4 citations · 7 across the 6 of their papers we have counts for
6 papers
Exploring General-Purpose Autonomous Multimodal Agents for Pathology Report Generation
Marc Aubreville, Taryn A. Donovan, Christof A. Bertram
Recent advances in agentic artificial intelligence, i.e. systems capable of autonomous perception, reasoning, and tool use, offer new opportunities for digital pathology. In this p…
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…
When Two Wrongs Don't Make a Right" -- Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology
Emely Rosbach, Jonas Ammeling, Sebastian Krügel +24
Artificial intelligence (AI)-based decision support systems hold promise for enhancing diagnostic accuracy and efficiency in computational pathology. However, human-AI collaboratio…
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…
Automated Volume Corrected Mitotic Index Calculation Through Annotation-Free Deep Learning using Immunohistochemistry as Reference Standard
Jonas Ammeling, Moritz Hecker, Jonathan Ganz +4
The volume-corrected mitotic index (M/V-Index) was shown to provide prognostic value in invasive breast carcinomas. However, despite its prognostic significance, it is not establis…
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…