Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charit\'e, and Aignostics

Alber, Maximilian, Tietz, Stephan, Dippel, Jonas, Milbich, Timo, Lesort, Timothée, Korfiatis, Panos, Krügener, Moritz, Cancer, Beatriz Perez, Shah, Neelay, Möllers, Alexander, Seegerer, Philipp, Carpen-Amarie, Alexandra, Standvoss, Kai, Dernbach, Gabriel, de Jong, Edwin, Schallenberg, Simon, Kunft, Andreas, von Ankershoffen, Helmut Hoffer, Schaeferle, Gavin, Duffy, Patrick, Redlon, Matt, Jurmeister, Philipp, Horst, David, Ruff, Lukas, Müller, Klaus-Robert, Klauschen, Frederick, Norgan, Andrew

arXiv.org Artificial Intelligence 

Recent advances in digital pathology have demonstrated the effectiveness of foundation models across diverse applications. In this report, we present Atlas, a novel vision foundation model based on the RudolfV approach. Our model was trained on a dataset comprising 1.2 million histopathology whole slide images, collected from two medical institutions: Mayo Clinic and Charit\'e - Universt\"atsmedizin Berlin. Comprehensive evaluations show that Atlas achieves state-of-the-art performance across twenty-one public benchmark datasets, even though it is neither the largest model by parameter count nor by training dataset size.

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