基于方向梯度的视网膜图像配准

S. Patankar, J. Kulkarni
{"title":"基于方向梯度的视网膜图像配准","authors":"S. Patankar, J. Kulkarni","doi":"10.1109/ICCIC.2012.6510276","DOIUrl":null,"url":null,"abstract":"Registration of retinal images provided by different modalities is required to facilitate diagnosis of the retina specifically in context with Diabetes Retinopathy (DR). Temporal registration is necessary in order to follow the various stages DR, whereas multimodal registration allows us to improve the identification of some lesions or to compare pieces of information gathered from different sources. This paper presents an algorithm for temporal and/or multimodal registration of retinal images based on directional gradient of salient vessel bifurcation points. Gradient along 0, +45 and 90 degrees around bifurcation point is invariant to rotation. We have validated this by using Fourier transform. This enables to estimate the correspondence of bifurcation points between the image pairs to be aligned. The retinal vessel tree is first segmented and vessel bifurcation points are located. A feature vector comprising of directional gradients along 0, +45 and 90 degrees around labeled bifurcation point in its 3 × 3 neighborhood is then computed in order to determine correspondence. The rotation is estimated from the coordinates of the matched vessel bifurcation points. The algorithm is tested on publically available DRIVE and STARE database. The overall registration error is observed to be 0.8% and 0.7% for STARE and DRIVE database respectively.","PeriodicalId":340238,"journal":{"name":"2012 IEEE International Conference on Computational Intelligence and Computing Research","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Directional gradient based registration of retinal images\",\"authors\":\"S. Patankar, J. Kulkarni\",\"doi\":\"10.1109/ICCIC.2012.6510276\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Registration of retinal images provided by different modalities is required to facilitate diagnosis of the retina specifically in context with Diabetes Retinopathy (DR). Temporal registration is necessary in order to follow the various stages DR, whereas multimodal registration allows us to improve the identification of some lesions or to compare pieces of information gathered from different sources. This paper presents an algorithm for temporal and/or multimodal registration of retinal images based on directional gradient of salient vessel bifurcation points. Gradient along 0, +45 and 90 degrees around bifurcation point is invariant to rotation. We have validated this by using Fourier transform. This enables to estimate the correspondence of bifurcation points between the image pairs to be aligned. The retinal vessel tree is first segmented and vessel bifurcation points are located. A feature vector comprising of directional gradients along 0, +45 and 90 degrees around labeled bifurcation point in its 3 × 3 neighborhood is then computed in order to determine correspondence. The rotation is estimated from the coordinates of the matched vessel bifurcation points. The algorithm is tested on publically available DRIVE and STARE database. The overall registration error is observed to be 0.8% and 0.7% for STARE and DRIVE database respectively.\",\"PeriodicalId\":340238,\"journal\":{\"name\":\"2012 IEEE International Conference on Computational Intelligence and Computing Research\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Computational Intelligence and Computing Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIC.2012.6510276\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Computational Intelligence and Computing Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIC.2012.6510276","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在糖尿病视网膜病变(DR)的背景下,需要对不同模式提供的视网膜图像进行配准,以促进视网膜的诊断。为了跟踪DR的各个阶段,时间配准是必要的,而多模态配准使我们能够改进对某些病变的识别或比较从不同来源收集的信息片段。本文提出了一种基于突出血管分叉点方向梯度的视网膜图像时间和/或多模态配准算法。围绕分岔点沿0、+45和90度的梯度对旋转是不变的。我们已经用傅里叶变换验证过了。这样就可以估计待对齐图像对之间分岔点的对应关系。首先对视网膜血管树进行分割,定位血管分叉点。然后计算其3 × 3邻域中标记分岔点周围沿0、+45和90度方向梯度的特征向量,以确定对应关系。从匹配的血管分岔点的坐标估计旋转。该算法在公开的DRIVE和STARE数据库上进行了测试。对于STARE和DRIVE数据库,总的注册误差分别为0.8%和0.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Directional gradient based registration of retinal images
Registration of retinal images provided by different modalities is required to facilitate diagnosis of the retina specifically in context with Diabetes Retinopathy (DR). Temporal registration is necessary in order to follow the various stages DR, whereas multimodal registration allows us to improve the identification of some lesions or to compare pieces of information gathered from different sources. This paper presents an algorithm for temporal and/or multimodal registration of retinal images based on directional gradient of salient vessel bifurcation points. Gradient along 0, +45 and 90 degrees around bifurcation point is invariant to rotation. We have validated this by using Fourier transform. This enables to estimate the correspondence of bifurcation points between the image pairs to be aligned. The retinal vessel tree is first segmented and vessel bifurcation points are located. A feature vector comprising of directional gradients along 0, +45 and 90 degrees around labeled bifurcation point in its 3 × 3 neighborhood is then computed in order to determine correspondence. The rotation is estimated from the coordinates of the matched vessel bifurcation points. The algorithm is tested on publically available DRIVE and STARE database. The overall registration error is observed to be 0.8% and 0.7% for STARE and DRIVE database respectively.
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:604180095
Book学术官方微信