Automatic detection of fovea using property of vessel free region

2015 Twenty First National Conference on Communications (NCC) Pub Date : 2015-04-16 DOI:10.1109/NCC.2015.7084852

J. Medhi, S. Dandapat

{"title":"Automatic detection of fovea using property of vessel free region","authors":"J. Medhi, S. Dandapat","doi":"10.1109/NCC.2015.7084852","DOIUrl":null,"url":null,"abstract":"Accumulation of blood and its constituents over fovea of the retina lead to irreversible vision degradation in Diabetic Retinopathy (DR). Thus, fovea location contains very vital information in automated analysis. In this study, we have developed a simple approach for identification of fovea location. The main advantage of the method is that it does not require prior knowledge of the spatial relationship of optic disc location. The algorithm first searches for the fovea region considering the information that fovea is devoid of blood vessels. Later, dark intensity property of fovea is utilized for its detection from the region of interest. The method requires detection of blood vessel network and then search for vessel free region. Various morphological image processing tools are explored in different color planes for the successful execution of the method. The algorithm is tested on 759 images of DRIVE, DIARETDB0, DIARETDB1, LOCAL, MESSIDOR and HRF databases containing both normal and pathological cases of DR, with efficiency of detection obtained at 100%, 96.85%, 97.67%, 98.46% 96.25% and 100% respectively. The overall accuracy is 98.21%.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Twenty First National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2015.7084852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 8

Abstract

Accumulation of blood and its constituents over fovea of the retina lead to irreversible vision degradation in Diabetic Retinopathy (DR). Thus, fovea location contains very vital information in automated analysis. In this study, we have developed a simple approach for identification of fovea location. The main advantage of the method is that it does not require prior knowledge of the spatial relationship of optic disc location. The algorithm first searches for the fovea region considering the information that fovea is devoid of blood vessels. Later, dark intensity property of fovea is utilized for its detection from the region of interest. The method requires detection of blood vessel network and then search for vessel free region. Various morphological image processing tools are explored in different color planes for the successful execution of the method. The algorithm is tested on 759 images of DRIVE, DIARETDB0, DIARETDB1, LOCAL, MESSIDOR and HRF databases containing both normal and pathological cases of DR, with efficiency of detection obtained at 100%, 96.85%, 97.67%, 98.46% 96.25% and 100% respectively. The overall accuracy is 98.21%.

查看原文本刊更多论文

利用无血管区特性自动检测中央凹

在糖尿病视网膜病变(DR)中，血液及其成分在视网膜中央凹的积累导致不可逆的视力退化。因此，在自动分析中，中央凹位置包含了非常重要的信息。在这项研究中，我们开发了一种简单的方法来识别中央凹的位置。该方法的主要优点是不需要事先了解视盘位置的空间关系。该算法首先考虑中央窝没有血管的信息，对中央窝区域进行搜索。然后，利用中央凹的暗强度特性从感兴趣区域进行检测。该方法首先检测血管网络，然后搜索血管无区。在不同的颜色平面上探索了各种形态图像处理工具，以成功地执行该方法。该算法在包含DR正常和病理病例的DRIVE、DIARETDB0、DIARETDB1、LOCAL、MESSIDOR和HRF数据库的759张图像上进行了测试，检测效率分别为100%、96.85%、97.67%、98.46%、96.25%和100%。总体准确率为98.21%。

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

2015 Twenty First National Conference on Communications (NCC)

自引率

0.00%

发文量