Automated measurements of morphological parameters of muscles and tendons

Shaima Ibraheem Jabbar*, Charles Day, Edward Chadwick

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Capturing accurate representations of musculoskeletal system morphology is a core aspect of musculoskeletal modelling of the upper limb. Measurements of important geometric parameters such as the thickness of muscles and tendons are key descriptors of the underlying morphology. Though the measurement of those parameters can be estimated manually using cadaveric measurements, this is not an appropriate technique for constructing a personalised musculoskeletal model for an individual. Therefore, this work proposes and applies a novel method for evaluating the geometric parameters of the upper extremity based on automated ultrasound image analysis. The proposed algorithm involves advanced techniques from artificial intelligence and image processing to outline the necessary details of the musculoskeletal morphology from appropriately enhanced ultrasound images. The ultrasound images were collected from 25 healthy volunteers from different parts of upper limb. The results were compared with measurements of a manual evaluation. Our results showed that the average discrepancy between the manual and automatic measures of triceps thickness is 0.115 mm. This represents improved accuracy compared to several current approaches.

Original languageEnglish
Article number025002
JournalBiomedical Physics and Engineering Express
Volume7
Issue number2
DOIs
Publication statusPublished - 6 Jan 2021

Keywords

  • Bland-Altman method
  • Fuzzy inference technique
  • Muscle thickness
  • Tendon thickness
  • Ultrasound images

Fingerprint

Dive into the research topics of 'Automated measurements of morphological parameters of muscles and tendons'. Together they form a unique fingerprint.

Cite this