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Body surface registration considering individual differences with non-rigid iterative closest point.

Ryosuke Tsumura1, Yuko Morishima2, Yoshihiko Koseki3

  • 1Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki, Japan. ryosuke.tsumura@aist.go.jp.

International Journal of Computer Assisted Radiology and Surgery
|February 6, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a non-rigid iterative closest point (ICP) registration method to guide stethoscope placement in remote auscultation. Selecting a similar body model significantly improves accuracy for telemedicine applications.

Keywords:
AuscultationCardiac examinationNon-rigid iterative closest pointRegistrationTelemedicine

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Area of Science:

  • Medical technology
  • Biomedical engineering
  • Telemedicine

Background:

  • Remote auscultation in telemedicine requires accurate stethoscope placement.
  • Individual body shape differences pose challenges for consistent medical equipment positioning.

Purpose of the Study:

  • To develop an efficient navigation system for stethoscope placement in remote auscultation.
  • To address individual body shape variations for accurate medical equipment localization.

Main Methods:

  • Proposed a non-rigid iterative closest point (ICP)-based registration method.
  • Utilized body surface registration between patient and reference models.
  • Investigated the impact of reference model similarity on registration accuracy.

Main Results:

  • Simulation showed registration error increases with body shape deviation.
  • Experimental results demonstrated an average error of 5-19 mm with similar reference models.
  • High correlation found between registration accuracy and model similarity.

Conclusions:

  • The non-rigid ICP registration method accurately localizes auscultation areas considering body shape.
  • Registration accuracy is highly dependent on the similarity between patient and reference body surfaces.
  • Validated through simulation and human trials, this method shows promise for telemedicine.