This is the official Pytorch implementation of my paper: "Weakly-supervised Biomechanically-constrained CT/MRI Registration of the Spine" (MICCAI 2022)
Python 3.8.8
Numpy 1.23.4
Scipy 1.9.3
Pytorch 1.13.0
MONAI 1.0.1
MMCV 1.7.0
MMENGINE 0.5.0
WANDB 0.13.10
SimpleITK 2.0.2
├──data_dir
│ ├──train
│ │ ├──001
│ │ │ ├──ct.nii.gz
│ │ │ ├──ct_mask.nii.gz
│ │ │ ├──mr_t1.nii.gz
│ │ │ ├──mr_mask.nii.gz
│ │ ├──002
...
│ ├──val
│ │ ├──...
...
│ ├──test
│ │ ├──...
Since the dataset used in the paper is confidential and belongs to the hospital, we cannot share it. If you are also doing spine registration and trying to construct your own dataset, it's recommended to use the free spine CT vertebra segmentation webtool Anduin.
The pretrained model weights are also unable to share due to the confidentiality of the dataset.
I use Weight&Biases for logging in training. It's convenient to use (view the plot without ssh to port) and free. If you prefer to use tensorboard, you could also construct your own logger and add it to run_epoch.
Check Elastix.
If you find this repository useful in your research, please consider to cite use in your work by:
@inproceedings{jian2022weakly,
title={Weakly-supervised Biomechanically-constrained CT/MRI Registration of the Spine},
author={Jian, Bailiang and Azampour, Mohammad Farid and De Benetti, Francesca and Oberreuter, Johannes and Bukas, Christina and Gersing, Alexandra S and Foreman, Sarah C and Dietrich, Anna-Sophia and Rischewski, Jon and Kirschke, Jan S and others},
booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2022: 25th International Conference, Singapore, September 18--22, 2022, Proceedings, Part VI},
pages={227--236},
year={2022},
organization={Springer}
}
Many thanks to the following repositories for providing helpful resources to my work:
© Bailiang Jian Licensed under the MIT Licensce