deerta0103 / FATFusion

[IPM 2024] Official implementation of FATFusion: A Functional-Anatomical Transformer for Medical Image Fusion

FATFusion: A Functional–Anatomical Transformer for Medical Image Fusion (IPM 2024).

This is the official implementation of the FATFusion model proposed in the paper (FATFusion: A Functional–Anatomical Transformer for Medical Image Fusion) 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 Trained Model is here.

Cite the paper

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

@ARTICLE{Tang_2024_FATFusion,
  author={Tang, Wei and He, Fazhi},
  journal={Information Processing & Management}, 
  title={FATFusion: A Functional–Anatomical Transformer for Medical Image Fusion}, 
  year={2024},
  volume={61},
  number={4},
  pages={103687},
  doi={10.1016/j.ipm.2024.103687}}

If you have any questions, feel free to contact me ([e-mail]).