Official Pytorch implementation of "Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRI" (MICCAI2023)
- Python 3.9
- asposestorage==1.0.2
- imageio==2.22.4
- matplotlib==3.6.2
- numpy==1.23.5
- opencv_python==4.6.0.66
- scikit_image==0.19.3
- scipy==1.10.1
- skimage==0.0
- thop==0.1.1.post2209072238
- torch==1.13.0
- torchvision==0.14.0
- tqdm==4.64.1
Downkload fastMRI dataset and IXI dataset.
Filter the multi contrast MRI datasets.
Run ./main.sh to train on the training dataset. Please update name_train, dir_data, save, ref_mat, ref_list in the bash file as your needs.
Download pre-trained weights and put it in the experiment folder.
Run ./test_save.sh to enlarge an LR image to an arbitrary size. Please update dir_data and pre_train in the bash file as your_path.
You can change the --scale ./test_save.sh to obtain the results of different scale factors.
You can also change the --ref_type_test ./test_save.sh to use HR(1) or LR(2) reference image.