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JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection

Shell 7.60% JavaScript 0.01% Python 92.20% MATLAB 0.20%

joined's Introduction

JOINED

This repository is an official PyTorch implementation of paper:

JOINED: Prior guided multi-task learning for joint optic disc/cup segmentation and fovea detection. In Medical Imaging with Deep Learning MIDL (2022), 2022.

MIDL 2022 image

Usage

1. Prepare data

Please go to "./Dataset/README.md" for details.

2. Environment

Please prepare an environment with python >= 3.7, and the use the command pip install -r requirements.txt for the dependencies.

3. Train/Test

  • Run the train script on GAMMA dataset. The batch size can be reduce to 8 or 4 to save memory (please also decrease the base_lr linearly), and both can reach similar performance. First coarse stage :
cd Coarse
bash train_smp.sh

After Coarse stage, you need to run the eval.sh to get the cropped data and then run the fine stage :

cd Fine
bash train.sh
  • Run the test script on GAMMA dataset. First coarse stage :
cd Coarse
bash eval.sh

After Coarse stage, and get the cropped data, run the fine stage :

cd Fine
bash eval.sh

Citations

@inproceedings{he2022joined,
    title={{JOINED}: Prior Guided Multitask Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection},
    author={Huaqing He and Li Lin and Zhiyuan Cai and Xiaoying Tang},
    booktitle={Medical Imaging with Deep Learning},
    year={2022},
    url={https://openreview.net/forum?id=HU6-t9oKvRW}
}

joined's People

Contributors

huaqinghe avatar

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