4 papers · 1 filter
Beyond Sparse Captions: Aligning Slide-Level Text and Patch-Level Vision in Pathology
Daniel Shao, Dongmin Bang, Luca L. Weishaupt +6
Contrastive vision-language (VL) pretraining in computational pathology has generally relied on curated image-caption datasets sourced from social media, educational videos, and re…
VIPER: An Expert-Curated Benchmark for Vision-Language Models in Veterinary Pathology
Luca L. Weishaupt, Simone de Brot, Javier Asin +9
Pathology vision-language models are advancing rapidly, yet existing benchmarks remain focused on human tissue, particularly oncology, leaving non-human pathology largely unaddress…
Multi-Teacher Contrastive Distillation for Edge-Efficient Pathology Foundation Models
Tim Lenz, Maurice Heide, Marco Gustav +2
Computational pathology foundation models (PFMs) have advanced whole-slide image analysis. However, their size and inference cost hinder local deployment in pathology departments.…
Class Visualizations and Activation Atlases for Enhancing Interpretability in Deep Learning-Based Computational Pathology
Marco Gustav, Fabian Wolf, Christina Glasner +6
The rapid adoption of transformer-based models in computational pathology has enabled prediction of molecular and clinical biomarkers from H&E whole-slide images, yet interpretabil…