PyTorch implementation for All-In-One Medical Image Restoration via Task-Adaptive Routing 
You can download the preprocessed datasets for MRI super-resolution, CT denoising, and PET synthesis from Baidu Netdisk here.
The original dataset for MRI super-resolution and CT denoising are as follows:
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MRI super-resolution: IXI dataset
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CT denoising: AAPM dataset
You can use AMIDE to visualize the ".nii" file. Note that the color map for MRI and CT images is "black/white linear," while the color map for PET images is "white/black linear." Additionally, you need to rescale the PET image according to the voxel size specified in the paper.
If you find AMIR useful in your research, please consider citing:
@inproceedings{yang2024amir,
title={All-In-One Medical Image Restoration via Task-Adaptive Routing},
author={Yang, Zhiwen and Chen, Haowei and Qian, Ziniu and Yi, Yang and Zhang, Hui and Zhao, Dan and Wei, Bingzheng and Xu, Yan},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={67--77},
year={2024},
organization={Springer}
}