We provide the Keras implements based on Tensorflow Backend for REFUGE challenge segmentation task.
conda create -n posal python=3.5
conda activate posal
pip install keras==2.2.0
pip insatll tensorflow-gpu==1.4.0
conda install tqdm
conda install -c anaconda scikit-image
conda install opencv- GPU, CUDA=9.0
- Clone this repo:
git clone https://github.com/EmmaW8/pOSAL.git
cd pOSALpython predict.py 0 # 0 is the avaliable GPU id, change is neccesary
Remember to check/change the data path and weight path
python train_DGS.py 0
python test_DGS.py 0cd matlab-code
Please change the input and output path in the generate_CDR_values.m file.
Acknowledge Some codes are revised according to selimsef/dsb2018_topcoders, HzFu/MNet_DeepCDR and evaluateion code . Thank them very much.
@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},
}