23 citations · 27 across the 5 of their papers we have counts for
5 papers
CHIMERA Challenge Task 2 and 3: Response Subtypes Classification and Progression Survival Prediction in Bladder Cancer Patients using Multimodal Datasets
Catherine Chia, Tongjie Wang, Robert Spaans +12
High-risk non-muscle-invasive bladder cancer (HR-NMIBC) carries substantial risks of recurrence and progression, while current clinical risk stratification remains limited. CHIMERA…
Self-Contrastive Weakly Supervised Learning Framework for Prognostic Prediction Using Whole Slide Images
Saul Fuster, Farbod Khoraminia, Julio Silva-Rodríguez +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…
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…
Vision Transformers for Small Histological Datasets Learned through Knowledge Distillation
Neel Kanwal, Trygve Eftestol, Farbod Khoraminia +2
Computational Pathology (CPATH) systems have the potential to automate diagnostic tasks. However, the artifacts on the digitized histological glass slides, known as Whole Slide Ima…
Active Learning Based Domain Adaptation for Tissue Segmentation of Histopathological Images
Saul Fuster, Farbod Khoraminia, Trygve Eftestøl +2
Accurate segmentation of tissue in histopathological images can be very beneficial for defining regions of interest (ROI) for streamline of diagnostic and prognostic tasks. Still,…