Vibration-Based Energy Metric for Restoring Needle Alignment in Autonomous Robotic Ultrasound
Zhongyu Chen, Chenyang Li, Xuesong Li, Dianye Huang, Zhongliang Jiang, Stefanie Speidel, Xiangyu Chu, K. W. Samuel Au

TL;DR
This paper introduces a vibration-based energy metric to improve needle alignment in robotic ultrasound procedures, effectively handling cases with poor visibility and misalignment, demonstrated through ex-vivo experiments.
Contribution
The paper presents a novel vibration-based energy metric and control strategy for restoring needle alignment despite ultrasound image limitations and plane misalignments.
Findings
Achieved translational error of 0.41±0.27 mm
Achieved rotational error of 0.51±0.19 degrees
Effective in ex-vivo porcine tissue experiments
Abstract
Precise needle alignment is essential for percutaneous needle insertion in robotic ultrasound-guided procedures. However, inherent challenges such as speckle noise, needle-like artifacts, and low image resolution make robust needle detection difficult, particularly when visibility is reduced or lost. In this paper, we propose a method to restore needle alignment when the ultrasound imaging plane and the needle insertion plane are misaligned. Unlike many existing approaches that rely heavily on needle visibility in ultrasound images, our method uses a more robust feature by periodically vibrating the needle using a mechanical system. Specifically, we propose a vibration-based energy metric that remains effective even when the needle is fully out of plane. Using this metric, we develop a control strategy to reposition the ultrasound probe in response to misalignments between the imaging…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoft Robotics and Applications
