SLPD: Slide-level Prototypical Distillation for WSIs

Understand

Improving the feature representation ability is the foundation of many whole slide pathological image (WSIs) tasks.

• Recent works have achieved great success in pathological-specific self-supervised learning (SSL).
• However, most of them only focus on learning patch-level representations, thus there is still a gap between pretext and slide-level downstream tasks, e.g., subtyping, grading and staging.
• Aiming towards slide-level representations, we propose Slide-Level Prototypical Distillation (SLPD) to explore intra- and inter-slide semantic structures for context modeling on WSIs.