RetinaRegNet: A Versatile Approach for Retinal Image Registration

arXiv:2404.16017v1 Announce Type: cross
Abstract: We introduce the RetinaRegNet model, which can achieve state-of-the-art performance across various retinal image registration tasks. RetinaRegNet does not require training on any retinal images. It begins by establishing point correspondences between two retinal images using image features derived from diffusion models. This process involves the selection of feature points from the moving image using the SIFT algorithm alongside random point sampling. For each selected feature point, a 2D correlation map is computed by assessing …

arxiv cs.ai cs.cv cs.gt cs.lg image registration type