Multimodal Retinal Image Registration Using Ransac Matching and Gradient Icp Algorithm

Abstract

Multimodal retinal imaging is an important facet of the diagnosis and therapy of retinal disorders like retinopathy, occlusion. Many imaging techniques for multimodal retinal images are developing in the recent years. These novel developments are subjected to a tradeoff between the computational time and effective registration. This study aims at developing a new algorithm based on the RANSAC matching and gradient iterative closest point technique which has proven to have less computational time with the best matched coordinates irrespective of the nature of the input retinal image. This study uses a new adaptive thresholding technique to extract the bifurcations from the target image and the control points are selected using the RANSAC matching algorithm. The registration is achieved by implementing gradient iterative closest point algorithm to minimize the mean square error between the target control points of the base and the reference images.