Simple Muscle Architecture Analysis (SMA): An ImageJ macro tool to automate measurements in B-mode ultrasound scans

Abraham, Thomas, Seynnes, Olivier R. and Cronin, Neil ORCID: 0000-0002-5332-1188 (2020) Simple Muscle Architecture Analysis (SMA): An ImageJ macro tool to automate measurements in B-mode ultrasound scans. PLoS ONE, 15 (2). e0229034. doi:10.1371/journal.pone.0229034

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Abstract

In vivo measurements of muscle architecture (i.e. the spatial arrangement of muscle fascicles) are routinely included in research and clinical settings to monitor muscle structure, function and plasticity. However, in most cases such measurements are performed manually, and more reliable and time-efficient automated methods are either lacking completely, or are inaccessible to those without expertise in image analysis. In this work, we propose an ImageJ script to automate the entire analysis process of muscle architecture in ultrasound images: Simple Muscle Architecture Analysis (SMA). Images are filtered in the spatial and frequency domains with built-in commands and external plugins to highlight aponeuroses and fascicles. Fascicle dominant orientation is then computed in regions of interest using the OrientationJ plugin. Bland-Altman plots of analyses performed manually or with SMA indicate that the automated analysis does not induce any systematic bias and that both methods agree equally through the range of measurements. Our test results illustrate the suitability of SMA to analyse images from superficial muscles acquired with a broad range of ultrasound settings.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Simple Muscle Architecture Analysis (SMA); Ultrasound scans; REF2021
Subjects:	Q Science > QP Physiology R Medicine > RM Therapeutics. Pharmacology > RM695 Physical medicine. physical therapy including massage, exercise, occupational therapy, hydrotherapy, phototherapy, radiotherapy, thermotherapy, electrotherapy
Divisions:	Schools and Research Institutes > School of Education and Science
Research Priority Areas:	Health, Life Sciences, Sport and Wellbeing
Depositing User:	Rhiannon Goodland
Date Deposited:	21 Oct 2020 11:11
Last Modified:	31 Aug 2023 09:07
URI:	https://eprints.glos.ac.uk/id/eprint/8908

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