{"title":"基于改进FCM和数学形态学的眼底病变识别","authors":"Li Hua, Hui Zhang","doi":"10.1109/ICSESS.2012.6269420","DOIUrl":null,"url":null,"abstract":"Fundus lesion identification is a worldwide problem. The traditional method has greater impact on human factors, subjective and cumbersome makes Fundus lesion identification Accuracy, objectivity and practicality not be guaranteed. To solve the above problem, an improved FCM algorithm for segmentation of Fundus lesion, the improved FCM algorithm clustering image segmentation Fundus lesion, and then remove the noise by mathematical morphology operations. Experimental results show that the algorithm can effectively identify the lesion in the Fundus image.","PeriodicalId":205738,"journal":{"name":"2012 IEEE International Conference on Computer Science and Automation Engineering","volume":"175 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fundus lesion identification based on the improved FCM and mathematical morphology\",\"authors\":\"Li Hua, Hui Zhang\",\"doi\":\"10.1109/ICSESS.2012.6269420\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fundus lesion identification is a worldwide problem. The traditional method has greater impact on human factors, subjective and cumbersome makes Fundus lesion identification Accuracy, objectivity and practicality not be guaranteed. To solve the above problem, an improved FCM algorithm for segmentation of Fundus lesion, the improved FCM algorithm clustering image segmentation Fundus lesion, and then remove the noise by mathematical morphology operations. Experimental results show that the algorithm can effectively identify the lesion in the Fundus image.\",\"PeriodicalId\":205738,\"journal\":{\"name\":\"2012 IEEE International Conference on Computer Science and Automation Engineering\",\"volume\":\"175 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Computer Science and Automation Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSESS.2012.6269420\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Computer Science and Automation Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2012.6269420","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fundus lesion identification based on the improved FCM and mathematical morphology
Fundus lesion identification is a worldwide problem. The traditional method has greater impact on human factors, subjective and cumbersome makes Fundus lesion identification Accuracy, objectivity and practicality not be guaranteed. To solve the above problem, an improved FCM algorithm for segmentation of Fundus lesion, the improved FCM algorithm clustering image segmentation Fundus lesion, and then remove the noise by mathematical morphology operations. Experimental results show that the algorithm can effectively identify the lesion in the Fundus image.