1 citations · 1 across the 2 of their papers we have counts for
3 papers
Leveraging Adversarial Learning for Pathological Fidelity in Virtual Staining
José Teixeira, Pascal Klöckner, Diana Montezuma +5
In addition to evaluating tumor morphology using H&E staining, immunohistochemistry is used to assess the presence of specific proteins within the tissue. However, this is a costly…
GANs vs. Diffusion Models for virtual staining with the HER2match dataset
Pascal Klöckner, José Teixeira, Diana Montezuma +3
Virtual staining is a promising technique that uses deep generative models to recreate histological stains, providing a faster and more cost-effective alternative to traditional ti…
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…