Atlas 2 -- Foundation models for clinical deployment
This work addresses the need for more effective and efficient pathology foundation models for clinical use, representing a strong specific gain rather than a broad paradigm shift.
The authors tackled the problem of limited clinical deployment of pathology foundation models due to tradeoffs in performance, robustness, and computational requirements by developing Atlas 2, Atlas 2-B, and Atlas 2-S, which achieved state-of-the-art performance across eighty public benchmarks.
Pathology foundation models substantially advanced the possibilities in computational pathology -- yet tradeoffs in terms of performance, robustness, and computational requirements remained, which limited their clinical deployment. In this report, we present Atlas 2, Atlas 2-B, and Atlas 2-S, three pathology vision foundation models which bridge these shortcomings by showing state-of-the-art performance in prediction performance, robustness, and resource efficiency in a comprehensive evaluation across eighty public benchmarks. Our models were trained on the largest pathology foundation model dataset to date comprising 5.5 million histopathology whole slide images, collected from three medical institutions Charité - Universtätsmedizin Berlin, LMU Munich, and Mayo Clinic.