光学精密工程2017，Vol.25Issue(5)：1378-1386,9.DOI:10.3788/OPE.20172505.1378
彩色视网膜眼底图像血管自动检测方法
Automatic detection method of blood vessel for color retina fundus images
摘要
Abstract
In order to provide effective foundation for retinal image registration, illumination adjustment and pathological detection of retina interior and other problems, a fully automatic method of detecting and recognizing blood vessel for color retina fundus images effectively was proposed.Aimed at the state with elongated tubular shape and preferably linear structure in local part of visible blood vessel, combinatorial shifted filter response model that is applicable to strip structure was used for feature extraction.Taking different features of blood vessel and the end of blood vessel into consideration, two types of filtering modes with symmetry and dissymmetry were configured for tracking, feature vector library was established by response acquired from combinatorial shifting filter response model (symmetry and dissymmetry) and G channel pixel value together and each pixel was classified and determined by AdaBoost classifier.The experimental result based on international public database DRIVE and STARE shows that the segmentation result of proposed method on two standard databases (DRIVE: Accuracy=0.948 9, Sensitivity=0.765 7, Specificity=0.980 9;STARE: Accuracy=0.956 7, Sensitivity=0.771 7, Specificity=0.976 6) is better than existing methods.It is applicable to computer-assisted quantitative analysis of color retina fundus images and can be used as clinical reference.关键词
视网膜图像分析/血管分割/组合移位滤波响应模型/AdaBoost分类器Key words
retinal image analysis/vessel segmentation/combinatorial shifting filter response model/AdaBoost classifier分类
信息技术与安全科学引用本文复制引用
黄文博,王珂,燕杨..彩色视网膜眼底图像血管自动检测方法[J].光学精密工程,2017,25(5):1378-1386,9.基金项目
国家留学基金委地方合作项目(No.留金法[2013]5045号) （No.留金法[2013]5045号）
吉林省教育厅"十三五"科学技术研究项目(No.吉教科合字[2016]第001号) （No.吉教科合字[2016]第001号）
长春师范大学自然科学基金资助项目(No.长师大自科合字[2015]第005号) （No.长师大自科合字[2015]第005号）
