5 papers · 1 filter
Hierarchical Classification for Improved Histopathology Image Analysis
Keunho Byeon, Jinsol Song, Seong Min Hong +2
Whole-slide image analysis is essential for diagnostic tasks in pathology, yet existing deep learning methods primarily rely on flat classification, ignoring hierarchical relations…
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…
Benchmarking Pathology Foundation Models: Adaptation Strategies and Scenarios
Jeaung Lee, Jeewoo Lim, Keunho Byeon +1
In computational pathology, several foundation models have recently emerged and demonstrated enhanced learning capability for analyzing pathology images. However, adapting these mo…
Centroid-aware feature recalibration for cancer grading in pathology images
Jaeung Lee, Keunho Byeon, Jin Tae Kwak
Cancer grading is an essential task in pathology. The recent developments of artificial neural networks in computational pathology have shown that these methods hold great potentia…