19 citations · 63 across the 21 of their papers we have counts for
4 papers · 1 filter
Is Self-Supervision Enough? Benchmarking Foundation Models Against End-to-End Training for Mitotic Figure Classification
Jonathan Ganz, Jonas Ammeling, Emely Rosbach +4
Foundation models (FMs), i.e., models trained on a vast amount of typically unlabeled data, have become popular and available recently for the domain of histopathology. The key ide…
On the Value of PHH3 for Mitotic Figure Detection on H&E-stained Images
Jonathan Ganz, Christian Marzahl, Jonas Ammeling +20
The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker as it is a measure for tumor cell proliferation. However…
Model-based Cleaning of the QUILT-1M Pathology Dataset for Text-Conditional Image Synthesis
Marc Aubreville, Jonathan Ganz, Jonas Ammeling +2
The QUILT-1M dataset is the first openly available dataset containing images harvested from various online sources. While it provides a huge data variety, the image quality and com…
Deep Learning model predicts the c-Kit-11 mutational status of canine cutaneous mast cell tumors by HE stained histological slides
Chloé Puget, Jonathan Ganz, Julian Ostermaier +7
Numerous prognostic factors are currently assessed histopathologically in biopsies of canine mast cell tumors to evaluate clinical behavior. In addition, PCR analysis of the c-Kit…