Automated multi-class knee cartilage segmentation on magnetic resonance imaging (MRI) scans from the Osteoarthritis Initiative (OAI / OAIZIB-CM). This repository provides a deep learning testbed for benchmarking and evaluating 2D, 2.5D, and 3D segmentation architectures on femoral cartilage (FC), medial tibial cartilage (MTC), and lateral tibial cartilage (LTC). - UNet (2D Slice baseline) - Pseudo3D (2.5D Triplet channel-stacking) - nnUNet (2D residual blocks with deep supervision) - TransUNet (Hybrid CNN-Transformer encoder with ViT bottleneck) - UNet3D (Volumetric 3D U-Net with attention gates) 1. Install dependencies: 2. Generate an experiment notebook
Independent publisher
Kunal Mahajan
ChodBhangra
Models in Library1
Datasets in Library0
Models on Hugging Face2
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