Diffeomorphic image registration with automatic time-step adjustment

In this paper, we propose an automated Euler´s time-step adjustment scheme for diffeomorphic image registration using stationary velocity fields (SVFs). The proposed variational problem aims at bounding the inverse consistency error by adaptively adjusting the number of Euler´s step required to realize the time integration. This particular formulation allows us to gain computationally since only relevant number of time steps are taken. We parameterize the SVFs using multi-scale Wendland kernels through the kernel bundle framework. In terms of performance, the proposed scheme reaches the same accuracy as a fixed time-step scheme however at a much less computational cost.