3D multi-label brain tumor segmentation from multimodal MRI (FLAIR, T1w, T1gd, T2w) using Decathlon data. End-to-end workflow with 3D SegResNet, Dice loss, and Mean Dice evaluation for glioma sub-region segmentation (edema, core, necrotic/cystic, enhancing). Focused on complex, heterogeneous tumor localization in clinical neuroimaging.
machine-learning deep-learning medical imageprocessing semantic-segmentation medical-image-processing multilabel-classification medical-image-analysis mri-brain pytorch-implementation mri-segmentation wandb monai-workflows segresnet decthlondataset machinelearningmetrics diceloss clinical-neuroimaging
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Updated
Jan 1, 2026 - Jupyter Notebook