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Automated Image Acquisition of Parasternal Long-Axis View With Robotic Echocardiography

  • Yuuki Shida*
  • , Souto Kumagai
  • , Ryosuke Tsumura
  • , Hiroyasu Iwata
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study proposes a method for finding a parasternal long-axis view in echocardiography autonomously with a robotic ultrasound (US) system. In obtaining this view, it is necessary to avoid the ribs and lungs because they reduce the clarity of US image. Meanwhile, the anatomical position and size of the heart, lungs, and ribs differ between individuals, which makes it difficult to find the optimal position of the US probe. Our proposed system is comprised of the following three processes. First, an exhaustive scan of the chest wall region is performed. The position of the probe that allows the mitral valve to be centrally positioned is estimated based on this scan. Second, the probe is rotated once in the yaw direction while being fixed in that position. The yaw angle is estimated at a point parallel to the left ventricular longitudinal axis in the acquired images. Finally, the pitch angle of the probe is estimated so that the probe avoids the connection between the mitral valve and the papillary muscle and chordae. To validate the proposed method, we performed human trials with five healthy subjects and measured the detection rate of observation points used to evaluate the image quality of parasternal long-axis view. The result showed that the median detection rate of the observation points was 63.3 ± 5.3%, which implies that the proposed method is valid.

Original languageEnglish
Pages (from-to)5228-5235
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume8
Issue number8
DOIs
Publication statusPublished - 2023 Aug 1

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Computer vision for medical robotics
  • medical robots and systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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