ESTIMATION OF THE SIZE OF STRUCTURAL FORMATIONS IN ULTRASOUND IMAGING THROUGH STATISTICAL ANALYSIS OF THE ECHO SIGNAL

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Abstract

The paper considers a fundamentally new approach to solving the problem of determining the size of structural formations in ultrasonic diagnostics, based on the theoretically justified possibility of estimating the size of inhomogeneities of the studied medium by analyzing the statistical characteristics of the ultrasonic signal scattered on these inhomogeneities. This possibility is conditioned by the fact that the statistical distribution of the ultrasound image data varies from Rayleigh distribution to Reiss 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, which will effectively detect a significant coherent component in the echo signal and thereby be used as a mathematical tool to estimate the size of medium inhomogeneities in ultrasound imaging. Such approach to the analysis of ultrasound images would provide a possibility of quantitative estimation of structural formations and thereby would increase significantly the information value of ultrasound diagnostics and possibility of pathology detection at early stages of its formation that opens perspectives for treatment efficiency increase.

About the authors

T. V. Yakovleva

Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences

Author for correspondence.
Email: tan-ya@bk.ru
Russian Federation, Moscow

N. S. Kulberg

Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences

Email: tan-ya@bk.ru
Russian Federation, Moscow

D. V. Leonov

Moscow Center for Diagnostics and Telemedicine, MPEI

Email: tan-ya@bk.ru
Russian Federation, Moscow

References

  1. Rice S.O. Mathematical Analysis of Random Noise // Bell Syst. Tech. Journal. 1944. V. 23. P. 282–322.
  2. Cai R. Statistical Characterization of the Medical Ultrasound Echo Signals. Sci Rep. 2016. V. 6. P. 39379.
  3. Parker K.J. Shapes and distributions of soft tissue scatterers. Physics in Medicine and Biology. Volume 64, Issue 17, 5 September 2019, article number 175022.
  4. Mohana Shankar P. A general statistical model for ultrasonic backscattering from tissues // IEEE Trans Ultrason Ferroelectr Freq Control. 2000. V. 47. № 3. P. 727–36. https://doi.org/10.1109/58.842062
  5. Martínez-Graullera O., Yagüe-Jiménez V., Romero M. P. and Ibáñez Rodríguez A. Improving ultrasonic medical image quality by attenuation of the secondary lobes // IEEE International Ultrasonics Symposium. 2019. P. 1286–1289. https://doi.org/10.1109/ULTSYM.2019.8926260
  6. Physical Principles of Medical Ultrasonics, 2nd ed, C.R. Hill (Editor), J.C. Bamber (Editor), G.R. ter Haar (Editor), ISBN: 978-0-471-97002-6, 2004, 528 P.
  7. Yakovleva T.V., Kulberg N.S. Noise and Signal Estimation in MRI: Two-Parametric Analysis of Rice-Distributed Data by Means of the Maximum Likelihood Approach. American Journal of Theoretical and Applied Statistics. 1013. V. 2. № 3. P. 67–79.
  8. Яковлева Т.В. Теоретическое обоснование математических методов совместного оценивания параметров сигнала и шума при анализе райсовских данных // Компьютерные исследования и моделирование. 2016. Т. 8. № 3. С. 445–473.https://doi.org/10.20537/2076-7633-2016-8-3-445-473
  9. Яковлева Т.В., Кульберг Н.С. Методы математической статистики как инструмент двухпараметрического анализа магнитно-резонансного изображения // Информатика и ее применения. 2014. Т. 8. Вып. 3. С. 79–89.
  10. Yakovleva T. Peculiarities of the Rice Statistical Distribution: Mathematical Substantiation // Applied and Computational Mathematics. 2018. V. 7. № 4. P. 188–196. Science Publishing Group. https://doi.org/10.11648/j.acm.20180704.12
  11. Vetsheva N.N., Reshetnikov R.V., Leonov D.V., Kulberg N.S., Mokienko O.A. Diagnostic value of lung ultrasound in COVID-19: systematic review and meta-analysis // Digital Diagnostics. 2020. V. 1. № 1. P. 13–26. https://doi.org/10.17816/DD46834

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Copyright (c) 2023 Т.В. Яковлева, Н.С. Кульберг, Д.В. Леонов