3 papers
eess.IV2024
NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning
Saul Fuster, Umay Kiraz, Trygve Eftestøl +2
The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime…
cs.CV2024
Self-Contrastive Weakly Supervised Learning Framework for Prognostic Prediction Using Whole Slide Images
Saul Fuster, Farbod Khoraminia, Julio Silva-RodrÃguez +7
We present a pioneering investigation into the application of deep learning techniques to analyze histopathological images for addressing the substantial challenge of automated pro…
eess.IV2024
Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offs
Neel Kanwal, Farbod Khoraminia, Umay Kiraz +6
Histopathology is a gold standard for cancer diagnosis under a microscopic examination. However, histological tissue processing procedures result in artifacts, which are ultimately…