Awesome

Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV

PyTorch implementation for 《Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV》

!!! Check our paper collection of recent Awesome-RWKV-in-Vision

Network Architecture

Effective Receptive Field

Visualization

Dataset

You can download the preprocessed datasets for MRI image super-resolution, CT image denoising, and PET image synthesis from Baidu Netdisk here.

The original dataset for MRI super-resolution and CT denoising are as follows:

• MRI super-resolution: IXI dataset

• CT denoising: AAPM dataset

TODO

• Restore-RWKV based on RWKV6
• Release the arXiv version paper
• Restore-RWKV based on RWKV4

Citation

If you find Restore-RWKV useful in your research, please consider citing:

@misc{yang2024restorerwkv,
      title={Restore-RWKV: Efficient and Effective Medical Image Restoration with RWKV}, 
      author={Zhiwen Yang and Hui Zhang and Dan Zhao and Bingzheng Wei and Yan Xu},
      year={2024},
      eprint={2407.11087},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}