COVID19

you can train your own dataset

creat a new folder 'data' and 'checkpoint'，then the directory structure is as follows:

-checkpoint

-data

-train   (train dataset)
    -image    (CT images)
    -mask     (GT images)
    -mask_    (EdgeEGT images)
-val        (validation dataset)
    -image    (CT images)
    -mask     (GT images)
    -mask_    (EdgeEGT images)

You can modify the parameter settings in /resources/train_config.yaml

-batch_size

-learning_rate

-weight_decay

-checkpoint_save_dir

-loss_function ...

finally run train.py, the model will saved in checkpoint folder.

Citation

Please cite our paper if you find the work useful:

@article{hu2022deep,
author = {Haigen Hu and Leizhao Shen and Qiu Guan and Xiaoxin Li and Qianwei Zhou and Su Ruan},
journal = {Pattern Recognition},
title = {Deep co-supervision and attention fusion strategy for automatic COVID-19 lung infection segmentation on CT images},
year = {2022},
volume = {124},
pages = {108452},
doi = {https://doi.org/10.1016/j.patcog.2021.108452},
}