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JOURNALS // Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia // Archive

Dokl. RAN. Math. Inf. Proc. Upr., 2023 Volume 509, Pages 87–93 (Mi danma367)

This article is cited in 1 paper

MATHEMATICS

Estimation of the size of structural formations in ultrasound imaging through statistical analysis of the echo signal

T. V. Yakovlevaa, N. S. Kulberga, D. V. Leonovb

a Federal Research Center "Computer Science and Control", Russian Academy of Sciences, Moscow, Russia
b Scientific and Practical Clinical Center for Diagnostics and Telemedicine Technologies, Moscow Department of Health, 127051, Moscow, Russia

Abstract: A fundamentally new approach to solving the problem of determining the size of structural formations in ultrasonic diagnostics is considered. The approach is based on the theoretically justified possibility of estimating the size of inhomogeneities of the studied medium by analyzing the statistical characteristics of an ultrasonic signal scattered on these inhomogeneities. This possibility is conditioned by the fact that the statistical distribution of ultrasound image data varies from Rayleigh distribution to Rice distribution depending on the relation between the coherence area size of the scattered signal and the beamwidth. The work aims at the development of a new method of statistical data analysis that will effectively detect a significant coherent component in the echo signal, thereby providing a mathematical tool for estimating the size of medium inhomogeneities in ultrasound imaging. This approach to ultrasound image analysis would provide the possibility of quantitative estimation of structural formations, which would lead to a significant increase in the information value of ultrasound diagnostics, and the possibility of early pathology detection, opening perspectives for an increase in treatment effectiveness.

Keywords: scattering, tissue differentiation, Rayleigh, Rice, ultrasonic diagnostics.

UDC: 534.141

Presented: Yu. G. Evtushenko
Received: 06.12.2022
Revised: 16.12.2022
Accepted: 20.12.2022

DOI: 10.31857/S2686954322600744


 English version:
Doklady Mathematics, 2023, 107:1, 72–76

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© Steklov Math. Inst. of RAS, 2026