In this work, we present a novel unsupervised image registration algorithm. It is differentiable end-to-end and can be used for both multi-modal and mono-modal registration. This is done using mutual information (MI) as a metric. The novelty here is that rather than using traditional ways of approximating MI, we use a neural estimator called MINE and supplement it with matrix exponential for transformation matrix computation. This leads to improved results as compared to the standard algorithms available out-of-the-box in state-of-the-art image registration toolboxes.
@article{arxiv.2001.09865,
title = {DRMIME: Differentiable Mutual Information and Matrix Exponential for Multi-Resolution Image Registration},
author = {Abhishek Nan and Matthew Tennant and Uriel Rubin and Nilanjan Ray},
journal= {arXiv preprint arXiv:2001.09865},
year = {2020}
}