StainExpert: A Unified Multi-Expert Diffusion Framework for Multi-Target Pathological Stain Translation

Pathological examination is critical for disease diagnosis, with various staining techniques providing detailed visualization of tissue structures. While hematoxylin and eosin (H&E) staining remains predominant, the special stains, immunohistochemistry (IHC) and multiplex immunofluorescence (mpIF) provide valuable complementary information for comprehensive diagnosis. However, current multi-stain workflows are time-consuming, labor-intensive, and tissue-exhaustive, requiring either re-staining or additional tissue sectioning. To address these challenges, we propose StainExpert, a unified multimodal diffusion framework for source-to-multi-target pathological stain translation. Unlike existing approaches that require separate models for each staining pair, StainExpert establishes the first multi-expert system where specialized networks collaboratively learn staining principles while maintaining domain-specific expertise. Through multi-expert and multi-objective optimization, it enables efficient translation from a single source to multiple targets. Additionally, our multimodal diffusion architecture integrates textual guidance with visual features, achieving superior accuracy and pathology-informed translation. Leveraging parameter-efficient design and model distillation, StainExpert matches GAN-level efficiency while delivering superior generation quality. We validate StainExpert across three datasets spanning H&E, special stains, IHC, and mpIF modalities. Extensive evaluation demonstrates that StainExpert generates high-quality virtual stains that preserve critical pathological features for accurate diagnosis. Beyond robust cross-domain generalization, StainExpert offers a transformative platform for efficient multi-target stain translation, advancing toward streamlined, tissue-conserving, and resource-efficient diagnostic workflows in computational pathology.