基于VGG-19模型的卷积神经网络白内障检测

Md. Sajjad Mahmud Khan, Mahiuddin Ahmed, Raseduz Zaman Rasel, Mohammad Monirujjaman Khan
{"title":"基于VGG-19模型的卷积神经网络白内障检测","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":"{\"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}","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

摘要

白内障是世界范围内视力损害和失明的主要原因之一。大约有50%的人失明。因此,早期发现和预防白内障可以减少视力损害和失明。与白内障不同,人工智能(AI)在青光眼、黄斑变性、糖尿病视网膜病变、角膜状况、年龄相关眼病等眼科领域的进展相当丰硕。现有的白内障检测方法大多是基于传统的机器学习方法。另一方面,人工提取视网膜特征是一个耗时的过程,需要专业的眼科医生。为此,我们提出了一种基于卷积神经网络的彩色眼底图像白内障检测模型VGG19。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cataract Detection Using Convolutional Neural Network with VGG-19 Model
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信