SemaNorm: Stain Normalization via Semantic and Morphology Alignment for Robust Cross-Hospital Computational Pathology

Stain variability remains a major source of domain shift in computational pathology, yet existing normalization methods largely optimize color consistency without explicitly preserving morphology or diagnostic semantics. We propose SemaNorm, a self-supervised stain canonicalization stain normalizer