3 papers
cs.CV2026
Leveraging Spatial Context for Positive Pair Sampling in Histopathology Image Representation Learning
Willmer Rafell Quinones Robles, Sakonporn Noree, Jongwoo Kim +3
Deep learning has shown strong potential in cancer classification from whole-slide images (WSIs), but the need for extensive expert annotations often limits its success. Annotation…
cs.CV2025
MicroMIL: Graph-Based Multiple Instance Learning for Context-Aware Diagnosis with Microscopic Images
Jongwoo Kim, Bryan Wong, Huazhu Fu +3
Cancer diagnosis has greatly benefited from the integration of whole-slide images (WSIs) with multiple instance learning (MIL), enabling high-resolution analysis of tissue morpholo…
cs.CV2025
Towards Classifying Histopathological Microscope Images as Time Series Data
Sungrae Hong, Hyeongmin Park, Youngsin Ko +3
As the frontline data for cancer diagnosis, microscopic pathology images are fundamental for providing patients with rapid and accurate treatment. However, despite their practical…