A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation

Chenghao Jiang, Renkai Wu, Yinghao Liu, Yue Wang, Qing Chang, Pengchen Liang*, and Yuan Fan*

1. Nanjing Medical University, Nanjing, China
2. Shanghai University, Shanghai, China
3. The Affiliated Stomatological Hospital of Nanjing Medical University, Nanjing, China
4. Jiangsu Province Engineering Research Center of Stomatological Translational Medicine, Nanjing, China
5. University of Shanghai for Science and Technology, Shanghai, China

Examples of proposed dataset segmentation tasks

Examples.of.proposed.dataset.segmentation.tasks.mp4

Examples of proposed dataset classification tasks

Examples.of.proposed.dataset.classification.tasks.mp4

0. Main Environments.

• python 3.8
• pytorch 1.12.0

1. The proposed datasets (Autooral dataset).
(1) The Autooral dataset is available here. It should be noted:

1. If you use the dataset, please cite the paper: https://www.nature.com/articles/s41598-024-69125-9
2. The Autooral dataset may only be used for academic research, not for commercial purposes.
3. If you can, please give us a like (Starred) for our GitHub project: https://github.com/wurenkai/HF-UNet-and-Autooral-dataset

(2) After getting the Autooral dataset, execute 'Prepare_Autooral.py' for preprocessing to generate the npy file. We also provide annotations for categorization to provide more richness to the study.

2. Train the HF-UNet.
Modify the dataset address in the config_setting.py file to the address where the npy is stored after preprocessing. Then, perform the following operation:

python train.py

• After trianing, you could obtain the outputs in './results/'

3. Test the HF-UNet.
First, in the test.py file, you should change the address of the checkpoint in 'resume_model' and fill in the location of the test data in 'data_path'.

python test.py

• After testing, you could obtain the outputs in './results/'

Citation

If you find this repository helpful, please consider citing:

@article{jiang2024high,
  title={A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation},
  author={Jiang, Chenghao and Wu, Renkai and Liu, Yinghao and Wang, Yue and Chang, Qing and Liang, Pengchen and Fan, Yuan},
  journal={Scientific Reports},
  volume={14},
  number={1},
  pages={20085},
  year={2024},
  publisher={Nature Publishing Group UK London}
}

References

• MHorUNet
• HorNet

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