Heart Position Estimation based on Bone Distribution toward Autonomous Robotic Fetal Ultrasonography

Yuuki Shida, Ryosuke Tsumura, Takabumi Watanabe, Hiroyasu Iwata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Autonomous fetal ultrasonography with a robotic ultrasound (US) can potentially solve the issue of the shortage of ob-gyn physicians in prenatal care. In fetal cardiac diagnosis, acoustic shading derived from the fetal skeleton makes the scanning procedure using a robotic US cumbersome. We hypothesize that fetal bone distribution can be used for determining the fetal position and for subsequently estimating the heart position. This paper serves a method for estimating fetal heart position for autonomous cardiac diagnosis. Our proposed system is comprised of following three processes. First, the fetal bone distribution is generated by following steps: detect shadow areas derived from fetal bones; calculate the three-dimensional (3D) position of the bones; and identify bone types (skull, spine, and others) based on its shadow features. Next, the fetal head position and body axis are estimated based on the generated 3D bone distribution. Finally, the fetal chest position and thoracic sagittal axis of the fetus are estimated based on anatomical structures, and the position of the heart is determined. We validated the proposed method by evaluating the accuracies of bone detection and heart position estimation with three pregnant volunteers. The false positive rate of bone detection is less than 10%, which is sufficient for the proposed method; further, the estimation error for the heart position was within an acceptable error of 15 mm. These results demonstrate the sufficient accuracy of the proposed estimation method and suggest the potential of autonomous fetal cardiac diagnosis using robotic US scanning.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages11393-11399
Number of pages7
ISBN (Electronic)9781728190778
DOIs
Publication statusPublished - 2021
Event2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China
Duration: 2021 May 302021 Jun 5

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2021-May
ISSN (Print)1050-4729

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Country/TerritoryChina
CityXi'an
Period21/5/3021/6/5

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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