A novel fusing algorithm for retinal fundus images

Authors:
Bin Fang;Xinge You;Yuan Yan Tang
Affiliations:
College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

In this paper, a novel fusing method for fundus retinal images based on robust registration techniques is proposed. In order to construct precise fusion map, we apply a ‘coarse-to-fine’ mapping strategy to accurately align pairs of identified vascular trees of retinas. A coarse mapping algorithm that exploits rigid model is first performed to maximize the goodness of fit between the vascular features over two time periods. However, the results suffer from local misalignment due to the inherent imprecise characteristics of the simplified model. A fine mapping algorithm is employed to eliminate ‘ghost vessels’ based on a local elastic matching technique. The transformed vectors for pixels in the registered fundus image are conveniently calculated by combining the local move vector and the global model transformed vector. Experiment results demonstrate nearly perfect fusion maps of several retinal fundus images in terms of visual inspection.