Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics

• URL: http://arxiv.org/abs/2501.05409v2
• Date: Fri, 10 Jan 2025 16:58:29 GMT
• Title: Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics
• Authors: Maximilian Alber, Stephan Tietz, Jonas Dippel, Timo Milbich, Timothée Lesort, Panos Korfiatis, Moritz Krügener, Beatriz Perez Cancer, Neelay Shah, Alexander Möllers, Philipp Seegerer, Alexandra Carpen-Amarie, Kai Standvoss, Gabriel Dernbach, Edwin de Jong, Simon Schallenberg, Andreas Kunft, Helmut Hoffer von Ankershoffen, Gavin Schaeferle, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew Norgan,
• Abstract summary: 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.
• Score: 61.0008867391683
• License:
• Abstract: 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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