Toward Lung Ultrasound Automation: Fully Autonomous Robotic Longitudinal and Transverse Scans Along Intercostal Spaces

Long Lei, Yingbai Hu, Zixing Jiang, Juzheng Miao, Xiao Luo, Yu Zhang, Qiong Wang, Shujun Wang, Zheng Li, Pheng Ann Heng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Lung ultrasound scanning is essential for diagnosing lung diseases. The scan effectiveness critically depends on both longitudinal and transverse scans through intercostal spaces to reduce rib shadowing interference, as well as maintaining the probe perpendicular to pleura for pathological artifact generation. Achieving this level of scan quality often depends heavily on the experience of doctors. Robotic ultrasound scanning shows promise, but currently lacks a direct path planning method for intercostal scanning, and probe orientation does not consider imaging differences between lungs and solid organs. In this paper, we aim to fully automate two fundamental operations in lung ultrasound scanning: longitudinal and transverse scans. We propose pioneering path planning methods along intercostal spaces and innovative solutions for adaptive probe posture adjustment using real-time pleural line feedback, specifically addressing the unique characteristics of lung ultrasound scanning. This ensures the acquisition of high-quality, diagnostically meaningful ultrasound images. In addition, we develop a robotic lung ultrasound system to validate the proposed methods. Extensive experimental results on two volunteers and a chest phantom confirm the efficacy of our methods, and demonstrate the system's feasibility in automated lung ultrasound examinations. Our work lays a solid foundation for automated robotic complete lung scanning.

Original languageEnglish
Pages (from-to)768-781
Number of pages14
JournalIEEE Transactions on Medical Robotics and Bionics
Volume7
Issue number2
DOIs
Publication statusPublished - May 2025

Keywords

  • Robotic ultrasound system
  • lung ultrasound
  • medical automation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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