1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Multicentric Dataset for Training and Benchmarking Breast Cancer Segmentation in H&E Slides
Carlijn Lems, Leslie Tessier, John-Melle Bokhorst +18
Automated semantic segmentation of whole-slide images (WSIs) stained with hematoxylin and eosin (H&E) is essential for large-scale artificial intelligence-based biomarker analysis…
Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers
Clément Grisi, Geert Litjens, Jeroen van der Laak
Vision Transformers are at the heart of the current surge of interest in foundation models for histopathology. They process images by breaking them into smaller patches following a…
Uncertainty-guided annotation enhances segmentation with the human-in-the-loop
Nadieh Khalili, Joey Spronck, Francesco Ciompi +2
Deep learning algorithms, often critiqued for their 'black box' nature, traditionally fall short in providing the necessary transparency for trusted clinical use. This challenge is…
Domain adaptation strategies for cancer-independent detection of lymph node metastases
Péter Bándi, Maschenka Balkenhol, Marcory van Dijk +3
Recently, large, high-quality public datasets have led to the development of convolutional neural networks that can detect lymph node metastases of breast cancer at the level of ex…