3 citations · 9 across the 13 of their papers we have counts for
13 papers
Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development
Zhongying Deng, Cheng Tang, Ziyan Huang +124
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…
Glance and Focus Reinforcement for Pan-cancer Screening
Linshan Wu, Jiaxin Zhuang, Hao Chen
Pan-cancer screening in large-scale CT scans remains challenging for existing AI methods, primarily due to the difficulty of localizing diverse types of tiny lesions in large CT vo…
UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation
Linshan Wu, Yuxiang Nie, Sunan He +12
The integration of AI-assisted biomedical image analysis into clinical practice demands AI-generated findings that are not only accurate but also interpretable to clinicians. Howev…
Diffusion-based Virtual Staining from Polarimetric Mueller Matrix Imaging
Xiaoyu Zheng, Jing Wen, Jiaxin Zhuang +6
Polarization, as a new optical imaging tool, has been explored to assist in the diagnosis of pathology. Moreover, converting the polarimetric Mueller Matrix (MM) to standardized st…
Beyond H&E: Unlocking Pathological Insights with Polarization Imaging
Yao Du, Jiaxin Zhuang, Xiaoyu Zheng +5
Histopathology image analysis is fundamental to digital pathology, with hematoxylin and eosin (H&E) staining as the gold standard for diagnostic and prognostic assessments. While H…
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…