Skip to content

Latest commit

 

History

History
47 lines (39 loc) · 2.41 KB

README.md

File metadata and controls

47 lines (39 loc) · 2.41 KB
Raw

MATR: Multimodal Medical Image Fusion via Multiscale Adaptive Transformer (IEEE TIP 2022).

This is the official implementation of the MATR model proposed in the paper (MATR: Multimodal Medical Image Fusion via Multiscale Adaptive Transformer) with Pytorch.

Requirements

  • CUDA 11.4
  • conda 4.10.1
  • Python 3.8.12
  • PyTorch 1.9.1
  • timm 0.4.12
  • tqdm
  • glob
  • pandas

Tips:

Dealing with RGB input: Refer to DPCN-Fusion.

Dataset is here.

The code for evaluation metrics is here.

Cite the paper

If this work is helpful to you, please cite it as:

@ARTICLE{Tang_2022_MATR,
  author={Tang, Wei and He, Fazhi and Liu, Yu and Duan, Yansong},
  journal={IEEE Transactions on Image Processing}, 
  title={MATR: Multimodal Medical Image Fusion via Multiscale Adaptive Transformer}, 
  year={2022},
  volume={31},
  number={},
  pages={5134-5149},
  doi={10.1109/TIP.2022.3193288}}

If you have any questions, feel free to contact me (weitang2021@whu.edu.cn).