Vesi Yulyanti, Hanung Adi Nugroho, I. Ardiyanto, Widhia K.Z. Oktoeberza
{"title":"基于面积、偏心率和范围特征的深色病灶消除,支持出血检测","authors":"Vesi Yulyanti, Hanung Adi Nugroho, I. Ardiyanto, Widhia K.Z. Oktoeberza","doi":"10.21924/CST.4.1.2019.110","DOIUrl":null,"url":null,"abstract":"One of the complications due to the long-term of diabetes is retinal vessels damaging called diabetic retinopathy. It is characterised by appearing the bleeding spots in the large size (haemorrhages) on the surface of retina. Early detection of haemorrhages is needed for preventing the worst effect which leads to vision loss. This study aims to detect haemorrhages by eliminating other dark lesion objects that have similar characteristics with haemorrhages based on three features, i.e. area, eccentricity and extent features. This study uses 43 retinal fundus images taken from DIARETDB1 database. Based on the validation process, the average level of sensitivity gained is 80.5%. These results indicate that the proposed method is quite capable of detecting haemorrhages which appear in the retinal surface.","PeriodicalId":36437,"journal":{"name":"Communications in Science and Technology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection\",\"authors\":\"Vesi Yulyanti, Hanung Adi Nugroho, I. Ardiyanto, Widhia K.Z. Oktoeberza\",\"doi\":\"10.21924/CST.4.1.2019.110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the complications due to the long-term of diabetes is retinal vessels damaging called diabetic retinopathy. It is characterised by appearing the bleeding spots in the large size (haemorrhages) on the surface of retina. Early detection of haemorrhages is needed for preventing the worst effect which leads to vision loss. This study aims to detect haemorrhages by eliminating other dark lesion objects that have similar characteristics with haemorrhages based on three features, i.e. area, eccentricity and extent features. This study uses 43 retinal fundus images taken from DIARETDB1 database. Based on the validation process, the average level of sensitivity gained is 80.5%. These results indicate that the proposed method is quite capable of detecting haemorrhages which appear in the retinal surface.\",\"PeriodicalId\":36437,\"journal\":{\"name\":\"Communications in Science and Technology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications in Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21924/CST.4.1.2019.110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21924/CST.4.1.2019.110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Dark lesion elimination based on area, eccentricity and extent features for supporting haemorrhages detection
One of the complications due to the long-term of diabetes is retinal vessels damaging called diabetic retinopathy. It is characterised by appearing the bleeding spots in the large size (haemorrhages) on the surface of retina. Early detection of haemorrhages is needed for preventing the worst effect which leads to vision loss. This study aims to detect haemorrhages by eliminating other dark lesion objects that have similar characteristics with haemorrhages based on three features, i.e. area, eccentricity and extent features. This study uses 43 retinal fundus images taken from DIARETDB1 database. Based on the validation process, the average level of sensitivity gained is 80.5%. These results indicate that the proposed method is quite capable of detecting haemorrhages which appear in the retinal surface.