5 citations · 5 across the 11 of their papers we have counts for
7 papers · 1 filter
Paired Uterine Whole-Slide Images and Pathology Reports for Multimodal Computational Pathology
Han Li, Jingsong Liu, Ayako Ura +14
Uterine diseases represent an important category of gynecologic pathology and require accurate histopathological assessment for diagnosis and treatment planning. Whole-slide images…
A Breast Vision Pathology Foundation Model for Real-world Clinical Utility
Yingxue Xu, Zhengyu Zhang, Xiuming Zhang +32
Pathology foundation models have shown strong retrospective performance, but whether such systems can support clinically relevant use remains unclear. This challenge is particularl…
A Deployment-Friendly Foundational Framework for Efficient Computational Pathology
Yu Cai, Cheng Jin, Zhengyu Zhang +25
Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image analysis. Here, we present LitePath, a dep…
Accurate and Scalable Multimodal Pathology Retrieval via Attentive Vision-Language Alignment
Hongyi Wang, Zhengjie Zhu, Junlin Hou +13
The rapid digitization of histopathology slides has opened new opportunities for computational tools in clinical and research workflows. Content-based slide retrieval can help path…
Generative AI for Misalignment-Resistant Virtual Staining to Accelerate Histopathology Workflows
Jiabo MA, Wenqiang Li, Jinbang Li +7
Accurate histopathological diagnosis often requires multiple differently stained tissue sections, a process that is time-consuming, labor-intensive, and environmentally taxing due…
A Versatile Foundation Model for AI-enabled Mammogram Interpretation
Fuxiang Huang, Jiayi Zhu, Yunfang Yu +20
Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in women globally. Mammography is essential for the early detection and diagno…
A Unified Low-level Foundation Model for Enhancing Pathology Image Quality
Ziyi Liu, Zhe Xu, Jiabo Ma +7
Foundation models have revolutionized computational pathology by achieving remarkable success in high-level diagnostic tasks, yet the critical challenge of low-level image enhancem…