19 citations · 23 across the 4 of their papers we have counts for
4 papers
Robustifying pathology foundation models via fine-tuning
Alexandre Filiot, Oskar Thaeter, Benoit Schmauch +1
Pathology foundation models (FMs) produce powerful tile-level representations which remain sensitive to scanner and staining variability, undermining deployment across laboratories…
CytoSyn: a Foundation Diffusion Model for Histopathology -- Tech Report
Thomas Duboudin, Xavier Fontaine, Etienne Andrier +7
Computational pathology has made significant progress in recent years, fueling advances in both fundamental disease understanding and clinically ready tools. This evolution is driv…
Distilling foundation models for robust and efficient models in digital pathology
Alexandre Filiot, Nicolas Dop, Oussama Tchita +8
In recent years, the advent of foundation models (FM) for digital pathology has relied heavily on scaling the pre-training datasets and the model size, yielding large and powerful…
Phikon-v2, A large and public feature extractor for biomarker prediction
Alexandre Filiot, Paul Jacob, Alice Mac Kain +1
Gathering histopathology slides from over 100 publicly available cohorts, we compile a diverse dataset of 460 million pathology tiles covering more than 30 cancer sites. Using this…