• DocumentCode
    743867
  • Title

    Magneto-Acousto-Electrical Tomography With Magnetic Induction for Conductivity Reconstruction

  • Author

    Liang Guo ; Guoqiang Liu ; Hui Xia

  • Author_Institution
    Instn. of Electr. Eng., Univ. of Chinese Acad. of Sci., Beijing, China
  • Volume
    62
  • Issue
    9
  • fYear
    2015
  • Firstpage
    2114
  • Lastpage
    2124
  • Abstract
    Magneto-acousto-electrical tomography (MAET) is an imaging modality proposed to conduct noninvasive electrical conductivity imaging of biological tissue with high spatial resolution. In this study, we present a method of MAET in coil detection mode, which is named as magneto-acousto-electrical tomography with magnetic induction (MAET-MI). Based on the analysis of the mechanism of MAET-MI, we derive a reciprocal theorem and give an integral equation for computing the induced voltage of the coil. The forward problem of MAET-MI can be solved by this integral equation. In the inverse problem of MAET-MI, two steps are taken to reconstruct the conductivity. The first step is to reconstruct the curl of the eddy current density in the reciprocal process by the compression sensing method. And then the conductivity is recovered by the iterative methods such as the Levenberg-Marquardt algorithm. Both the mechanism of MAET-MI and the reconstruction of conductivity are verified by computer simulations. We have also conducted the phantom experiments. The reconstructed images are approximately consistent with the phantom´s conductivity. The imaging results prove the ability and the reliability of our proposed methods. It is shown that the relative conductivity distribution can be reconstructed with our proposed reciprocal theorem in MAET-MI modality. Comparing with the traditional MAET, The MAET-MI modality would benefit from the noncontact measurement and be convenient for clinical application.
  • Keywords
    acoustic tomography; bioelectric phenomena; biological tissues; biomagnetism; compressed sensing; current density; eddy currents; electric field integral equations; electric impedance imaging; electrical conductivity; electromagnetic induction; image reconstruction; image resolution; inverse problems; magnetic field integral equations; magnetoacoustic effects; magnetoelectric effects; medical image processing; phantoms; Levenberg-Marquardt algorithm; MAET-MI modality; biological tissue; clinical application; coil detection mode; compression sensing method; computer simulations; conductivity reconstruction; eddy current density; high spatial resolution; imaging modality; integral equation; inverse problem; magnetic induction; magneto-acousto-electrical tomography; noncontact measurement; noninvasive electrical conductivity imaging; phantom conductivity; phantom experiments; reciprocal theorem; reconstructed images; relative conductivity distribution; Coils; Conductivity; Image reconstruction; Magnetic fields; Magnetic resonance imaging; Ultrasonic imaging; Vectors; Compression sensing (CS) method; Conductivity reconstructing, CS method; Magnetic induction; Magneto-acousto-electrical tomography; Reciprocal theorem; conductivity reconstructing; magnetic induction; magneto-acousto-electrical tomography (MAET); reciprocal theorem;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2014.2382562
  • Filename
    6990545