Ridge-based retinal image registration algorithm involving OCT fundus images

This paper proposes an algorithm for retinal image registration involving OCT fundus images (OFIs). The first application of the algorithm is to register OFIs with color fundus photographs; such registration between multimodal retinal images can help correlate features across imaging modalities, which is important for both clinical and research purposes. The second application is to perform the montage of several OFIs, which allows us to construct 3D OCT images over a large field of view out of separate OCT datasets. We use blood vessel ridges as registration features. The brute force search and an Iterative Closest Point (ICP) algorithm are employed for image pair registration. Global alignment to minimize the distance between matching pixel pairs is used to obtain the montage of OFIs. Quality of OFIs is the big limitation factor of the registration algorithm. In the first experiment, the effect of manual OFI enhancement on registration was evaluated for the affine model on 11 image pairs from diseased eyes. The average root mean square error (RMSE) decreases from 58 μm to 40 μm. This indicates that the registration algorithm is robust to manual enhancement. In the second experiment for the montage of OFIs, the algorithm was tested on 6 sets from healthy eyes and 6 sets from diseased eyes, each set having 8 partially overlapping SD-OCT images. Visual evaluation showed that the montage performance was acceptable for normal cases, and not good for abnormal cases due to low visibility of blood vessels. The average RMSE for a typical montage case from a healthy eye is 2.3 pixels (69 μm).