Diagnostic Mode Detecting Solid Mineral Inclusions in Medical Ultrasound Imaging
- Authors: Leonov D.V.1,2, Kulberg N.S.1,3, Gromov A.I.4, Morozov S.P.1, Vladzimirskiy A.V.1
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Affiliations:
- Research and Practical Center of Medical Radiology, Moscow Healthcare Department
- Moscow Power Engineering Institute
- Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
- A.I. Yevdokimov Moscow State University of Medicine and Dentistry of the Ministry of Healthcare of the Russian Federation
- Issue: Vol 64, No 5 (2018)
- Pages: 624-636
- Section: Physical Foundations of Technical Acoustics
- URL: https://journals.rcsi.science/1063-7710/article/view/186691
- DOI: https://doi.org/10.1134/S1063771018050068
- ID: 186691
Cite item
Abstract
The proposed ultrasound imaging mode allows detection of objects, which essentially differ in their scattering properties from the surrounding tissues and liquids. The objects in question are primarily microcalcifications, renal and urinary stones. Our previous study has shown that the Doppler signals from these objects have two components common for echoes from solid mineral inclusions. They can be in superposition with the blood and noise signals. One of these two mineral-related components is characterized by cavitation, the other – by elastic vibrations of the object presumably caused by acoustic radiation force. According to statistical and energy parameters, these components differ from each other, as well as from noise and blood echoes. The article proposes a practical method for identifying signals with mineral-related components. This method is the base for the novel diagnostic visualization mode specifically designed for the mineral inclusions detection with ultrasound.
About the authors
D. V. Leonov
Research and Practical Center of Medical Radiology, Moscow Healthcare Department; Moscow Power Engineering Institute
Author for correspondence.
Email: LeonovDV@mpei.ru
Russian Federation, Moscow, 109029; Moscow, 111250
N. S. Kulberg
Research and Practical Center of Medical Radiology, Moscow Healthcare Department; Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Author for correspondence.
Email: Kulberg@yandex.ru
Russian Federation, Moscow, 109029; Moscow, 119333
A. I. Gromov
A.I. Yevdokimov Moscow State University of Medicine and Dentistry of the Ministry of Healthcare of the Russian Federation
Email: Kulberg@yandex.ru
Russian Federation, Moscow, 127206
S. P. Morozov
Research and Practical Center of Medical Radiology, Moscow Healthcare Department
Email: Kulberg@yandex.ru
Russian Federation, Moscow, 109029
A. V. Vladzimirskiy
Research and Practical Center of Medical Radiology, Moscow Healthcare Department
Email: Kulberg@yandex.ru
Russian Federation, Moscow, 109029
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