4 citations · 11 across the 11 of their papers we have counts for
5 papers · 2 filters
CPath-Omni: A Unified Multimodal Foundation Model for Patch and Whole Slide Image Analysis in Computational Pathology
Yuxuan Sun, Yixuan Si, Chenglu Zhu +7
The emergence of large multimodal models (LMMs) has brought significant advancements to pathology. Previous research has primarily focused on separately training patch-level and wh…
Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysis
Honglin Li, Yunlong Zhang, Pingyi Chen +3
Histopathology Whole Slide Image (WSI) analysis serves as the gold standard for clinical cancer diagnosis in the daily routines of doctors. To develop computer-aided diagnosis mode…
Large-scale cervical precancerous screening via AI-assisted cytology whole slide image analysis
Honglin Li, Yusuan Sun, Chenglu Zhu +8
Cervical Cancer continues to be the leading gynecological malignancy, posing a persistent threat to women's health on a global scale. Early screening via cytology Whole Slide Image…
WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering
Pingyi Chen, Chenglu Zhu, Sunyi Zheng +2
Whole slide imaging is routinely adopted for carcinoma diagnosis and prognosis. Abundant experience is required for pathologists to achieve accurate and reliable diagnostic results…
Benchmarking PathCLIP for Pathology Image Analysis
Sunyi Zheng, Xiaonan Cui, Yuxuan Sun +7
Accurate image classification and retrieval are of importance for clinical diagnosis and treatment decision-making. The recent contrastive language-image pretraining (CLIP) model h…