Estimation of muscle pennation angle in ultrasound images using the beamlet transform

Ultrasound imaging has been widely used to investigate the architecture properties of skeletal muscle, including the measurement of the pennation angle. In this study, we propose a beamlet-based algorithm to detect the straight line-shaped patterns of aponeurosis, fascicle or bone, and then to quantify the pennation angle in ultrasound images. The results demonstrate that the proposed algorithm can well detect the pennatoin angles in thirty ultrasound images with the correlation coefficient of 0.945, the standard root mean square error of 0.682°, and the relative root mean square error of 3.498%. The results suggest that this beamlet-based algorithm provides an alternative approach for the orientation estimation in musculoskeletal ultrasound images.

[1]  T. Loupas,et al.  An adaptive weighted median filter for speckle suppression in medical ultrasonic images , 1989 .

[2]  Yan-Ning Zhang,et al.  Adaptive linear feature detection based on beamlet , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[3]  Ghassan Hamarneh,et al.  Automated Tracking of Muscle Fascicle Orientation in B-mode Ultrasound Images , 2022 .

[4]  Xiaoming Huo,et al.  Beamlets and Multiscale Image Analysis , 2002 .

[5]  John N. Howell,et al.  In vivo Measurement of Fascicle Length and Pennation Angle of the Human Biceps femoris Muscle , 2001, Cells Tissues Organs.

[6]  G. Loeb,et al.  Real‐time sonography to estimate muscle thickness: Comparison with MRI and CT , 2001, Journal of clinical ultrasound : JCU.

[7]  Yang Ming-qiang.  Line Detection Based on Beamlet Transform , 2007 .

[8]  Glenn R. Easley,et al.  Generalized Discrete Radon Transforms and Applications to Image Processing , 2009 .

[9]  Constantinos N. Maganaris,et al.  Ultrasonographic assessment of human skeletal muscle size , 2003, European Journal of Applied Physiology.

[10]  R. Lieber.  Skeletal Muscle Structure, Function, and Plasticity: The Physiological Basis of Rehabilitation , 2002 .

[11]  Wang Xiaohu,et al.  Image Edge Detection Based on Beamlet Transform , 2012 .

[12]  S. Gandevia,et al.  Measurement of muscle contraction with ultrasound imaging , 2003, Muscle & nerve.

[13]  Yongjin Zhou,et al.  Estimation of muscle fiber orientation in ultrasound images using revoting hough transform (RVHT). , 2008, Ultrasound in medicine & biology.

[14]  Olivier Ecabert,et al.  Adaptive Hough transform for the detection of natural shapes under weak affine transformations , 2004, Pattern Recognit. Lett..

[15]  Qinghua Huang,et al.  Continuous Monitoring of Sonomyography, Electromyography and Torque Generated by Normal Upper Arm Muscles During Isometric Contraction: Sonomyography Assessment for Arm Muscles , 2008, IEEE Transactions on Biomedical Engineering.