no code implementations • 12 Mar 2024 • Nicolas Brieu, Nicolas Triltsch, Philipp Wortmann, Dominik Winter, Shashank Saran, Marlon Rebelatto, Günter Schmidt
Generative models enable the translation from a source image domain where readily trained models are available to a target domain unseen during training.
no code implementations • 11 Mar 2024 • Dominik Winter, Nicolas Triltsch, Philipp Plewa, Marco Rosati, Thomas Padel, Ross Hill, Markus Schick, Nicolas Brieu
The creation of in-silico datasets can expand the utility of existing annotations to new domains with different staining patterns in computational pathology.
no code implementations • 28 Jun 2022 • Nicolas Brieu, Felix J. Segerer, Ansh Kapil, Philipp Wortmann, Guenter Schmidt
Unsupervised and unpaired domain translation using generative adversarial neural networks, and more precisely CycleGAN, is state of the art for the stain translation of histopathology images.
no code implementations • 10 Jul 2019 • Nicolas Brieu, Armin Meier, Ansh Kapil, Ralf Schoenmeyer, Christos G. Gavriel, Peter D. Caie, Günter Schmidt
The detection of nuclei is one of the most fundamental components of computational pathology.
no code implementations • 26 Jun 2019 • Ansh Kapil, Tobias Wiestler, Simon Lanzmich, Abraham Silva, Keith Steele, Marlon Rebelatto, Guenter Schmidt, Nicolas Brieu
The analysis of the tumor environment on digital histopathology slides is becoming key for the understanding of the immune response against cancer, supporting the development of novel immuno-therapies.
no code implementations • 28 Jun 2018 • Ansh Kapil, Armin Meier, Aleksandra Zuraw, Keith Steele, Marlon Rebelatto, Günter Schmidt, Nicolas Brieu
The level of PD-L1 expression in immunohistochemistry (IHC) assays is a key biomarker for the identification of Non-Small-Cell-Lung-Cancer (NSCLC) patients that may respond to anti PD-1/PD-L1 treatments.