ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration

Please also check out our newly proposed registration model 👉 TransMorph
The pretrained model and the quantitative results of ViT-V-Net on IXI dataset are available here: IXI_dataset.
Additionally, we have made our preprocessed IXI dataset publicly available!

keywords: vision transformer, convolutional neural networks, image registration

This is a PyTorch implementation of my short paper:

Chen, Junyu, et al. "ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration. " Medical Imaging with Deep Learning (MIDL), 2021.

train.py is the training script. models.py contains ViT-V-Net model.

Pretrained ViT-V-Net: pretrained model

Dataset: Due to restrictions, we cannot distribute our brain MRI data. However, several brain MRI datasets are publicly available online: IXI, ADNI, OASIS, ABIDE, etc. Note that those datasets may not contain labels (segmentation). To generate labels, you can use FreeSurfer, which is an open-source software for normalizing brain MRI images. Here are some useful commands in FreeSurfer: Brain MRI preprocessing and subcortical segmentation using FreeSurfer.

Model Architecture:

Vision Transformer Achitecture:

Example Results:

Quantitative Results:

Reference:

TransUnet

ViT-pytorch

VoxelMorph

If you find this code is useful in your research, please consider to cite:

@inproceedings{chen2021vitvnet,
 title={ViT-V-Net: Vision Transformer for Unsupervised Volumetric Medical Image Registration},
 author={Junyu Chen and Yufan He and Eric Frey and Ye Li and Yong Du},
  booktitle={Medical Imaging with Deep Learning},
  year={2021},
  url={https://openreview.net/forum?id=h3HC1EU7AEz}
  }