Awesome
Oval-Shape-Aware-Weakly-Semi-Supervised Optic-Disc-and-Cup-Segmentation
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Prepare your data.
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Download the pre-train Res2Net parameters and put it into ./lib/res_weight/
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https://drive.google.com/file/d/1hr5n4OuhAnEKXiVJy9aPbcRwMsiqASAb/view?usp=sharing
Train
- run python train.py
Test
- Download our pre-trained model's parameter then put it into your-own-path
- https://drive.google.com/file/d/1RBp5MjFnT7lIxI9Asu-a1P-yF-gMtc5p/view?usp=sharing
- run test.py
Citation
If you find our work useful or our work gives you any insights, please cite:
@InProceedings{Meng_2022_Shape,
title = {Shape-Aware Weakly/Semi-Supervised Optic Disc and Cup Segmentation with Regional/Marginal Consistency},
author = {Meng, Yanda and Chen, Xu and Zhang, Hongrun and Zhao, Yitian and Gao, Dongxu and Hamill, Barbra and Patri, Godhuli and Peto, Tunde and Madhusudhan, Savita and Zheng, Yalin},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
year = {2022},
organization={Springer}
}