52 citations · 98 across the 25 of their papers we have counts for
27 papers
SurgAM: Surgical Affordance Map Prediction with Multimodal Feature Fusion for Robot Autonomy
Lei Song, Yonghao Long, Mengya Xu +3
Surgical automation is being increasingly studied, yet bridging visual scene understanding with autonomous action planning remains a fundamental challenge. While much research effo…
Generalized Recognition of Basic Surgical Actions Enables Skill Assessment and Vision-Language-Model-based Surgical Planning
Mengya Xu, Daiyun Shen, Jie Zhang +19
Artificial intelligence, imaging, and large language models have the potential to transform surgical practice, training, and automation. Understanding and modeling of basic surgica…
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…
The Dresden Dataset for 4D Reconstruction of Non-Rigid Abdominal Surgical Scenes
Reuben Docea, Rayan Younis, Yonghao Long +10
The D4D Dataset provides paired endoscopic video and high-quality structured-light geometry for evaluating 3D reconstruction of deforming abdominal soft tissue in realistic surgica…
ARport: An Augmented Reality System for Markerless Image-Guided Port Placement in Robotic Surgery
Zheng Han, Zixin Yang, Yonghao Long +3
Purpose: Precise port placement is a critical step in robot-assisted surgery, where port configuration influences both visual access to the operative field and instrument maneuvera…
Learning dissection trajectories from expert surgical videos via imitation learning with equivariant diffusion
Hongyu Wang, Yonghao Long, Yueyao Chen +6
Endoscopic Submucosal Dissection (ESD) is a well-established technique for removing epithelial lesions. Predicting dissection trajectories in ESD videos offers significant potentia…
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…
Multi-objective Cross-task Learning via Goal-conditioned GPT-based Decision Transformers for Surgical Robot Task Automation
Jiawei Fu, Yonghao Long, Kai Chen +2
Surgical robot task automation has been a promising research topic for improving surgical efficiency and quality. Learning-based methods have been recognized as an interesting para…
SimEndoGS: Efficient Data-driven Scene Simulation using Robotic Surgery Videos via Physics-embedded 3D Gaussians
Zhenya Yang, Kai Chen, Yonghao Long +1
Surgical scene simulation plays a crucial role in surgical education and simulator-based robot learning. Traditional approaches for creating these environments with surgical scene…
Efficient EndoNeRF Reconstruction and Its Application for Data-driven Surgical Simulation
Yuehao Wang, Bingchen Gong, Yonghao Long +2
The healthcare industry has a growing need for realistic modeling and efficient simulation of surgical scenes. With effective models of deformable surgical scenes, clinicians are a…
Efficient Physically-based Simulation of Soft Bodies in Embodied Environment for Surgical Robot
Zhenya Yang, Yonghao Long, Kai Chen +2
Surgical robot simulation platform plays a crucial role in enhancing training efficiency and advancing research on robot learning. Much effort have been made by scholars on develop…
Visual-Kinematics Graph Learning for Procedure-agnostic Instrument Tip Segmentation in Robotic Surgeries
Jiaqi Liu, Yonghao Long, Kai Chen +3
Accurate segmentation of surgical instrument tip is an important task for enabling downstream applications in robotic surgery, such as surgical skill assessment, tool-tissue intera…
Value-Informed Skill Chaining for Policy Learning of Long-Horizon Tasks with Surgical Robot
Tao Huang, Kai Chen, Wang Wei +3
Reinforcement learning is still struggling with solving long-horizon surgical robot tasks which involve multiple steps over an extended duration of time due to the policy explorati…
Human-in-the-loop Embodied Intelligence with Interactive Simulation Environment for Surgical Robot Learning
Yonghao Long, Wang Wei, Tao Huang +2
Surgical robot automation has attracted increasing research interest over the past decade, expecting its potential to benefit surgeons, nurses and patients. Recently, the learning…
Distilled Visual and Robot Kinematics Embeddings for Metric Depth Estimation in Monocular Scene Reconstruction
Ruofeng Wei, Bin Li, Hangjie Mo +5
Estimating precise metric depth and scene reconstruction from monocular endoscopy is a fundamental task for surgical navigation in robotic surgery. However, traditional stereo matc…
AutoLaparo: A New Dataset of Integrated Multi-tasks for Image-guided Surgical Automation in Laparoscopic Hysterectomy
Ziyi Wang, Bo Lu, Yonghao Long +4
Computer-assisted minimally invasive surgery has great potential in benefiting modern operating theatres. The video data streamed from the endoscope provides rich information to su…
Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery
Yuehao Wang, Yonghao Long, Siu Hin Fan +1
Reconstruction of the soft tissues in robotic surgery from endoscopic stereo videos is important for many applications such as intra-operative navigation and image-guided robotic s…
Robotic Surgery Remote Mentoring via AR with 3D Scene Streaming and Hand Interaction
Yonghao Long, Chengkun Li, Qi Dou
With the growing popularity of robotic surgery, education becomes increasingly important and urgently needed for the sake of patient safety. However, experienced surgeons have limi…
Integrating Artificial Intelligence and Augmented Reality in Robotic Surgery: An Initial dVRK Study Using a Surgical Education Scenario
Yonghao Long, Jianfeng Cao, Anton Deguet +2
Robot-assisted surgery has become progressively more and more popular due to its clinical advantages. In the meanwhile, the artificial intelligence and augmented reality in robotic…
PEg TRAnsfer Workflow recognition challenge report: Does multi-modal data improve recognition?
Arnaud Huaulmé, Kanako Harada, Quang-Minh Nguyen +16
This paper presents the design and results of the "PEg TRAnsfert Workflow recognition" (PETRAW) challenge whose objective was to develop surgical workflow recognition methods based…
Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery
Ruofeng Wei, Bin Li, Hangjie Mo +6
Objective: The computation of anatomical information and laparoscope position is a fundamental block of surgical navigation in Minimally Invasive Surgery (MIS). Recovering a dense…
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark
Martin Wagner, Beat-Peter Müller-Stich, Anna Kisilenko +38
PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the…
E-DSSR: Efficient Dynamic Surgical Scene Reconstruction with Transformer-based Stereoscopic Depth Perception
Yonghao Long, Zhaoshuo Li, Chi Hang Yee +4
Reconstructing the scene of robotic surgery from the stereo endoscopic video is an important and promising topic in surgical data science, which potentially supports many applicati…
Temporal Memory Relation Network for Workflow Recognition from Surgical Video
Yueming Jin, Yonghao Long, Cheng Chen +3
Automatic surgical workflow recognition is a key component for developing context-aware computer-assisted systems in the operating theatre. Previous works either jointly modeled th…