Virchow2 is a selfsupervised vision transformer pretrained using 3.1M whole slide histopathology images. The model can be used as a tilelevel feature extractor (frozen or finetuned) to achieve stateoftheart results for a wide variety of downstream computational pathology use cases. Model D
PRISM is a multimodal generative foundation model for slidelevel analysis of H&Estained histopathology images. Utilizing Virchow tile embeddings and clinical report texts for pretraining, PRISM combines these embeddings into a single slide embedding and generates a textbased diagnostic report.
Virchow is a selfsupervised vision transformer pretrained using 1.5M whole slide histopathology images. The model can be used as a tilelevel feature extractor (frozen or finetuned) to achieve stateoftheart results for a wide variety of downstream computational pathology use cases. Model Det
Virchow2G is a selfsupervised vision transformer pretrained using 3.1M whole slide histopathology images. It supports both hematoxylin and eosin (H&E) and immunohistochemistry (IHC) stained slides, enhancing its versatility across various pathology tasks. The model can be used as a tilelevel featu
Virchow2G Mini is a distilled, lightweight vision transformer model derived from Virchow2G, designed to deliver highperformance pathology insights with exceptional computational efficiency. Trained on 3.1 million whole slide histopathology images, it serves as a tilelevel feature extractor (frozen