TL,DR arXiv
We propose a novel regularization-based sanity-enforcer method that imposes two sanity checks on the deep registration model to reduce its inverse consistency errors and increase its discriminative power simultaneously.
One can always use the google drive data files for IXI and OASIS datasets, kindly processed by Junyu Chen [here]. A big shout out to his effort.If data path is set, simply run sanity_checks_*.py
Trained models can be found [here].
@inproceedings{duan2023sanity,
title={Towards Saner Deep Image Registration},
author={Duan, Bin and Zhong, Ming and Yan, Yan},
booktitle={ICCV},
year={2023}
}
This repo is heavily based on Junyu Chen's and Tony C. W. Mok's codes. Great thanks to them!