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01_Data_preprocessing.ipynb		01_Data_preprocessing.ipynb
02_Training_3D_U-Net-83.59iou.ipynb		02_Training_3D_U-Net-83.59iou.ipynb
README.md		README.md

README.md

Training 3D U-Net for Brain Tumor Segmentation (BraTS-GLI)

This folder contains the Jupyter Notebooks for the LearnOpenCV article - Training 3D U-Net for Brain Tumor Segmentation (BraTS2023-GLI).

We have provided:

code to prepare dataset (01_Data_Preprocessing.ipynb)
Model Training Script (02_Training_3D_U-Net-83.59iou.ipynb)
Video inference code, at the last section of (02_Training_3D_U-Net-83.59iou.ipynb)

Model Download:

Download trained model from here and place it under model_checkpoint/3D_UNet_Brats2023/version_0/ckpt.tar . One can simply change the relative model path according to your notebook.

Instructions:

Run the 01_Data_Preprocessing.ipynb to download and preprocess the BraTS2023-GLI Subset from Kaggle.
After data preprocessing steps, switch to 02_Training_3D_U-Net-83.59iou.ipynb for custom data loader preparation, model definition, training and inference scripts.

You can download the trained weights and code files as well from the below link.

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