Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements
Tracking the myotendinous junction (MTJ) motion in consecutive ultrasound images is essential to assess muscle and tendon interaction and understand the mechanics’ muscle-tendon unit and its pathological conditions during motion. However, the inherent speckle noises and ambiguous boundari...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10016656/ |
| _version_ | 1797805029085675520 |
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| author | Guang-Quan Zhou Shi-Hao Hua Yikang He Kai-Ni Wang Dandan Zhou Hongxing Wang Ruoli Wang |
| author_facet | Guang-Quan Zhou Shi-Hao Hua Yikang He Kai-Ni Wang Dandan Zhou Hongxing Wang Ruoli Wang |
| author_sort | Guang-Quan Zhou |
| collection | DOAJ |
| description | Tracking the myotendinous junction (MTJ) motion in consecutive ultrasound images is essential to assess muscle and tendon interaction and understand the mechanics’ muscle-tendon unit and its pathological conditions during motion. However, the inherent speckle noises and ambiguous boundaries deter the reliable identification of MTJ, thus restricting their usage in human motion analysis. This study advances a fully automatic displacement measurement method for MTJ using prior shape knowledge on the Y-shape MTJ, precluding the influence of irregular and complicated hyperechoic structures in muscular ultrasound images. Our proposed method first adopts the junction candidate points using a combined measure of Hessian matrix and phase congruency, followed by a hierarchical clustering technique to refine the candidates approximating the position of the MTJ. Then, based on the prior knowledge of Y-shape MTJ, we finally identify the best matching junction points according to intensity distributions and directions of their branches using multiscale Gaussian templates and a Kalman filter. We evaluated our proposed method using the ultrasound scans of the gastrocnemius from 8 young, healthy volunteers. Our results present more consistent with the manual method in the MTJ tracking method than existing optical flow tracking methods, suggesting its potential in facilitating muscle and tendon function examinations with in vivo ultrasound imaging. |
| first_indexed | 2024-03-13T05:45:54Z |
| format | Article |
| id | doaj.art-87fa7676137b4d6a957d5b612c8cc815 |
| institution | Directory Open Access Journal |
| issn | 1558-0210 |
| language | English |
| last_indexed | 2024-03-13T05:45:54Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj.art-87fa7676137b4d6a957d5b612c8cc8152023-06-13T20:10:28ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1558-02102023-01-013185186210.1109/TNSRE.2023.323558710016656Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template MeasurementsGuang-Quan Zhou0https://orcid.org/0000-0002-6467-3592Shi-Hao Hua1https://orcid.org/0000-0001-9474-6580Yikang He2https://orcid.org/0000-0002-6347-7098Kai-Ni Wang3https://orcid.org/0000-0002-4000-188XDandan Zhou4Hongxing Wang5Ruoli Wang6https://orcid.org/0000-0002-2232-5258School of Biological Science and Medical Engineering, Southeast University, Nanjing, ChinaSchool of Biological Science and Medical Engineering, Southeast University, Nanjing, ChinaDepartment of Rehabilitation Medicine, Zhongda Hospital, Southeast University, Nanjing, ChinaSchool of Biological Science and Medical Engineering, Southeast University, Nanjing, ChinaDepartment of Critical Care Medicine, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, ChinaDepartment of Rehabilitation Medicine, Zhongda Hospital, Southeast University, Nanjing, ChinaDepartment of Engineering Mechanics, KTH MoveAbility Laboratory, Royal Institute of Technology, Stockholm, SwedenTracking the myotendinous junction (MTJ) motion in consecutive ultrasound images is essential to assess muscle and tendon interaction and understand the mechanics’ muscle-tendon unit and its pathological conditions during motion. However, the inherent speckle noises and ambiguous boundaries deter the reliable identification of MTJ, thus restricting their usage in human motion analysis. This study advances a fully automatic displacement measurement method for MTJ using prior shape knowledge on the Y-shape MTJ, precluding the influence of irregular and complicated hyperechoic structures in muscular ultrasound images. Our proposed method first adopts the junction candidate points using a combined measure of Hessian matrix and phase congruency, followed by a hierarchical clustering technique to refine the candidates approximating the position of the MTJ. Then, based on the prior knowledge of Y-shape MTJ, we finally identify the best matching junction points according to intensity distributions and directions of their branches using multiscale Gaussian templates and a Kalman filter. We evaluated our proposed method using the ultrasound scans of the gastrocnemius from 8 young, healthy volunteers. Our results present more consistent with the manual method in the MTJ tracking method than existing optical flow tracking methods, suggesting its potential in facilitating muscle and tendon function examinations with in vivo ultrasound imaging.https://ieeexplore.ieee.org/document/10016656/Myotendinous junction detectionultrasoundhierarchical clusteringHessian matrixphase congruencyGaussian templates |
| spellingShingle | Guang-Quan Zhou Shi-Hao Hua Yikang He Kai-Ni Wang Dandan Zhou Hongxing Wang Ruoli Wang Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements IEEE Transactions on Neural Systems and Rehabilitation Engineering Myotendinous junction detection ultrasound hierarchical clustering Hessian matrix phase congruency Gaussian templates |
| title | Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements |
| title_full | Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements |
| title_fullStr | Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements |
| title_full_unstemmed | Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements |
| title_short | Automatic Myotendinous Junction Identification in Ultrasound Images Based on Junction-Based Template Measurements |
| title_sort | automatic myotendinous junction identification in ultrasound images based on junction based template measurements |
| topic | Myotendinous junction detection ultrasound hierarchical clustering Hessian matrix phase congruency Gaussian templates |
| url | https://ieeexplore.ieee.org/document/10016656/ |
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