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http://hdl.handle.net/10397/78595
Title: | Automatic myotendinous junction tracking in ultrasound images with phase-based segmentation | Authors: | Zhou, GQ Zhang, Y Wang, RL Zhou, P Zheng, YP Tarassova, O Arndt, A Chen, Q |
Issue Date: | 2018 | Source: | BioMed research international, 2018, 3697835 | 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 (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 ofmultiple correlation (CMC). In vivo experiments demonstrated that MTJ tracking with the proposedmethod (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, whichmay facilitate further research and applications related to the architectural change of muscles and tendons. | Publisher: | Hindawi Publishing Corporation | Journal: | BioMed research international | ISSN: | 2314-6133 | EISSN: | 2314-6141 | DOI: | 10.1155/2018/3697835 | Rights: | Copyright © 2018 Guang-Quan Zhou et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The following publication Guang-Quan Zhou, Yi Zhang, Ruo-Li Wang, Ping Zhou, Yong-Ping Zheng, Olga Tarassova, Anton Arndt, Qiang Chen, "Automatic Myotendinous Junction Tracking in Ultrasound Images with Phase-Based Segmentation", BioMed Research International, vol. 2018, Article ID 3697835, 12 pages, 2018 is available at https://doi.org/10.1155/2018/3697835. |
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