7 papers
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…
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,…
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…
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…
GPC: Generative and General Pathology Image Classifier
Anh Tien Nguyen, Jin Tae Kwak
Deep learning has been increasingly incorporated into various computational pathology applications to improve its efficiency, accuracy, and robustness. Although successful, most pr…
CAMP: Continuous and Adaptive Learning Model in Pathology
Anh Tien Nguyen, Keunho Byeon, Kyungeun Kim +3
There exist numerous diagnostic tasks in pathology. Conventional computational pathology formulates and tackles them as independent and individual image classification problems, th…
Towards a text-based quantitative and explainable histopathology image analysis
Anh Tien Nguyen, Trinh Thi Le Vuong, Jin Tae Kwak
Recently, vision-language pre-trained models have emerged in computational pathology. Previous works generally focused on the alignment of image-text pairs via the contrastive pre-…