9 papers
Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts
Rulin Zhou, Wanhao Liu, Guoheng Ma +8
Controllable surgical world models can provide a generative foundation for surgical artificial intelligence and simulation by synthesizing realistic instrument--tissue interactions…
EndoWAM: A Grounded World-Action Model for Generalizable Endoscopic Navigation
Jinsong Lin, Zikang Pan, Wanhao Liu +10
Autonomous endoscopic navigation can reduce clinicians' operational burden, yet robust control remains challenging due to tissue deformation, transient occlusions, and rapidly chan…
Boosting Generalizable Depth Estimation in Endoscopy by Mixture of Lightweight Experts and Intrinsic Image Alignment
Liangjing Shao, Beilei Cui, Yiming Huang +2
Depth estimation is a significant task for 3D perception in endoscopic surgeries. However, illumination interference and feature diversity in various endoscopic scenes are still ch…
Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation
Changjing Liu, Yiming Huang, Beilei Cui +5
Efficient surgical segmentation empowers clinical diagnosis, intraoperative monitoring, and downstream robotic pipelines for reconstruction and simulation. Although prompt-driven f…
CoGE: Sim-to-Real Online Geometric Estimation for Monocular Colonoscopy
Liangjing Shao, Beilei Cui, Hongliang Ren
Geometric estimation including depth estimation and scene reconstruction is a crucial technique for colonoscopy which can provide surgeons with 3D spatial perception and navigation…
EndoGMDE: Generalizable Monocular Depth Estimation with Mixture of Low-Rank Experts for Diverse Endoscopic Scenes
Liangjing Shao, Chenkang Du, Benshuang Chen +2
Self-supervised monocular depth estimation is a significant task for low-cost and efficient 3D scene perception and measurement in endoscopy. However, the variety of illumination c…