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Detailed Analytical Approach to Solve the Magnetoacoustic Tomography with Magnetic Induction (MAT-MI) Problem for Three-Layer Objects

Author

Listed:
  • Adam Ryszard Zywica

    (Department of Electrical and Computer Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, Poland)

  • Marcin Ziolkowski

    (Department of Electrical and Computer Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, Poland)

  • Stanislaw Gratkowski

    (Department of Electrical and Computer Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, 70-310 Szczecin, Poland)

Abstract

This paper is devoted to an analytical approach to the magnetoacoustic tomography with magnetic induction (MAT-MI) problem for three-layer low-conductivity objects. For each layer, we determined closed-form analytical expressions for the eddy current density and Lorentz force vectors based on the separation of variables method. Next, the analytical formulas were validated with numerical solutions obtained with the help of the finite element method (FEM). Based on the acoustic dipole radiation theory, the influence of the transducer reception pattern on MAT-MI was investigated. To obtain acoustic wave patterns, as a system transfer function we proposed the Morlet wavelet. Finally, image reconstruction examples for objects of more complex shapes are presented, and the influence of the MAT-MI scanning resolution and the presence of the noise on the image reconstruction quality was studied in detail.

Suggested Citation

  • Adam Ryszard Zywica & Marcin Ziolkowski & Stanislaw Gratkowski, 2020. "Detailed Analytical Approach to Solve the Magnetoacoustic Tomography with Magnetic Induction (MAT-MI) Problem for Three-Layer Objects," Energies, MDPI, vol. 13(24), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:24:p:6515-:d:459715
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    Cited by:

    1. Bartosz Przysucha & Dariusz Wójcik & Tomasz Rymarczyk & Krzysztof Król & Edward Kozłowski & Marcin Gąsior, 2023. "Analysis of Reconstruction Energy Efficiency in EIT and ECT 3D Tomography Based on Elastic Net," Energies, MDPI, vol. 16(3), pages 1-22, February.
    2. Dariusz Wójcik & Tomasz Rymarczyk & Bartosz Przysucha & Michał Gołąbek & Dariusz Majerek & Tomasz Warowny & Manuchehr Soleimani, 2023. "Energy Reduction with Super-Resolution Convolutional Neural Network for Ultrasound Tomography," Energies, MDPI, vol. 16(3), pages 1-14, January.

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