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cs.CV2026
CoralBay: A Self-Supervised CT Foundation Model
Ioannis Gatopoulos, Nicolas Känzig, Sebastian Otálora +1
Self-supervised learning has enabled large-scale pre-training on 2D natural images, producing general-purpose visual representations that transfer effectively across tasks. However…
cs.CV2025
Training state-of-the-art pathology foundation models with orders of magnitude less data
Mikhail Karasikov, Joost van Doorn, Nicolas Känzig +5
The field of computational pathology has recently seen rapid advances driven by the development of modern vision foundation models (FMs), typically trained on vast collections of p…
cs.CV2024
Towards Large-Scale Training of Pathology Foundation Models
kaiko. ai, Nanne Aben, Edwin D. de Jong +7
Driven by the recent advances in deep learning methods and, in particular, by the development of modern self-supervised learning algorithms, increased interest and efforts have bee…