Some important required packages include:

• Pytorch version >=0.4.1.
• TensorBoardX
• Python == 3.6
• Efficientnet-Pytorch pip install efficientnet_pytorch
• Some basic python packages such as Numpy, Scikit-image, SimpleITK, Scipy ......

Follow official guidance to install Pytorch.

1. Clone the repo:

git clone https://github.com/HiLab-git/SSL4MIS.git
cd SSL4MIS

1. Download the processed data and put the data in ../data/BraTS2019 or ../data/ACDC, please read and follow the README.

2. Train the model

cd code
python train_XXXXX_3D.py or python train_XXXXX_2D.py or bash train_acdc_XXXXX.sh

1. Test the model

python test_XXXXX.py

• Mean Teacher[2D/3D]
• Entropy Minimization[2D/3D]
• Deep Adversarial Networks[2D/3D]
• Uncertainty Aware Mean Teacher[2D/3D]
• Interpolation Consistency Training[2D/3D]
• Uncertainty Rectified Pyramid Consistency[2D/3D]
• Cross Pseudo Supervision[2D/3D]
• Cross Consistency Training[2D]
• Deep Co-Training[2D]
• Cross Teaching between CNN and Transformer[2D]
• Regularized Dropout[2D/3D]

• Part of the code is adapted from open-source codebase and original implementations of algorithms, we thank these author for their fantastic and efficient codebase, such as, UA-MT, Attention-Gated-Networks and segmentatic_segmentation.pytorch .