{"title":"基于图像分解的超声图像模糊聚类分割","authors":"Yan Xu","doi":"10.1109/ISIEA.2009.5356492","DOIUrl":null,"url":null,"abstract":"Ultrasound image segmentation is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, we propose a segmentation scheme using fuzzy c-means (FCM) clustering incorporating spatial information based on image decomposition. First, an ultrasound image is decomposed into a sum of two functions, u+v, where u denotes the image intensity while v refers to the texture. And then, a spatial FCM clustering method is applied on the image intensity component for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than other preprocessing or segmentation methods.","PeriodicalId":6447,"journal":{"name":"2009 IEEE Symposium on Industrial Electronics & Applications","volume":"1 1","pages":"6-10"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Image decomposition based ultrasound image segmentation by using fuzzy clustering\",\"authors\":\"Yan Xu\",\"doi\":\"10.1109/ISIEA.2009.5356492\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ultrasound image segmentation is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, we propose a segmentation scheme using fuzzy c-means (FCM) clustering incorporating spatial information based on image decomposition. First, an ultrasound image is decomposed into a sum of two functions, u+v, where u denotes the image intensity while v refers to the texture. And then, a spatial FCM clustering method is applied on the image intensity component for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than other preprocessing or segmentation methods.\",\"PeriodicalId\":6447,\"journal\":{\"name\":\"2009 IEEE Symposium on Industrial Electronics & Applications\",\"volume\":\"1 1\",\"pages\":\"6-10\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Symposium on Industrial Electronics & Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIEA.2009.5356492\",\"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 IEEE Symposium on Industrial Electronics & Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIEA.2009.5356492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image decomposition based ultrasound image segmentation by using fuzzy clustering
Ultrasound image segmentation is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, we propose a segmentation scheme using fuzzy c-means (FCM) clustering incorporating spatial information based on image decomposition. First, an ultrasound image is decomposed into a sum of two functions, u+v, where u denotes the image intensity while v refers to the texture. And then, a spatial FCM clustering method is applied on the image intensity component for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than other preprocessing or segmentation methods.