4 papers
MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classification
Anh-Tien Nguyen, Duy Minh Ho Nguyen, Nghiem Tuong Diep +7
Whole slide pathology image classification presents challenges due to gigapixel image sizes and limited annotation labels, hindering model generalization. This paper introduces a p…
Normal and Abnormal Pathology Knowledge-Augmented Vision-Language Model for Anomaly Detection in Pathology Images
Jinsol Song, Jiamu Wang, Anh Tien Nguyen +4
Anomaly detection in computational pathology aims to identify rare and scarce anomalies where disease-related data are often limited or missing. Existing anomaly detection methods,…
Pathology-Informed Latent Diffusion Model for Anomaly Detection in Lymph Node Metastasis
Jiamu Wang, Keunho Byeon, Jinsol Song +4
Anomaly detection is an emerging approach in digital pathology for its ability to efficiently and effectively utilize data for disease diagnosis. While supervised learning approach…
VLEER: Vision and Language Embeddings for Explainable Whole Slide Image Representation
Anh Tien Nguyen, Keunho Byeon, Kyungeun Kim +1
Recent advances in vision-language models (VLMs) have shown remarkable potential in bridging visual and textual modalities. In computational pathology, domain-specific VLMs, which…