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…
Dataset creation for supervised deep learning-based analysis of microscopic images -- review of important considerations and recommendations
Christof A. Bertram, Viktoria Weiss, Jonas Ammeling +6
Supervised deep learning (DL) receives great interest for automated analysis of microscopic images with an increasing body of literature supporting its potential. The development a…
SWAN -- Enabling Fast and Mobile Histopathology Image Annotation through Swipeable Interfaces
Sweta Banerjee, Timo Gosch, Sara Hester +11
The annotation of large scale histopathology image datasets remains a major bottleneck in developing robust deep learning models for clinically relevant tasks, such as mitotic figu…
Histologic Dataset of Normal and Atypical Mitotic Figures on Human Breast Cancer (AMi-Br)
Christof A. Bertram, Viktoria Weiss, Taryn A. Donovan +6
Assessment of the density of mitotic figures (MFs) in histologic tumor sections is an important prognostic marker for many tumor types, including breast cancer. Recently, it has be…
Dataset on Bi- and Multi-Nucleated Tumor Cells in Canine Cutaneous Mast Cell Tumors
Christof A. Bertram, Taryn A. Donovan, Marco Tecilla +8
Tumor cells with two nuclei (binucleated cells, BiNC) or more nuclei (multinucleated cells, MuNC) indicate an increased amount of cellular genetic material which is thought to faci…
A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research
Marc Aubreville, Christof A. Bertram, Taryn A. Donovan +3
Canine mammary carcinoma (CMC) has been used as a model to investigate the pathogenesis of human breast cancer and the same grading scheme is commonly used to assess tumor malignan…