Retinal Fundus Image Registration via Vascular Structure Graph Matching

被引:31
|
作者
Deng, Kexin [1 ]
Tian, Jie [1 ,2 ]
Zheng, Jian [2 ]
Zhang, Xing [2 ]
Dai, Xiaoqian [2 ]
Xu, Min [2 ]
机构
[1] Xidian Univ, Sch Elect Engn, Xian 710071, Shanxi, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.1155/2010/906067
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Motivated by the observation that a retinal fundus image may contain some unique geometric structures within its vascular trees which can be utilized for feature matching, in this paper, we proposed a graph-based registration framework called GM-ICP to align pairwise retinal images. First, the retinal vessels are automatically detected and represented as vascular structure graphs. A graph matching is then performed to find global correspondences between vascular bifurcations. Finally, a revised ICP algorithm incorporating with quadratic transformation model is used at fine level to register vessel shape models. In order to eliminate the incorrect matches from global correspondence set obtained via graph matching, we proposed a structure-based sample consensus (STRUCT-SAC) algorithm. The advantages of our approach are threefold: (1) global optimumsolution can be achieved with graph matching; (2) ourmethod is invariant to linear geometric transformations; and (3) heavy local feature descriptors are not required. The effectiveness of our method is demonstrated by the experiments with 48 pairs retinal images collected from clinical patients.
引用
收藏
页数:13
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