78 citations · 83 across the 7 of their papers we have counts for
5 papers · 1 filter
Rethinking U-net Skip Connections for Biomedical Image Segmentation
Frauke Wilm, Jonas Ammeling, Mathias Öttl +3
The U-net architecture has significantly impacted deep learning-based segmentation of medical images. Through the integration of long-range skip connections, it facilitated the pre…
Simple and Efficient Confidence Score for Grading Whole Slide Images
Mélanie Lubrano, Yaëlle Bellahsen-Harrar, Rutger Fick +2
Grading precancerous lesions on whole slide images is a challenging task: the continuous space of morphological phenotypes makes clear-cut decisions between different grades often…
Enabling Collagen Quantification on HE-stained Slides Through Stain Deconvolution and Restained HE-HES
Guillaume Balezo, Christof A. Bertram, Cyprien Tilmant +3
In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by adding Saffron (S) to…
Interpretable HER2 scoring by evaluating clinical Guidelines through a weakly supervised, constrained Deep Learning Approach
Manh Dan Pham, Cyprien Tilmant, Stéphanie Petit +3
The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring h…
Recommendations on test datasets for evaluating AI solutions in pathology
André Homeyer, Christian Geißler, Lars Ole Schwen +27
Artificial intelligence (AI) solutions that automatically extract information from digital histology images have shown great promise for improving pathological diagnosis. Prior to…