331 citations · 582 across the 11 of their papers we have counts for
5 papers · 1 filter
Artificial Intelligence-Based Classification of Spitz Tumors
Ruben T. Lucassen, Marjanna Romers, Chiel F. Ebbelaar +10
Spitz tumors are diagnostically challenging due to overlap in atypical histological features with conventional melanomas. We investigated to what extent AI models, using histologic…
Multi-Scanner Canine Cutaneous Squamous Cell Carcinoma Histopathology Dataset
Frauke Wilm, Marco Fragoso, Christof A. Bertram +7
In histopathology, scanner-induced domain shifts are known to impede the performance of trained neural networks when tested on unseen data. Multi-domain pre-training or dedicated d…
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…
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…
Deep Learning-Based Grading of Ductal Carcinoma In Situ in Breast Histopathology Images
Suzanne C. Wetstein, Nikolas Stathonikos, Josien P. W. Pluim +5
Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerab…