Deep Learning-Based Brain Tissue Segmentation Using U-Net and MRI Data
Published:
Developed a U-Net model for CSF, GM, and WM segmentation from IBSR18 MRI scans, with advanced preprocessing, augmentation, and one-hot encoding. Achieved strong Dice scores using a PyTorch pipeline with Weights & Biases for experiment tracking and hyperparameter optimization.
Keywords: Brain Tissue Segmentation, U-Net, MRI, IBSR18, PyTorch, Weights & Biases, Deep Learning