2 citations · 4 across the 9 of their papers we have counts for
9 papers
HyperVLP: Enhancing Hierarchical Surgical Video-Language Pre-training in Hyperbolic Space
Yaojun Hu, Kun Yuan, Nassir Navab +3
Surgical vision-language foundation models typically adopt educational materials, such as surgical lecture videos, to transfer surgical knowledge encoded in language into visual re…
Surg-R1: A Hierarchical Reasoning Foundation Model for Scalable and Interpretable Surgical Decision Support with Multi-Center Clinical Validation
Jian Jiang, Chenxi Lin, Yiming Gu +24
Surgical scene understanding demands not only accurate predictions but also interpretable reasoning that surgeons can verify against clinical expertise. However, existing surgical…
Where It Moves, It Matters: Referring Surgical Instrument Segmentation via Motion
Meng Wei, Kun Yuan, Shi Li +7
Enabling intuitive, language-driven interaction with surgical scenes is a critical step toward intelligent operating rooms and autonomous surgical robotic assistance. However, the…
LapFM: A Laparoscopic Segmentation Foundation Model via Hierarchical Concept Evolving Pre-training
Qing Xu, Kun Yuan, Yuxiang Luo +4
Surgical segmentation is pivotal for scene understanding yet remains hindered by annotation scarcity and semantic inconsistency across diverse procedures. Existing approaches typic…
Recognizing Surgical Phases Anywhere: Few-Shot Test-time Adaptation and Task-graph Guided Refinement
Kun Yuan, Tingxuan Chen, Shi Li +9
The complexity and diversity of surgical workflows, driven by heterogeneous operating room settings, institutional protocols, and anatomical variability, present a significant chal…
SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting
Yiming Huang, Long Bai, Beilei Cui +6
In contemporary surgical research and practice, accurately comprehending 3D surgical scenes with text-promptable capabilities is particularly crucial for surgical planning and real…
SurgVidLM: Towards Multi-grained Surgical Video Understanding with Large Language Model
Guankun Wang, Junyi Wang, Wenjin Mo +11
Surgical scene understanding is critical for surgical training and robotic decision-making in robot-assisted surgery. Recent advances in Multimodal Large Language Models (MLLMs) ha…
EndoVLA: Dual-Phase Vision-Language-Action Model for Autonomous Tracking in Endoscopy
Chi Kit Ng, Long Bai, Guankun Wang +6
In endoscopic procedures, autonomous tracking of abnormal regions and following circumferential cutting markers can significantly reduce the cognitive burden on endoscopists. Howev…
Can DeepSeek Reason Like a Surgeon? An Empirical Evaluation for Vision-Language Understanding in Robotic-Assisted Surgery
Boyi Ma, Yanguang Zhao, Jie Wang +5
The DeepSeek models have shown exceptional performance in general scene understanding, question-answering (QA), and text generation tasks, owing to their efficient training paradig…