19 citations · 63 across the 21 of their papers we have counts for
4 papers · 1 filter
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…
Benchmarking Foundation Models for Mitotic Figure Classification
Jonas Ammeling, Jonathan Ganz, Emely Rosbach +4
The performance of deep learning models is known to scale with data quantity and diversity. In pathology, as in many other medical imaging domains, the availability of labeled imag…
Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation
Sweta Banerjee, Viktoria Weiss, Taryn A. Donovan +9
Atypical mitosis marks a deviation in the cell division process that has been shown be an independent prognostic marker for tumor malignancy. However, atypical mitosis classificati…