2 citations · 3 across the 6 of their papers we have counts for
7 papers
A general-purpose System One decision model for clinical records
Andrew Zhang, Trinh T. L. Vuong, Sophia J. Wagner +14
Clinical care, health-system operations and biomedical discovery depend on extracting reliable answers from patient records, yet applying diverse clinical questions across entire p…
MiTHras: Task-specific Hierarchical Semi-supervised Contrastive Masked Autoencoder for Mitotic Figure Analysis
Trinh T. L. Vuong, Simon Graham, Quoc Dang Vu +5
Mitotic figure (MF) analysis supports tumor grading and prognostic assessment, but automated models remain sensitive to differences in tissue type and image acquisition. We present…
S-Chain: Structured Visual Chain-of-Thought For Medicine
Khai Le-Duc, Duy M. H. Nguyen, Phuong T. H. Trinh +21
Faithful reasoning in medical vision-language models (VLMs) requires not only accurate predictions but also transparent alignment between textual rationales and visual evidence. Wh…
ViDRiP-LLaVA: A Dataset and Benchmark for Diagnostic Reasoning from Pathology Videos
Trinh T. L. Vuong, Jin Tae Kwak
We present ViDRiP-LLaVA, the first large multimodal model (LMM) in computational pathology that integrates three distinct image scenarios, including single patch images, automatica…
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…
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-…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…