{"title":"基于深度学习的视网膜眼底图像血管分割","authors":"L. Ngo, Jae‐Ho Han","doi":"10.1109/IWW-BCI.2017.7858169","DOIUrl":null,"url":null,"abstract":"Rising of deep learning methodologies draws huge attention to their application in image processing and classification. Catching up the trends, this study briefly presents state-of-the-art of deep learning applications in medical imaging interfered with achievements of blood vessel segmentation methods in neurosensory retinal fundus images. Successful segmentation based on deep learning offers advantage in diagnosing ophthalmological disease or pathology.","PeriodicalId":443427,"journal":{"name":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Advanced deep learning for blood vessel segmentation in retinal fundus images\",\"authors\":\"L. Ngo, Jae‐Ho Han\",\"doi\":\"10.1109/IWW-BCI.2017.7858169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rising of deep learning methodologies draws huge attention to their application in image processing and classification. Catching up the trends, this study briefly presents state-of-the-art of deep learning applications in medical imaging interfered with achievements of blood vessel segmentation methods in neurosensory retinal fundus images. Successful segmentation based on deep learning offers advantage in diagnosing ophthalmological disease or pathology.\",\"PeriodicalId\":443427,\"journal\":{\"name\":\"2017 5th International Winter Conference on Brain-Computer Interface (BCI)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th International Winter Conference on Brain-Computer Interface (BCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWW-BCI.2017.7858169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th International Winter Conference on Brain-Computer Interface (BCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWW-BCI.2017.7858169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Advanced deep learning for blood vessel segmentation in retinal fundus images
Rising of deep learning methodologies draws huge attention to their application in image processing and classification. Catching up the trends, this study briefly presents state-of-the-art of deep learning applications in medical imaging interfered with achievements of blood vessel segmentation methods in neurosensory retinal fundus images. Successful segmentation based on deep learning offers advantage in diagnosing ophthalmological disease or pathology.