3 papers
cs.CV2024
FALFormer: Feature-aware Landmarks self-attention for Whole-slide Image Classification
Doanh C. Bui, Trinh Thi Le Vuong, Jin Tae Kwak
Slide-level classification for whole-slide images (WSIs) has been widely recognized as a crucial problem in digital and computational pathology. Current approaches commonly conside…
eess.IV2024
DIOR-ViT: Differential Ordinal Learning Vision Transformer for Cancer Classification in Pathology Images
Ju Cheon Lee, Keunho Byeon, Boram Song +2
In computational pathology, cancer grading has been mainly studied as a categorical classification problem, which does not utilize the ordering nature of cancer grades such as the…
cs.CV2024
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-…