22 citations · 46 across the 18 of their papers we have counts for
19 papers
Multi-Modal Explainable Medical AI Assistant for Trustworthy Human-AI Collaboration
Honglong Yang, Shanshan Song, Yi Qin +6
Generalist Medical AI (GMAI) systems have demonstrated expert-level performance in biomedical perception tasks, yet their clinical utility remains limited by inadequate multi-modal…
Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images
Hualiang Wang, Yiqun Lin, Xinpeng Ding +1
General networks for 3D medical image segmentation have recently undergone extensive exploration. Behind the exceptional performance of these networks lies a significant demand for…
C^2RV: Cross-Regional and Cross-View Learning for Sparse-View CBCT Reconstruction
Yiqun Lin, Jiewen Yang, Hualiang Wang +3
Cone beam computed tomography (CBCT) is an important imaging technology widely used in medical scenarios, such as diagnosis and preoperative planning. Using fewer projection views…
Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Models
Xinpeng Ding, Jinahua Han, Hang Xu +3
The rise of multimodal large language models (MLLMs) has spurred interest in language-based driving tasks. However, existing research typically focuses on limited tasks and often o…
EtC: Temporal Boundary Expand then Clarify for Weakly Supervised Video Grounding with Multimodal Large Language Model
Guozhang Li, Xinpeng Ding, De Cheng +3
Early weakly supervised video grounding (WSVG) methods often struggle with incomplete boundary detection due to the absence of temporal boundary annotations. To bridge the gap betw…
GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
Jiewen Yang, Xinpeng Ding, Ziyang Zheng +2
Echocardiogram video segmentation plays an important role in cardiac disease diagnosis. This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentat…