Models (2)
RudolfV
Aignostics / TU Berlin / BIFOLD / Charité – Universitätsmedizin Berlin / German Cancer Research Center (DKFZ) / LMU Munich / Korea University / Max Planck Institute for Informatics
Released January 8, 2024
A self-supervised foundation model for computational pathology, designed with pathologist input and trained on a diverse multi-stain whole-slide image corpus.
LVM-Med
University of Stuttgart / German Research Center for Artificial Intelligence (DFKI) / Max Planck Institute for Informatics / University of Texas at Austin / University of Bonn / University of California, San Diego / National University of Singapore
Released June 20, 2023
Self-supervised vision foundation model pretrained on ~1.3M medical images via second-order graph matching, transferable across 15 medical imaging tasks.