Dongbo Zhang, Xiong Li, Xingyu Shang, Yao Yi, Yaonan Wang
{"title":"糖尿病视网膜病变图像出血检测的鲁棒性","authors":"Dongbo Zhang, Xiong Li, Xingyu Shang, Yao Yi, Yaonan Wang","doi":"10.1109/ACPR.2011.6166529","DOIUrl":null,"url":null,"abstract":"To improve the robust performance to detect hemorrhage lesions in diabetic retinopathy image, a background estimation and vessel exclusion based algorithm is proposed in this paper. Candidate hemorrhages are located by background estimation and Mahalanobis distance, and then on the basis of shape analysis, vessel exclusion is conducted to remove non hemorrhage pixels. Experiments results show that the performance of our method is effective to reduce the false negative results arise from inaccurate vessel structure.","PeriodicalId":287232,"journal":{"name":"The First Asian Conference on Pattern Recognition","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Robust hemorrhage detection in diabetic retinopathy image\",\"authors\":\"Dongbo Zhang, Xiong Li, Xingyu Shang, Yao Yi, Yaonan Wang\",\"doi\":\"10.1109/ACPR.2011.6166529\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve the robust performance to detect hemorrhage lesions in diabetic retinopathy image, a background estimation and vessel exclusion based algorithm is proposed in this paper. Candidate hemorrhages are located by background estimation and Mahalanobis distance, and then on the basis of shape analysis, vessel exclusion is conducted to remove non hemorrhage pixels. Experiments results show that the performance of our method is effective to reduce the false negative results arise from inaccurate vessel structure.\",\"PeriodicalId\":287232,\"journal\":{\"name\":\"The First Asian Conference on Pattern Recognition\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The First Asian Conference on Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACPR.2011.6166529\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The First Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2011.6166529","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust hemorrhage detection in diabetic retinopathy image
To improve the robust performance to detect hemorrhage lesions in diabetic retinopathy image, a background estimation and vessel exclusion based algorithm is proposed in this paper. Candidate hemorrhages are located by background estimation and Mahalanobis distance, and then on the basis of shape analysis, vessel exclusion is conducted to remove non hemorrhage pixels. Experiments results show that the performance of our method is effective to reduce the false negative results arise from inaccurate vessel structure.