This digital poster session presents recent advances in segmentation methodologies for musculoskeletal (MSK) MRI, spanning joints, bones, cartilage, muscle, and multi-tissue analysis. Methodological themes include atlas-based and shape-model approaches, diffusion- and wavelet-driven augmentation, semi-supervised and transformer-based learning, LLM-enhanced multimodal networks, and interactive user-in-the-loop segmentation. These contributions emphasize robust, data-efficient, and clinically meaningful MSK segmentation, supporting quantitative biomarkers, reproducibility, and improved workflow integration.

Skill Level: Intermediate