4 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
Uncertainty Estimation in Pathology Foundation Models via Deep Mutual Learning
Gbègninougbo Aurel Davy Tchokponhoue, Sevda Öğüt, Ali Idri +2
Pathology foundation models (PFMs) offer generalizable representations for whole-slide image (WSI) analysis, yet their clinical adoption remains limited. Specifically, their predic…
GrapHist: Graph Self-Supervised Learning for Histopathology
Sevda Öğüt, Cédric Vincent-Cuaz, Natalia Dubljevic +4
Self-supervised vision models have achieved notable success in digital pathology. However, their domain-agnostic transformer architectures are not originally designed to account fo…
Revisiting Automatic Data Curation for Vision Foundation Models in Digital Pathology
Boqi Chen, Cédric Vincent-Cuaz, Lydia A. Schoenpflug +12
Vision foundation models (FMs) are accelerating the development of digital pathology algorithms and transforming biomedical research. These models learn, in a self-supervised manne…