Retinal Fundus Image Registration via Vascular Structure Graph Matching
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 retin...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2010-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2010/906067 |
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| Summary: | 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 optimum solution can be achieved with graph matching; (2)
our method 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. |
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| ISSN: | 1687-4188 1687-4196 |