24 citations · 45 across the 17 of their papers we have counts for
20 papers
VeCAS: Vessel-Focused Contrast-Free Angiogram Synthesis for Vascular Interventions
De-Xing Huang, Chen-Yu Wang, Hao Liang +10
X-ray angiography relies on iodinated contrast agents to visualize vascular structures during image-guided interventions. However, contrast administration carries risks of adverse…
DINO-Med3D: Bridging Dimension and Domain Gaps in Volumetric Segmentation via Progressive Adaptation
Haoyu Hu, Xiyao Ma, Shiqi Liu +4
Although DINOv3 has demonstrated remarkable semantic discrimination in natural imagery, its direct application to volumetric medical segmentation is hindered by inherent dimension…
REASON: Probability map-guided dual-branch fusion framework for gastric content assessment
Nu-Fnag Xiao, De-Xing Huang, Le-Tian Wang +8
Accurate assessment of gastric content from ultrasound is critical for stratifying aspiration risk at induction of general anesthesia. However, traditional methods rely on manual t…
VLA Model Post-Training via Action-Chunked PPO and Self Behavior Cloning
Si-Cheng Wang, Tian-Yu Xiang, Xiao-Hu Zhou +6
Reinforcement learning (RL) is a promising avenue for post-training vision-language-action (VLA) models, but practical deployment is hindered by sparse rewards and unstable trainin…
Online Adaptation via Dual-Stage Alignment and Self-Supervision for Fast-Calibration Brain-Computer Interfaces
Sheng-Bin Duan, Jian-Long Hao, Tian-Yu Xiang +5
Individual differences in brain activity hinder the online application of electroencephalogram (EEG)-based brain computer interface (BCI) systems. To overcome this limitation, this…
Task-Oriented Learning for Automatic EEG Denoising
Tian-Yu Xiang, Zheng Lei, Xiao-Hu Zhou +7
Electroencephalography (EEG) denoising methods typically depend on manual intervention or clean reference signals. This work introduces a task-oriented learning framework for autom…
VasoMIM: Vascular Anatomy-Aware Masked Image Modeling for Vessel Segmentation
De-Xing Huang, Xiao-Hu Zhou, Mei-Jiang Gui +7
Accurate vessel segmentation in X-ray angiograms is crucial for numerous clinical applications. However, the scarcity of annotated data presents a significant challenge, which has…
Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends
Tian-Yu Xiang, Ao-Qun Jin, Xiao-Hu Zhou +11
Vision-language-action (VLA) models extend vision-language models (VLM) by integrating action generation modules for robotic manipulation. Leveraging the strengths of VLM in vision…
VLA Model-Expert Collaboration for Bi-directional Manipulation Learning
Tian-Yu Xiang, Ao-Qun Jin, Xiao-Hu Zhou +8
The emergence of vision-language-action (VLA) models has given rise to foundation models for robot manipulation. Although these models have achieved significant improvements, their…
Learning Novel Skills from Language-Generated Demonstrations
Ao-Qun Jin, Tian-Yu Xiang, Xiao-Hu Zhou +8
Robots are increasingly deployed across diverse domains to tackle tasks requiring novel skills. However, current robot learning algorithms for acquiring novel skills often rely on…
CAS-GAN for Contrast-free Angiography Synthesis
De-Xing Huang, Xiao-Hu Zhou, Mei-Jiang Gui +6
Iodinated contrast agents are widely utilized in numerous interventional procedures, yet posing substantial health risks to patients. This paper presents CAS-GAN, a novel GAN frame…
SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentation
De-Xing Huang, Xiao-Hu Zhou, Xiao-Liang Xie +8
Automatic vessel segmentation plays a pivotal role in the development of next-generation interventional navigation systems for surgical robotics. However, current approaches still…
MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation
De-Xing Huang, Xiao-Hu Zhou, Mei-Jiang Gui +6
Medical image segmentation takes an important position in various clinical applications. 2.5D-based segmentation models bridge the computational efficiency of 2D-based models with…
CROP: Conservative Reward for Model-based Offline Policy Optimization
Hao Li, Xiao-Hu Zhou, Shu-Hai Li +6
Offline reinforcement learning (RL) aims to optimize a policy using collected data without online interactions. Model-based approaches are particularly appealing for addressing off…
DOMAIN: MilDly COnservative Model-BAsed OfflINe Reinforcement Learning
Xiao-Yin Liu, Xiao-Hu Zhou, Mei-Jiang Gui +7
Model-based reinforcement learning (RL), which learns an environment model from the offline dataset and generates more out-of-distribution model data, has become an effective appro…
CASOG: Conservative Actor-critic with SmOoth Gradient for Skill Learning in Robot-Assisted Intervention
Hao Li, Xiao-Hu Zhou, Xiao-Liang Xie +3
Robot-assisted intervention has shown reduced radiation exposure to physicians and improved precision in clinical trials. However, existing vascular robotic systems follow master-s…
BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation
Zhen-Liang Ni, Gui-Bin Bian, Guan-An Wang +5
Surgical instrument segmentation is extremely important for computer-assisted surgery. Different from common object segmentation, it is more challenging due to the large illuminati…
RAUNet: Residual Attention U-Net for Semantic Segmentation of Cataract Surgical Instruments
Zhen-Liang Ni, Gui-Bin Bian, Xiao-Hu Zhou +6
Semantic segmentation of surgical instruments plays a crucial role in robot-assisted surgery. However, accurate segmentation of cataract surgical instruments is still a challenge d…
Attention-Guided Lightweight Network for Real-Time Segmentation of Robotic Surgical Instruments
Zhen-Liang Ni, Gui-Bin Bian, Zeng-Guang Hou +3
The real-time segmentation of surgical instruments plays a crucial role in robot-assisted surgery. However, it is still a challenging task to implement deep learning models to do r…
RASNet: Segmentation for Tracking Surgical Instruments in Surgical Videos Using Refined Attention Segmentation Network
Zhen-Liang Ni, Gui-Bin Bian, Xiao-Liang Xie +3
Segmentation for tracking surgical instruments plays an important role in robot-assisted surgery. Segmentation of surgical instruments contributes to capturing accurate spatial inf…