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BioMed Research International
Volume 2018 (2018), Article ID 3697835, 12 pages
https://doi.org/10.1155/2018/3697835
Research Article

Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation

1School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
2National Demonstration Center for Experimental Biomedical Engineering Education, Southeast University, Nanjing, China
3Department of Women’s and Children’s Health, Karolinska Institute, Stockholm, Sweden
4BioMEX Center and Department of Mechanics, Royal Institute of Technology, Stockholm, Sweden
5Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
6The Swedish School of Sport and Health Sciences, Stockholm, Sweden
7Department of Clinical Intervention and Technology, Karolinska Institute, Stockholm, Sweden

Correspondence should be addressed to Guang-Quan Zhou; nc.ude.ues@uohz.nauqgnaug

Received 31 August 2017; Revised 29 January 2018; Accepted 18 February 2018; Published 19 March 2018

Academic Editor: Cristiana Corsi

Copyright © 2018 Guang-Quan Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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 ( 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 = ) was more consistent with the manual measurements than existing optical flow tracking methods (CMC = ). 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.