6 citations · 8 across the 3 of their papers we have counts for
3 papers
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
Valentin Anklin, Pushpak Pati, Guillaume Jaume +6
Segmenting histology images into diagnostically relevant regions is imperative to support timely and reliable decisions by pathologists. To this end, computer-aided techniques have…
Quantifying Explainers of Graph Neural Networks in Computational Pathology
Guillaume Jaume, Pushpak Pati, Behzad Bozorgtabar +7
Explainability of deep learning methods is imperative to facilitate their clinical adoption in digital pathology. However, popular deep learning methods and explainability techniqu…
NINEPINS: Nuclei Instance Segmentation with Point Annotations
Ting-An Yen, Hung-Chun Hsu, Pushpak Pati +3
Deep learning-based methods are gaining traction in digital pathology, with an increasing number of publications and challenges that aim at easing the work of systematically and ex…