78 citations · 180 across the 6 of their papers we have counts for
3 papers · 1 filter
Whole Slide Concepts: A Supervised Foundation Model For Pathological Images
Till Nicke, Daniela Schacherer, Jan Raphael Schäfer +6
Foundation models (FMs) are transforming computational pathology by offering new ways to analyze histopathology images. However, FMs typically require weeks of training on large da…
Recommendations on test datasets for evaluating AI solutions in pathology
André Homeyer, Christian Geißler, Lars Ole Schwen +27
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to…
Evaluating Generic Auto-ML Tools for Computational Pathology
Lars Ole Schwen, Daniela Schacherer, Christian Geißler +1
Image analysis tasks in computational pathology are commonly solved using convolutional neural networks (CNNs). The selection of a suitable CNN architecture and hyperparameters is…