Visualization of Shoulder Ligaments Motion by Ultrasound Speckle Tracking Method

Norma Hermawan, Mizuki Fujiwara, Yoshihiro Hagiwara, Yoshifumi Saijo

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

Abstract

There is no unified consensus on the pathophysiology of adhesive capsulitis which is also called as frozen shoulder. Some studies have suggested that coracohumeral ligament (CHL) played an important role in adhesive capsulitis. These studies showed relation between disease prevalence and CHL thickness by means of ultrasound or MRI. Other possible etiology of the disease is the adhesion of shoulder ligament with each other. In the present study, shoulder ligaments motion is visualized with velocity vector by speckle tracking and temporal outlier removal algorithm to process ultrasound movie during forced movement of shoulder joint. The measurement with a typical subject has demonstrated an improvement of velocity vector deviation of up to 43% by the proposed outlier removal technique.

Original languageEnglish
Title of host publication42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEnabling Innovative Technologies for Global Healthcare, EMBC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2084-2087
Number of pages4
ISBN (Electronic)9781728119908
DOIs
Publication statusPublished - 2020 Jul
Event42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
Duration: 2020 Jul 202020 Jul 24

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2020-July
ISSN (Print)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
CountryCanada
CityMontreal
Period20/7/2020/7/24

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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