10 citations · 16 across the 11 of their papers we have counts for
11 papers
QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View
Trinh T. L. Vuong, Doanh C. Bui, Jin Tae Kwak
In this paper, we present our solutions for a spectrum of automation tasks in life-saving intervention procedures within the Trauma THOMPSON (T3) Challenge, encompassing action rec…
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…
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…
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…
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-…