README

[MICCAI2023] The official implementation of Low-dose CT image super-resolution network with dual-guidance feature distillation and dual-path content communication.

This repository is modified from BasicSR. Thanks for the open source code of BasicSR.

Installation

conda create -n new_env python=3.9.7 -y
conda activate new_env
pip install -r requirements.txt
pip install -e .

More details could be found in the installation ducoment of BasicSR.

Data preparation

You should prepare your data in this way:

data_rootdir
    - dataset_name
        - img
            - hr_nd
                - train
                - val
                - test
            - lr_ld
                - x2
                    - train
                    - train_avg
                    - val
                    - val_avg
                    - test
                    - test_avg
                - x4
                    - train
                    - train_avg
                    - val
                    - val_avg
                    - test
                    - test_avg
            - lr_nd
                - x2
                    - train
                    - val
                    - test
                - x4
                    - train
                    - val
                    - test
        -mask
            - hr
                - train
                - val
                - test
            - x2
                - train
                - val
                - test
            - x4
                - train
                - val
                - test

And you should modify the path in configuration files in "opations/train/*.yml" or "opations/test/*.yml".

Training

Run:

python basicsr/train.py --opt options/train/your_config_file.yml

The model files will be saved in "experiments" folder.

Testing

Firstly, you should modify the model paths in "opations/test/*.yml". Then, run:

python basicsr/test.py --opt options/test/your_config_file.yml

The results will be saved in "results" folder.

An example, including models and dataset, could be found in BaiduDisk:z3gy.

Cite

@inproceedings{chi2023low,
  title={Low-Dose CT Image Super-Resolution Network with Dual-Guidance Feature Distillation and Dual-Path Content Communication},
  author={Chi, Jianning and Sun, Zhiyi and Zhao, Tianli and Wang, Huan and Yu, Xiaosheng and Wu, Chengdong},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={98--108},
  year={2023},
  organization={Springer}
}