Even though simultaneous optimization of similarity metrics is a standard procedure in the field of semantic segmentation, surprisingly, this is much less established for image registration. To help closing this gap in the literature, we investigate in a complex multi-modal 3D setting whether simultaneous optimization of registration metrics, here implemented by means of primitive summation, can benefit image registration. We evaluate two challenging datasets containing collections of pre- to post-operative and pre- to intra-operative MR images of glioma. Employing the proposed optimization, we demonstrate improved registration accuracy in terms of TRE on expert neuroradiologists' landmark annotations.
@article{arxiv.2304.01601,
title = {Primitive Simultaneous Optimization of Similarity Metrics for Image Registration},
author = {Diana Waldmannstetter and Benedikt Wiestler and Julian Schwarting and Ivan Ezhov and Marie Metz and Spyridon Bakas and Bhakti Baheti and Satrajit Chakrabarty and Daniel Rueckert and Jan S. Kirschke and Rolf A. Heckemann and Marie Piraud and Bjoern H. Menze and Florian Kofler},
journal= {arXiv preprint arXiv:2304.01601},
year = {2023}
}