Adaptive Affinity-Based Knowledge Distillation for Generalizable MRI Segmentation in Resource-Limited Settings

A novel relation-based knowledge distillation framework that combines adaptive affinity-based and kernel-based distillation to enable lightweight student models to effectively replicate the feature representations of powerful teacher models, facilitating robust performance even in the face of domain shift and data heterogeneity.