conda create -n brats python=3.8
pip install -r requirements.txt

1. Download the BraTS2023 Adult Glioma dataset and put it on the dataset/ folder, so it will contain the following:

├── dataset
│   ├── ASNR-MICCAI-BraTS2023-GLI-Challenge-TrainingData
│   ├── ASNR-MICCAI-BraTS2023-GLI-Challenge-ValidationData
│   ├── brats21_folds.json
│   ├── BraTS2023_2017_GLI_Mapping.xlsx

2. Run preprocessing.py, but please check the source_directory and target_directory variables to make sure everything is correct.

conda activate brats-gli
python preprocessing.py 

For training a MedNeXt model, you can run the following command (but you may need to configure your wandb account beforehand):

python mednext_train.py

To calculate 5-fold CV Dice and HD95, we need to do two things;

• get predictions from 5-fold (cv-get-predictions.py).
• run post-processing and evaluation (cv-postprocessing-and-eval.py).
• The idea of separating cv-get-predictions.py and cv-postprocessing-and-eval.py is to allow us to tune post-processing faster.