activity
20202026
most citedA Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model

9 citations · 26 across the 26 of their papers we have counts for

collaborators
Showing 2025Show all

13 papers · 1 filter

cs.CV2025

MambaMIL+: Modeling Long-Term Contextual Patterns for Gigapixel Whole Slide Image

Qian Zeng, Yihui Wang, Shu Yang +9

Whole-slide images (WSIs) are an important data modality in computational pathology, yet their gigapixel resolution and lack of fine-grained annotations challenge conventional deep…

cs.CV2025

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…

cs.LG2025

A Clinical-grade Universal Foundation Model for Intraoperative Pathology

Zihan Zhao, Fengtao Zhou, Ronggang Li +20

Intraoperative pathology is pivotal to precision surgery, yet its clinical impact is constrained by diagnostic complexity and the limited availability of high-quality frozen-sectio…

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.LG2025

A Multimodal Foundation Model to Enhance Generalizability and Data Efficiency for Pan-cancer Prognosis Prediction

Huajun Zhou, Fengtao Zhou, Jiabo Ma +6

Multimodal data provides heterogeneous information for a holistic understanding of the tumor microenvironment. However, existing AI models often struggle to harness the rich inform…

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

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…

eess.IV2025

A Versatile Pathology Co-pilot via Reasoning Enhanced Multimodal Large Language Model

Zhe Xu, Ziyi Liu, Junlin Hou +13

Multimodal large language models (MLLMs) have emerged as powerful tools for computational pathology, offering unprecedented opportunities to integrate pathological images with lang…

cs.CV2025

Genome-Anchored Foundation Model Embeddings Improve Molecular Prediction from Histology Images

Cheng Jin, Fengtao Zhou, Yunfang Yu +13

Precision oncology requires accurate molecular insights, yet obtaining these directly from genomics is costly and time-consuming for broad clinical use. Predicting complex molecula…

cs.CV2025★ 3 cited

PathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncology

Jiabo Ma, Yingxue Xu, Fengtao Zhou +23

The emergence of pathology foundation models has revolutionized computational histopathology, enabling highly accurate, generalized whole-slide image analysis for improved cancer d…

cs.CV2025★ 1 cited

PathOrchestra: A Comprehensive Foundation Model for Computational Pathology with Over 100 Diverse Clinical-Grade Tasks

Fang Yan, Jianfeng Wu, Jiawen Li +24

The complexity and variability inherent in high-resolution pathological images present significant challenges in computational pathology. While pathology foundation models leveragi…

eess.IV2025

FreeTumor: Large-Scale Generative Tumor Synthesis in Computed Tomography Images for Improving Tumor Recognition

Linshan Wu, Jiaxin Zhuang, Yanning Zhou +12

Tumor is a leading cause of death worldwide, with an estimated 10 million deaths attributed to tumor-related diseases every year. AI-driven tumor recognition unlocks new possibilit…

q-bio.QM2025★ 1 cited

Generalizable Cervical Cancer Screening via Large-scale Pretraining and Test-Time Adaptation

Hao Jiang, Cheng Jin, Huangjing Lin +15

Cervical cancer is a leading malignancy in female reproductive system. While AI-assisted cytology offers a cost-effective and non-invasive screening solution, current systems strug…