This repository contains the weights for a 3D U-Net model trained from scratch on the BraTS 2020 dataset for volumetric medical image segmentation. The model identifies and segments complex brain tumor sub-regions using multi-modal MRI scans (T1, T1ce, T2, FLAIR). The training pipeline was engineered using PyTorch and MONAI, featuring Automatic Mixed Precision (AMP) and overlapping sliding-window inference optimized for 16GB GPU constraints. (Note: Upload the Multi-Planar 3D reconstruction and Class-Wise Error Map images you generated in Kaggle directly here using the image upload button in the Hugging Face editor.)
Independent publisher
Sagar Kumar
sagarguptaiitp
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