10 papers
Democratizing and accelerating AI-driven pathology research through agentic intelligence
Jiabo Ma, Cheng Jin, Yihui Wang +19
Computational pathology has advanced rapidly with the emergence of foundation models, yet widespread adoption remains limited by substantial technical complexity and programming re…
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, Jiabo Ma +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, Jiabo Ma +9
The rapid digitization of histopathology slides has opened up new possibilities for computational tools in clinical and research workflows. Among these, content-based slide retriev…
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…
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…