4 papers
Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures
Sweta Banerjee, Alireza Teimoury, Nils Porsche +11
Pathology foundation models (FMs) are models trained on vast amounts of typically unlabeled data and have been shown to yield regularized latent spaces that can be used effectively…
A filtering scheme for confocal laser endomicroscopy (CLE)-video sequences for self-supervised learning
Nils Porsche, Flurin Müller-Diesing, Sweta Banerjee +2
Confocal laser endomicroscopy (CLE) is a non-invasive, real-time imaging modality that can be used for in-situ, in-vivo imaging and the microstructural analysis of mucous structure…
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 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…