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cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…