ALMFnet Introduction

This is the implementation of the paper Learning to Search a Lightweight Generalized Network for Medical Image Fusion (IEEE TCSVT). Our generalized model supports the fusion of medical images combining MRI with PET/CT/SPECT modalities.

Requirements

• python >= 3.6

• pytorch >= 1.7

• torchvision >= 0.8

• For other packages, please refer to the requirements.txt

Test

python eval.py

Search & Train

step 1

python train_search_lat.py

step 2

Find the string that describes the searched architectures by using the trained model. Copy and paste it into the genotypes.py, the format should consist of the primary architecture string.

step 3

python train.py

Citation

If you use any part of this code in your research, please cite our paper:

@article{mu2023learning,
  title={Learning to Search a Lightweight Generalized Network for Medical Image Fusion},
  author={Mu, Pan and Wu, Guanyao and Liu, Jinyuan and Zhang, Yuduo and Fan, Xin and Liu, Risheng},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2023},
  publisher={IEEE}
}

Any Question

If you have any questions or concerns regarding the code, please feel free to raise them in Issues or email Guanyao Wu.