Abstract:

Multi-modality image registration is widely used in remote sensing, clinical medicine and other fields. Many models for multi-modality image registration have been proposed in the past few decades. Concerning this problem, there are two major challenges: (1) the existence of physical mesh folding; (2) the ill-posedness of similarity measure minimization/maximization problem. In order to address those problems, a multi-scale approach for diffeomorphic image registration based on Rényi's statistical dependence measure is proposed, which can avoid estimating joint probability density function, and obtain a smooth minimizer of the energy functional without mesh folding and prior regularization. In addition, the existence of solution for the proposed model and the convergence of the multi-scale approach are proved. And numerical experiments are performed to show the efficiency of the proposed algorithm in the monomodality image registration and multi-modality image registration.

Key words: Multi-modality, Diffeomorphic, Multi-scale, Image registration, Rényi's statistical dependence measure