Virchow: A Million-Slide Digital Pathology Foundation Model

Understand

The use of artificial intelligence to enable precision medicine and decision support systems through the analysis of pathology images has the potential to revolutionize the diagnosis and treatment of cancer.

• Such applications will depend on models' abilities to capture the diverse patterns observed in pathology images.
• To address this challenge, we present Virchow, a foundation model for computational pathology.
• Using self-supervised learning empowered by the DINOv2 algorithm, Virchow is a vision transformer model with 632 million parameters trained on 1.5 million hematoxylin and eosin stained whole slide images from diverse tissue and specimen types, which is orders of magnitude more data than previous works.