![](/images/graphics-bg.png)
Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation
Joint Authors
Zheng, Yongping
Zhou, Guang-Quan
Zhang, Yi
Wang, Ruo-Li
Zhou, Ping
Tarassova, Olga
Arndt, Anton
Chen, Qiang
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-19
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Displacement of the myotendinous junction (MTJ) obtained by ultrasound imaging is crucial to quantify the interactive length changes of muscles and tendons for understanding the mechanics and pathological conditions of the muscle-tendon unit during motion.
However, the lack of a reliable automatic measurement method restricts its application in human motion analysis.
This paper presents an automated measurement of MTJ displacement using prior knowledge on tendinous tissues and MTJ, precluding the influence of nontendinous components on the estimation of MTJ displacement.
It is based on the perception of tendinous features from musculoskeletal ultrasound images using Radon transform and thresholding methods, with information about the symmetric measures obtained from phase congruency.
The displacement of MTJ is achieved by tracking manually marked points on tendinous tissues with the Lucas-Kanade optical flow algorithm applied over the segmented MTJ region.
The performance of this method was evaluated on ultrasound images of the gastrocnemius obtained from 10 healthy subjects (26.0±2.9 years of age).
Waveform similarity between the manual and automatic measurements was assessed by calculating the overall similarity with the coefficient of multiple correlation (CMC).
In vivo experiments demonstrated that MTJ tracking with the proposed method (CMC = 0.97±0.02) was more consistent with the manual measurements than existing optical flow tracking methods (CMC = 0.79±0.11).
This study demonstrated that the proposed method was robust to the interference of nontendinous components, resulting in a more reliable measurement of MTJ displacement, which may facilitate further research and applications related to the architectural change of muscles and tendons.
American Psychological Association (APA)
Zhou, Guang-Quan& Zhang, Yi& Wang, Ruo-Li& Zhou, Ping& Zheng, Yongping& Tarassova, Olga…[et al.]. 2018. Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation. BioMed Research International،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1126015
Modern Language Association (MLA)
Zhou, Guang-Quan…[et al.]. Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation. BioMed Research International No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1126015
American Medical Association (AMA)
Zhou, Guang-Quan& Zhang, Yi& Wang, Ruo-Li& Zhou, Ping& Zheng, Yongping& Tarassova, Olga…[et al.]. Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation. BioMed Research International. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1126015
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1126015