Techniques for temporal registration of retinal images

Temporal registration of retinal images is helpful to provide physicians important information in tracking the evolution of eye-related diseases. The vascular structure of the retina is the most appropriate feature representation for registration. This paper describes a fast chamfer matching applied to the vascular structure to align pairs of fundus images. While the fast chamfer matching is able to achieve successful alignment consistently, it fails to find correct model parameters in a few cases. To alleviate this problem, we propose a nonparametric elastic matching method. The two matching algorithms are tested on 98 pairs of temporal fundus images. We found that elastic matching gives better performance than the fast chamfer matching method where there are 3 failure cases were reported.