminary investigation appears promising.