A review on automatic identification of fovea in retinal fundus images

S. RajeshI., Bharathi Malakreddy Arikerie, B. Reshmi
{"title":"A review on automatic identification of fovea in retinal fundus images","authors":"S. RajeshI., Bharathi Malakreddy Arikerie, B. Reshmi","doi":"10.1504/ijmei.2020.10028646","DOIUrl":null,"url":null,"abstract":"Identification of retinal diseases is a very significant area of ophthalmology. Regular procedures are extremely specific, which rely on manual observation and highly prone to error. Hence, it is extremely fundamental to set up an automatic system for screening of vision threatening diseases like diabetic retinopathy (DR) and diabetic maculopathy (DM). Patients who are suffering from DR are at high risk to have DM which may lead to blindness, if not detected and treated appropriately at the appropriate time. Automatic analysis of retinal images requires knowledge and the properties of anatomical structures and retinal lesions. Thus, locating fovea plays a vital role in the analysis of retinal images. In recent times image processing has become a very effective tool for the detection and analysis of abnormalities in retinal images. This survey paper depicts the fundamental terminology related to automatic detection of macula and fovea. Literature review of various methods used for finding fovea in retinal fundus images is discussed. Detection issues involved in fovea are also discussed in this paper.","PeriodicalId":193362,"journal":{"name":"Int. J. Medical Eng. Informatics","volume":"157 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Medical Eng. Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijmei.2020.10028646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Identification of retinal diseases is a very significant area of ophthalmology. Regular procedures are extremely specific, which rely on manual observation and highly prone to error. Hence, it is extremely fundamental to set up an automatic system for screening of vision threatening diseases like diabetic retinopathy (DR) and diabetic maculopathy (DM). Patients who are suffering from DR are at high risk to have DM which may lead to blindness, if not detected and treated appropriately at the appropriate time. Automatic analysis of retinal images requires knowledge and the properties of anatomical structures and retinal lesions. Thus, locating fovea plays a vital role in the analysis of retinal images. In recent times image processing has become a very effective tool for the detection and analysis of abnormalities in retinal images. This survey paper depicts the fundamental terminology related to automatic detection of macula and fovea. Literature review of various methods used for finding fovea in retinal fundus images is discussed. Detection issues involved in fovea are also discussed in this paper.
视网膜眼底图像中中央窝自动识别的研究进展
视网膜疾病的识别是眼科的一个非常重要的领域。常规程序非常具体,依赖于人工观察,很容易出错。因此,建立糖尿病视网膜病变(DR)、糖尿病黄斑病变(DM)等威胁视力疾病的自动筛查系统是非常重要的。患有DR的患者患糖尿病的风险很高,如果不及时发现和适当治疗,糖尿病可能导致失明。视网膜图像的自动分析需要解剖学结构和视网膜病变的知识和特性。因此,中央凹的定位在视网膜图像分析中起着至关重要的作用。近年来,图像处理已成为检测和分析视网膜图像异常的有效工具。本文描述了与黄斑和中央凹自动检测相关的基本术语。本文讨论了在视网膜眼底图像中寻找中央窝的各种方法。本文还讨论了涉及中央窝的检测问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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