Simple Muscle Architecture Analysis

Simple Muscle Architecture Analysis automates measurement of muscle fascicle and aponeurosis geometry from B-mode ultrasound images to quantify in vivo muscle architecture for research and clinical assessment.


Key Features:

  • Implementation: Implemented as an ImageJ macro that operates on B-mode ultrasound scans.
  • Automation: Automates measurement of muscle architecture parameters, reducing manual annotation steps.
  • Image Processing: Applies spatial and frequency-domain filtering using built-in ImageJ commands and external plugins to enhance visibility of aponeuroses and fascicles.
  • Orientation Analysis: Uses the OrientationJ plugin to compute the dominant orientation of muscle fascicles within defined regions of interest.
  • Quantitative Outputs: Produces measurements of fascicle orientation and aponeurosis geometry for subsequent analysis.
  • Validation: Assesses agreement with manual methods using Bland-Altman plots to evaluate systematic bias.

Scientific Applications:

  • Superficial muscle ultrasound analysis: Analysis of B-mode images of superficial muscles to extract architectural parameters.
  • Muscle plasticity studies: Quantification of fascicle and aponeurosis changes in studies of muscle adaptation and plasticity.
  • Rehabilitation and clinical assessment: Objective measurement of muscle architecture for evaluating rehabilitation outcomes and clinical diagnostics.

Methodology:

Implemented as an ImageJ macro that performs spatial and frequency-domain filtering via built-in commands and external plugins, computes dominant fascicle orientation with OrientationJ in regions of interest, and evaluates agreement with manual measurements using Bland-Altman plots.

Topics

Details

Added:
1/18/2021
Last Updated:
2/19/2021

Operations

Publications

Seynnes OR, Cronin NJ. Simple Muscle Architecture Analysis (SMA): An ImageJ macro tool to automate measurements in B-mode ultrasound scans. PLOS ONE. 2020;15(2):e0229034. doi:10.1371/journal.pone.0229034. PMID:32049973. PMCID:PMC7015391.