43 citations · 58 across the 21 of their papers we have counts for
23 papers
Mask2Restore: Self-Supervised Ultrasound Despeckling via Inpainting
Xuesong Li, Yingtai Xu, Zhongliang Jiang +2
Medical ultrasound (US) is inherently degraded by speckle, a granular interference pattern that is often treated as a complex form of noise in image restoration. However, unlike ra…
Scanning While Imagining: A Scene-Graph World Model for Robotic Ultrasound Navigation
Xuesong Li, Shuai Chen, Feng Li +3
Ultrasound (US) acquisition depends on the operator's ability to interpret anatomy and anticipate how the view will change with probe motion. Many robotic US navigation methods sel…
Look-Closer-Then-Diagnose: Confidence-Aware Ultrasound VQA via Active Zooming
Yue Zhou, Erxuan Wu, Yikang Sun +5
Vision-Language Models (VLMs) have significantly advanced medical visual question answering, yet their performance in ultrasound remains suboptimal. In clinical practice, sonograph…
SurgOnAir: Hierarchy-Aware Real-Time Surgical Video Commentary
Jingyi He, Yue Zhou, Long Bai +3
Understanding surgical workflow in real time is fundamental for intelligent surgical embodiment, where AI systems continuously perceive and respond as surgery proceeds. In the oper…
Feasibility of Augmented Reality-Guided Robotic Ultrasound with Cone-Beam CT Integration for Spine Procedures
Tianyu Song, Felix Pabst, Feng Li +5
Accurate needle placement in spine interventions is critical for effective pain management, yet it depends on reliable identification of anatomical landmarks and careful trajectory…
From Scanning Guidelines to Action: A Robotic Ultrasound Agent with LLM-Based Reasoning
Yuan Bi, Yiping Zhou, Pei Liu +3
Robotic ultrasound offers advantages over free-hand scanning, including improved reproducibility and reduced operator dependency. In clinical practice, US acquisition relies heavil…
Robotic Ultrasound Makes CBCT Alive
Feng Li, Ziyuan Li, Zhongliang Jiang +2
Intraoperative Cone Beam Computed Tomography (CBCT) provides a reliable 3D anatomical context essential for interventional planning. However, its static nature fails to provide con…
Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment
Feng Li, Yuan Bi, Tianyu Song +2
Purpose: Spinal instability is a widespread condition that causes pain, fatigue, and restricted mobility, profoundly affecting patients' quality of life. In clinical practice, the…
UltraAD: Fine-Grained Ultrasound Anomaly Classification via Few-Shot CLIP Adaptation
Yue Zhou, Yuan Bi, Wenjuan Tong +3
Precise anomaly detection in medical images is critical for clinical decision-making. While recent unsupervised or semi-supervised anomaly detection methods trained on large-scale…
Does Machine Unlearning Truly Remove Knowledge?
Haokun Chen, Yueqi Zhang, Yuan Bi +9
In recent years, Large Language Models (LLMs) have achieved remarkable advancements, drawing significant attention from the research community. Their capabilities are largely attri…
Robotic CBCT Meets Robotic Ultrasound
Feng Li, Yuan Bi, Dianye Huang +2
The multi-modality imaging system offers optimal fused images for safe and precise interventions in modern clinical practices, such as computed tomography - ultrasound (CT-US) guid…
Gaze-Guided Robotic Vascular Ultrasound Leveraging Human Intention Estimation
Yuan Bi, Yang Su, Nassir Navab +1
Medical ultrasound has been widely used to examine vascular structure in modern clinical practice. However, traditional ultrasound examination often faces challenges related to int…
Synomaly Noise and Multi-Stage Diffusion: A Novel Approach for Unsupervised Anomaly Detection in Medical Images
Yuan Bi, Lucie Huang, Ricarda Clarenbach +4
Anomaly detection in medical imaging plays a crucial role in identifying pathological regions across various imaging modalities, such as brain MRI, liver CT, and carotid ultrasound…
Needle Segmentation Using GAN: Restoring Thin Instrument Visibility in Robotic Ultrasound
Zhongliang Jiang, Xuesong Li, Xiangyu Chu +5
Ultrasound-guided percutaneous needle insertion is a standard procedure employed in both biopsy and ablation in clinical practices. However, due to the complex interaction between…
Class-Aware Cartilage Segmentation for Autonomous US-CT Registration in Robotic Intercostal Ultrasound Imaging
Zhongliang Jiang, Yunfeng Kang, Yuan Bi +3
Ultrasound imaging has been widely used in clinical examinations owing to the advantages of being portable, real-time, and radiation-free. Considering the potential of extensive de…
Autonomous Path Planning for Intercostal Robotic Ultrasound Imaging Using Reinforcement Learning
Yuan Bi, Cheng Qian, Zhicheng Zhang +2
Ultrasound (US) has been widely used in daily clinical practice for screening internal organs and guiding interventions. However, due to the acoustic shadow cast by the subcutaneou…
Machine Learning in Robotic Ultrasound Imaging: Challenges and Perspectives
Yuan Bi, Zhongliang Jiang, Felix Duelmer +2
This article reviews the recent advances in intelligent robotic ultrasound (US) imaging systems. We commence by presenting the commonly employed robotic mechanisms and control tech…
Motion Magnification in Robotic Sonography: Enabling Pulsation-Aware Artery Segmentation
Dianye Huang, Yuan Bi, Nassir Navab +1
Ultrasound (US) imaging is widely used for diagnosing and monitoring arterial diseases, mainly due to the advantages of being non-invasive, radiation-free, and real-time. In order…
Intelligent Robotic Sonographer: Mutual Information-based Disentangled Reward Learning from Few Demonstrations
Zhongliang Jiang, Yuan Bi, Mingchuan Zhou +3
Ultrasound (US) imaging is widely used for biometric measurement and diagnosis of internal organs due to the advantages of being real-time and radiation-free. However, due to inter…
Skeleton Graph-based Ultrasound-CT Non-rigid Registration
Zhongliang Jiang, Xuesong Li, Chenyu Zhang +3
Autonomous ultrasound (US) scanning has attracted increased attention, and it has been seen as a potential solution to overcome the limitations of conventional US examinations, suc…
MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization
Yuan Bi, Zhongliang Jiang, Ricarda Clarenbach +3
Generalization capabilities of learning-based medical image segmentation across domains are currently limited by the performance degradation caused by the domain shift, particularl…
Precise Repositioning of Robotic Ultrasound: Improving Registration-based Motion Compensation using Ultrasound Confidence Optimization
Zhongliang Jiang, Nehil Danis, Yuan Bi +4
Robotic ultrasound (US) imaging has been seen as a promising solution to overcome the limitations of free-hand US examinations, i.e., inter-operator variability. However, the fact…
VesNet-RL: Simulation-based Reinforcement Learning for Real-World US Probe Navigation
Yuan Bi, Zhongliang Jiang, Yuan Gao +3
Ultrasound (US) is one of the most common medical imaging modalities since it is radiation-free, low-cost, and real-time. In freehand US examinations, sonographers often navigate a…