Author
Listed:
- Maxim Shishlenin
(Institute of Computational Mathematics and Mathematical Geophysics, 630090 Novosibirsk, Russia
Sobolev Institute of Mathematics, 630090 Novosibirsk, Russia
These authors contributed equally to this work.)
- Andrey Kozelkov
(Russian Federal Nuclear Center, All-Russian Research Institute of Experimental Physics, 607188 Sarov, Russia
Nizhny Novgorod State Technical University n.a. R.E. Alekseev, 603155 Nizhny Novgorod, Russia
Sarov Institute of Physics and Technology—Branch of the National Research Nuclear University “MEPHI”, 607186 Sarov, Russia
These authors contributed equally to this work.)
- Nikita Novikov
(Institute of Computational Mathematics and Mathematical Geophysics, 630090 Novosibirsk, Russia
Sobolev Institute of Mathematics, 630090 Novosibirsk, Russia
These authors contributed equally to this work.)
Abstract
The article aimed to show the fundamental possibility of constructing a computational digital twin of the acoustic tomograph within the framework of a unified physics–mathematical model based on the Navier–Stokes equations. The authors suggested that the size of the modeling area is quite small, sound waves are waves of “small” disturbance, and given that a person consists of more than 60% water, human organs can be modeled using a liquid model, taking into account their density. During numerical experiments, we obtained the pressure registered in the receivers that are located on the side walls of the tomograph. The differences in pressure values are shown depending on the configuration of inclusions in the mannequin imitating internal organs. The results show that the developed technology can be used to probe the human body in medical acoustic tomographs and determine the acoustic parameters of the human body to detect neoplasms.
Suggested Citation
Maxim Shishlenin & Andrey Kozelkov & Nikita Novikov, 2024.
"Nonlinear Medical Ultrasound Tomography: 3D Modeling of Sound Wave Propagation in Human Tissues,"
Mathematics, MDPI, vol. 12(2), pages 1-14, January.
Handle:
RePEc:gam:jmathe:v:12:y:2024:i:2:p:212-:d:1315440
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