A novel strategy for the visualization of cross-sectional skeletal muscle contraction

Jizhou Li, Yongjin Zhou, Andong Wang, Lei Wang, Yongping Zheng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In recent years, ultrasound imaging have been widely used to assess human muscle. Quantitative ultrasound can provide objective information about muscle architectures and changes of motion pattern during muscle contraction. However, there are few reports about the visualization of cross-sectional skeletal muscle motion using descriptive color coding strategy. In this study, ultrasound images were recorded from right quadriceps femoris muscle during isometric knee extension, and a motion estimation method based on a theory for warping was used to compute morphological changes of muscle during contraction. Then a novel color coding strategy, which agrees with the established directing rules in medical imaging, was applied to present the motion field. In comparison with the traditional color coding method, the new strategy was more capable of providing detailed information about the velocity and morphological changes in different region of muscle intuitively. The proposed approach has the potential to be applied for the functional understanding and segmentation of various muscle sections.
Original languageEnglish
Title of host publication2013 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2013
DOIs
Publication statusPublished - 1 Dec 2013
Event2013 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2013 - Kunming, Yunnan, China
Duration: 5 Aug 20138 Aug 2013

Conference

Conference2013 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2013
Country/TerritoryChina
CityKunming, Yunnan
Period5/08/138/08/13

Keywords

  • Motion estimation
  • Quadriceps femoris muscle
  • Ultrasound

ASJC Scopus subject areas

  • Signal Processing

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