78 citations · 180 across the 6 of their papers we have counts for
7 papers
Sharing standardized image-derived data in computational pathology using DICOM
Daniela P. Schacherer, Christopher P. Bridge, David Clunie +13
Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into co…
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…
Joining Forces for Pathology Diagnostics with AI Assistance: The EMPAIA Initiative
Norman Zerbe, Lars Ole Schwen, Christian Geißler +17
Over the past decade, artificial intelligence (AI) methods in pathology have advanced substantially. However, integration into routine clinical practice has been slow due to numero…
Digitization of Pathology Labs: A Review of Lessons Learned
Lars Ole Schwen, Tim-Rasmus Kiehl, Rita Carvalho +2
Pathology laboratories are increasingly using digital workflows. This has the potential of increasing lab efficiency, but the digitization process also involves major challenges. S…
The NCI Imaging Data Commons as a platform for reproducible research in computational pathology
Daniela P. Schacherer, Markus D. Herrmann, David A. Clunie +7
Background and Objectives: Reproducibility is a major challenge in developing machine learning (ML)-based solutions in computational pathology (CompPath). The NCI Imaging Data Comm…
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…