3 papers
q-bio.QM2026
WILSON - Multi-magnification composites as a foundation for patient-level pathology analysis and diagnostic text generation
Saghir Alfasly, Wataru Uegami, Sobhan Hemati +17
Pathologists examine tissue sections across multiple magnifications and slides, integrating morphological information to establish a diagnosis. In contrast, most pathology foundati…
cs.CV2026
CRISP -- Clustering-Based Redundancy-Reduced Instance Sampling for Pathology Case Representation and Retrieval
Zahra Rahimi Afzal, Wataru Uegami, Saghir Alfasly +6
Digital pathology archives increasingly contain multiple whole-slide images (WSIs) per case, capturing spatially distinct tumor regions and reflecting intrinsic morphological heter…
cs.CV2026
Validation of Whole-Slide Foundation Models for Image Retrieval in TCGA Data
Tianhao Lei, Parsa Esmaeilkhani, Saghir Alfasly +5
Foundation models are reshaping computational histopathology, yet their value for whole-slide image retrieval relative to strong patch-based and supervised aggregation baselines re…