This oral session presents methodologically innovative submissions focused on segmentation in MRI, spanning brain and cardiac applications across human, fetal, neonatal, and preclinical imaging. The selected works highlight advances in high-resolution neuroanatomical segmentation, cortical and subcortical structure modeling, and cardiac structure and function segmentation, leveraging physics-guided learning, self-supervision, test-time adaptation, and domain generalization. Collectively, the session emphasizes robust segmentation methodologies that generalize across resolutions, contrasts, developmental stages, and imaging domains, reflecting the current frontier of segmentation research in MRI.

Skill Level: Intermediate