Literature DB >> 19646699

Automated tracking of muscle fascicle orientation in B-mode ultrasound images.

Manku Rana1, Ghassan Hamarneh, James M Wakeling.   

Abstract

B-mode ultrasound can be used to non-invasively image muscle fascicles during both static and dynamic contractions. Digitizing these muscle fascicles can be a timely and subjective process, and usually studies have used the images to determine the linear fascicle lengths. However, fascicle orientations can vary along each fascicle (curvature) and between fascicles. The purpose of this study was to develop and test two methods for automatically tracking fascicle orientation. Images were initially filtered using a multiscale vessel enhancement (a technique used to enhance tube-like structures), and then fascicle orientations quantified using either the Radon transform or wavelet analysis. Tests on synthetic images showed that these methods could identify fascicular orientation with errors of less than 0.06 degrees . Manual digitization of muscle fascicles during a dynamic contraction resulted in a standard deviation of angle estimates of 1.41 degrees across ten researchers. The Radon transform predicted fascicle orientations that were not significantly different from the manually digitized values, whilst the wavelet analysis resulted in angles that were 1.35 degrees less, and reasons for these differences are discussed. The Radon transform can be used to identify the dominant fascicular orientation within an image, and thus used to estimate muscle fascicle lengths. The wavelet analysis additionally provides information on the local fascicle orientations and can be used to quantify fascicle curvatures and regional differences with fascicle orientation across an image.

Mesh:

Year:  2009        PMID: 19646699     DOI: 10.1016/j.jbiomech.2009.06.003

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  26 in total

1.  Lower Limb Motion Estimation Using Ultrasound Imaging: A Framework for Assistive Device Control.

Authors:  Mohammad Hassan Jahanandish; Nicholas P Fey; Kenneth Hoyt
Journal:  IEEE J Biomed Health Inform       Date:  2019-01-09       Impact factor: 5.772

2.  3D curvature of muscle fascicles in triceps surae.

Authors:  Manku Rana; Ghassan Hamarneh; James M Wakeling
Journal:  J Appl Physiol (1985)       Date:  2014-10-16

3.  A computational approach to calculate personalized pennation angle based on MRI: effect on motion analysis.

Authors:  Andra Chincisan; Karelia Tecante; Matthias Becker; Nadia Magnenat-Thalmann; Christof Hurschler; Hon Fai Choi
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-07-03       Impact factor: 2.924

4.  A semiautomatic method for in vivo three-dimensional quantitative analysis of fascial layers mobility based on 3D ultrasound scans.

Authors:  S Condino; G Turini; S Parrini; A Stecco; F Busoni; V Ferrari; M Ferrari; M Gesi
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-03-06       Impact factor: 2.924

5.  Prior-Apprised Unsupervised Learning of Subpixel Curvilinear Features in Low Signal/Noise Images.

Authors:  Shuhui Yin; Ming Tien; Haw Yang
Journal:  Biophys J       Date:  2020-04-19       Impact factor: 4.033

6.  Reliability of a semi-automated algorithm for the vastus lateralis muscle architecture measurement based on ultrasound images.

Authors:  Robert Marzilger; Kirsten Legerlotz; Chrystalla Panteli; Sebastian Bohm; Adamantios Arampatzis
Journal:  Eur J Appl Physiol       Date:  2017-12-06       Impact factor: 3.078

7.  Imaging transverse isotropic properties of muscle by monitoring acoustic radiation force induced shear waves using a 2-D matrix ultrasound array.

Authors:  Michael Wang; Brett Byram; Mark Palmeri; Ned Rouze; Kathryn Nightingale
Journal:  IEEE Trans Med Imaging       Date:  2013-05-14       Impact factor: 10.048

8.  Estimating skeletal muscle fascicle curvature from B-mode ultrasound image sequences.

Authors:  John Darby; Baihua Li; Nicholas Costen; Ian Loram; Emma Hodson-Tole
Journal:  IEEE Trans Biomed Eng       Date:  2013-02-06       Impact factor: 4.538

9.  Transperineal Sonography Evaluation of Muscles and Vascularity in the Male Pelvic Floor.

Authors:  Shawn C Roll; Jason J Kutch
Journal:  J Diagn Med Sonogr       Date:  2013-01

10.  Automatic thickness estimation for skeletal muscle in ultrasonography: evaluation of two enhancement methods.

Authors:  Pan Han; Ye Chen; Lijuan Ao; Gaosheng Xie; Huihui Li; Lei Wang; Yongjin Zhou
Journal:  Biomed Eng Online       Date:  2013-01-22       Impact factor: 2.819

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