Literature DB >> 34852623

Statistical modeling of ultrasound signals related to the packing factor of wave scattering phenomena for structural characterization.

François Destrempes1, Guy Cloutier1.   

Abstract

The two-dimensional homodyned K-distribution has been widely used to model the echo envelope of ultrasound radio frequency (RF) signals in the field of medical ultrasonics. The main contribution of this work is to present a theoretical framework for supporting this model of the echo envelope and statistical models of the RF signals and their Hilbert transform in the case in which the scatterers' positions may be dependent. In doing so, the law of large numbers, Lyapounov's central limit theorem, and the Berry-Esseen theorem are being used. In particular, the proposed theoretical framework supports a previous conjecture relating the scatterer clustering parameter of the homodyned K-distribution to the packing factor W, which is related to the spatial organization of the scatterers, appearing in statistical physics or backscatter coefficient modeling. Simulations showed that the proposed modeling is valid for a number of scatterers and packing factors varying by steps of 2 from 1 to 21 and 1 to 11, respectively. The proposed framework allows, in principle, the detection of the structural information taking place at a scale smaller than the wavelength based solely on the statistical analysis of the RF signals or their echo envelope, although this goal was previously achieved based on the spectral analysis of ultrasound signals.

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Year:  2021        PMID: 34852623     DOI: 10.1121/10.0007047

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  2 in total

Review 1.  Power laws prevail in medical ultrasound.

Authors:  K J Parker
Journal:  Phys Med Biol       Date:  2022-04-20       Impact factor: 4.174

2.  Imaging the Effects of Whole-Body Vibration on the Progression of Hepatic Steatosis by Quantitative Ultrasound Based on Backscatter Envelope Statistics.

Authors:  Jui Fang; Ming-Wei Lai; Hao-Tsai Cheng; Anca Cristea; Zhuhuang Zhou; Po-Hsiang Tsui
Journal:  Pharmaceutics       Date:  2022-03-29       Impact factor: 6.525

  2 in total

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