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posal's Introduction

pOSAL: Patch-based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation.


We provide the Keras implements based on Tensorflow Backend for REFUGE challenge segmentation task.

Getting Started

Prerequisites

  • python 3.5
  • tensorflow 1.4.0
  • keras 2.2.0
  • GPU, CUDA

Packages

  • tqdm
  • skimage
  • opencv
  • scipy
  • matplotlib

Running Evaluation

  • Clone this repo:
git clone https://github.com/EmmaW8/pOSAL.git
cd pOSAL
python predict.py

Running Training for Dri-GS dataset

python train_DGS.py
python test_DGS.py

Before running test, please check whether the model weight path is correct.

Acknowledge Some codes are revised according to selimsef/dsb2018_topcoders and HzFu/MNet_DeepCDR. Thank them very much.

Citation

@article{wang2019patch,
  journal={IEEE Transactions on Medical Imaging},
  title={Patch-Based Output Space Adversarial Learning for Joint Optic Disc and Cup Segmentation},
  author={Wang, Shujun and Yu, Lequan and Yang, Xin and Fu, Chi-Wing and Heng, Pheng-Ann},
  year={2019},
  volume={38},
  number={11},
  pages={2485-2495},
  publisher={IEEE},
  doi={10.1109/TMI.2019.2899910},
  }

posal's People

Contributors

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Watchers

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