Recent advances in digital pathology have demonstrated the effectiveness of foundation models across diverse applications. In this report, we present 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 our model 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.

本研究解决了数字病理领域模型性能不足的问题，提出了一种基于RudolfV方法的新型视觉基础模型。该模型在来自梅奥诊所和夏里特医学大学的120万张组织病理全切片图像上进行了训练，并在21个公共基准数据集上实现了领先的表现，展示了其显著的应用潜力。

梅奥诊所、夏里特医院和Aignostics提出的新型病理基础模型