Application of Artificial Intelligence to Automate the Reconstruction of Muscle Cross-Sectional Area Obtained by Ultrasound.

Journal: Medicine and science in sports and exercise
PMID: 38637954

Abstract

PURPOSE: Manual reconstruction (MR) of the vastus lateralis (VL) muscle cross-sectional area (CSA) from sequential ultrasound (US) images is accessible, is reproducible, and has concurrent validity with magnetic resonance imaging. However, this technique requires numerous controls and procedures during image acquisition and reconstruction, making it laborious and time-consuming. The aim of this study was to determine the concurrent validity of VL CSA assessments between MR and computer vision-based automated reconstruction (AR) of CSA from sequential images of the VL obtained by US.

Authors

  • Deivid Gomes DA Silva
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Diego Gomes DA Silva
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Vitor Angleri
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Maíra Camargo Scarpelli
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • João Guilherme Almeida Bergamasco
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Sanmy Rocha Nóbrega
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Felipe Damas
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Talisson Santos Chaves
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Heloisa DE Arruda Camargo
    Department of Computer Science, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.
  • Carlos Ugrinowitsch
  • Cleiton Augusto Libardi
    MUSCULAB-Laboratory of Neuromuscular Adaptations to Resistance Training, Department of Physical Education, Federal University of São Carlos (UFSCar), São Carlos, BRAZIL.

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