2 citations · 2 across the 1 of their papers we have counts for
4 papers
Atlas: A Novel Pathology Foundation Model by Mayo Clinic, Charité, and Aignostics
Maximilian Alber, Stephan Tietz, Jonas Dippel +24
Recent advances in digital pathology have demonstrated the effectiveness of foundation models across diverse applications. In this report, we present Atlas, a novel vision foundati…
Do Histopathological Foundation Models Eliminate Batch Effects? A Comparative Study
Jonah Kömen, Hannah Marienwald, Jonas Dippel +1
Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the lack of annotated data…
AI-based Anomaly Detection for Clinical-Grade Histopathological Diagnostics
Jonas Dippel, Niklas Prenißl, Julius Hense +10
While previous studies have demonstrated the potential of AI to diagnose diseases in imaging data, clinical implementation is still lagging behind. This is partly because AI models…
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder
Jonas Dippel, Matthias Lenga, Thomas Goerttler +2
It is common practice to reuse models initially trained on different data to increase downstream task performance. Especially in the computer vision domain, ImageNet-pretrained wei…