3 papers
cs.CV2025
Leveraging Vision-Language Embeddings for Zero-Shot Learning in Histopathology Images
Md Mamunur Rahaman, Ewan K. A. Millar, Erik Meijering
Zero-shot learning holds tremendous potential for histopathology image analysis by enabling models to generalize to unseen classes without extensive labeled data. Recent advancemen…
eess.IV2025
GRAPHITE: Graph-Based Interpretable Tissue Examination for Enhanced Explainability in Breast Cancer Histopathology
Raktim Kumar Mondol, Ewan K. A. Millar, Peter H. Graham +3
Explainable AI (XAI) in medical histopathology is essential for enhancing the interpretability and clinical trustworthiness of deep learning models in cancer diagnosis. However, th…
eess.IV2024
Semi-supervised variational autoencoder for cell feature extraction in multiplexed immunofluorescence images
Piumi Sandarenu, Julia Chen, Iveta Slapetova +6
Advancements in digital imaging technologies have sparked increased interest in using multiplexed immunofluorescence (mIF) images to visualise and identify the interactions between…