13 citations · 18 across the 3 of their papers we have counts for
3 papers
From Whole-slide Image to Biomarker Prediction: A Protocol for End-to-End Deep Learning in Computational Pathology
Omar S. M. El Nahhas, Marko van Treeck, Georg Wölflein +9
Hematoxylin- and eosin (H&E) stained whole-slide images (WSIs) are the foundation of diagnosis of cancer. In recent years, development of deep learning-based methods in computation…
Regression-based Deep-Learning predicts molecular biomarkers from pathology slides
Omar S. M. El Nahhas, Chiara M. L. Loeffler, Zunamys I. Carrero +14
Deep Learning (DL) can predict biomarkers from cancer histopathology. Several clinically approved applications use this technology. Most approaches, however, predict categorical la…
Test Time Transform Prediction for Open Set Histopathological Image Recognition
Adrian Galdran, Katherine J. Hewitt, Narmin L. Ghaffari +3
Tissue typology annotation in Whole Slide histological images is a complex and tedious, yet necessary task for the development of computational pathology models. We propose to addr…