Md. Sajjad Mahmud Khan, Mahiuddin Ahmed, Raseduz Zaman Rasel, Mohammad Monirujjaman Khan
{"title":"Cataract Detection Using Convolutional Neural Network with VGG-19 Model","authors":"Md. Sajjad Mahmud Khan, Mahiuddin Ahmed, Raseduz Zaman Rasel, Mohammad Monirujjaman Khan","doi":"10.1109/AIIoT52608.2021.9454244","DOIUrl":null,"url":null,"abstract":"Cataract is one of the prevalent causes of visual impairment and blindness worldwide. There is around 50% of overall blindness. Therefore, an early detection and prevention of cataract may reduce the visual impairment and the blindness. The advancement of Artificial Intelligence (AI) in the field of ophthalmology such as glaucoma, macular degeneration, diabetic retinopathy, corneal conditions, age related eye diseases is quite fruitful unlike cataract. Most of the existing approaches on cataract detection are based on traditional machine learning methods. On the other hand, the manual extraction of retinal features is a time-consuming process and requires an expert ophthalmologist. So, we proposed a model VGG19 which is a convolutional neural network model to detect the cataract by using color fundus images.","PeriodicalId":443405,"journal":{"name":"2021 IEEE World AI IoT Congress (AIIoT)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE World AI IoT Congress (AIIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIIoT52608.2021.9454244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26
Abstract
Cataract is one of the prevalent causes of visual impairment and blindness worldwide. There is around 50% of overall blindness. Therefore, an early detection and prevention of cataract may reduce the visual impairment and the blindness. The advancement of Artificial Intelligence (AI) in the field of ophthalmology such as glaucoma, macular degeneration, diabetic retinopathy, corneal conditions, age related eye diseases is quite fruitful unlike cataract. Most of the existing approaches on cataract detection are based on traditional machine learning methods. On the other hand, the manual extraction of retinal features is a time-consuming process and requires an expert ophthalmologist. So, we proposed a model VGG19 which is a convolutional neural network model to detect the cataract by using color fundus images.