{"title":"基于模糊c均值和附加形状元素的脑MR图像分割","authors":"O. Ozyurt, A. Dinçer, C. Ozturk","doi":"10.1109/BIYOMUT.2009.5130271","DOIUrl":null,"url":null,"abstract":"Using the intensity of the element in interest, standard FCM generates the membership values to all classes. When used for segmentation of images, this method is not capable of correcting the effects of noise. To overcome that problem, we propose a modification on the standard method. The voxels in the neighborhood are taken into account, forming the shape elements in additon to the intensity of the voxel in interest. The resulting input vector is used with FCM. The proposed method was tested with MR brain image with and without added syntetic noise.","PeriodicalId":119026,"journal":{"name":"2009 14th National Biomedical Engineering Meeting","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Brain MR image segmentation with fuzzy C-means and using additional shape elements\",\"authors\":\"O. Ozyurt, A. Dinçer, C. Ozturk\",\"doi\":\"10.1109/BIYOMUT.2009.5130271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Using the intensity of the element in interest, standard FCM generates the membership values to all classes. When used for segmentation of images, this method is not capable of correcting the effects of noise. To overcome that problem, we propose a modification on the standard method. The voxels in the neighborhood are taken into account, forming the shape elements in additon to the intensity of the voxel in interest. The resulting input vector is used with FCM. The proposed method was tested with MR brain image with and without added syntetic noise.\",\"PeriodicalId\":119026,\"journal\":{\"name\":\"2009 14th National Biomedical Engineering Meeting\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 14th National Biomedical Engineering Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIYOMUT.2009.5130271\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 14th National Biomedical Engineering Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIYOMUT.2009.5130271","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Brain MR image segmentation with fuzzy C-means and using additional shape elements
Using the intensity of the element in interest, standard FCM generates the membership values to all classes. When used for segmentation of images, this method is not capable of correcting the effects of noise. To overcome that problem, we propose a modification on the standard method. The voxels in the neighborhood are taken into account, forming the shape elements in additon to the intensity of the voxel in interest. The resulting input vector is used with FCM. The proposed method was tested with MR brain image with and without added syntetic noise.