Muscle Composition Analysis of Ultrasound Images: A Narrative Review of Texture Analysis.

Autor:	Paris MT; Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada. Electronic address: m2paris@uwaterloo.ca., Mourtzakis M; Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada.
Jazyk:	angličtina
Zdroj:	Ultrasound in medicine & biology [Ultrasound Med Biol] 2021 Apr; Vol. 47 (4), pp. 880-895. Date of Electronic Publication: 2021 Jan 13.
DOI:	10.1016/j.ultrasmedbio.2020.12.012
Abstrakt:	Skeletal muscle composition, often characterized by the degree of intramuscular adipose tissue, deteriorates with aging and disease and contributes to impairments in function and metabolism. Ultrasound can provide surrogate measures of muscle composition through measurement of echo intensity; however, there are several limitations associated with its analysis. More complex image processing features, broadly known as texture analysis, can also provide surrogates of muscle composition and may circumvent some of the limitations associated with muscle echo intensity. Here, texture features from the intensity histogram, gray-level co-occurrence matrix, run-length matrix, local binary pattern, blob analysis, texture anisotropy index and wavelet analysis are discussed. The purpose of this review was to provide a conceptual understanding of texture analysis as it pertains to muscle composition of ultrasound images. Competing Interests: Conflict of interests disclosure The authors declare no conflicts of interests. (Copyright © 2020 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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