A global-to-local matching strategy for registering retinal fundus images

Authors:
Xinge You;Bin Fang;Zhenyu He;Yuan Yan Tang
Affiliations:
Department of Computer Science, Hong Kong Baptist University;Department of Computer Science, Hong Kong Baptist University;Department of Computer Science, Hong Kong Baptist University;Department of Computer Science, Hong Kong Baptist University
Venue:
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
Year:
2005

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Abstract

In this paper, a multi-resolution rigid-model-based global matching algorithm is employed to register tree structures of blood vessels extracted from retinal fundus images. To further improve alignment of the vessels, a local structure-deformed elastic matching algorithm is proposed to eliminate the existence of ‘ghost vessels' for accurate registration. The matching methods are tested on 268 pairs of retinal fundus images. Experiment results show that our global-to-local registration strategy is able to achieve an average centreline mapping errors of 1.85 pixels with average execution time of 207 seconds. The registration results have also been visually validated by corresponding fusion maps.