Medical Domain Generalization (mDG) aims to improve the ability of models to generalize to unseen medical domains, which is particularly important for the clinical deployment of histopathology image analysis systems across different hospitals and imaging devices. However, due to variations in staining protocols, scanner characteristics, and tissue preparation procedures, pathological images often exhibit significant domain shifts, posing substantial challenges for traditional supervised learning methods and existing domain generalization approaches.