162 citations · 652 across the 41 of their papers we have counts for
5 papers · 2 filters
Deep Learning-Based Automatic Assessment of AgNOR-scores in Histopathology Images
Jonathan Ganz, Karoline Lipnik, Jonas Ammeling +10
Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription. Due to the silver affinity of associated proteins, argyrophilic NORs (AgNORs) can be…
Mind the Gap: Scanner-induced domain shifts pose challenges for representation learning in histopathology
Frauke Wilm, Marco Fragoso, Christof A. Bertram +7
Computer-aided systems in histopathology are often challenged by various sources of domain shift that impact the performance of these algorithms considerably. We investigated the p…
Enabling Collagen Quantification on HE-stained Slides Through Stain Deconvolution and Restained HE-HES
Guillaume Balezo, Christof A. Bertram, Cyprien Tilmant +3
In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by adding Saffron (S) to…
Mitosis domain generalization in histopathology images -- The MIDOG challenge
Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram +32
The density of mitotic figures within tumor tissue is known to be highly correlated with tumor proliferation and thus is an important marker in tumor grading. Recognition of mitoti…
Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset
Frauke Wilm, Marco Fragoso, Christian Marzahl +8
Due to morphological similarities, the differentiation of histologic sections of cutaneous tumors into individual subtypes can be challenging. Recently, deep learning-based approac…