Imaging electrical impedance from acoustic measurements by means of magnetoacoustic tomography with magnetic induction (MAT-MI)

Xu Li, Yuan Xu, Bin He

Research output: Contribution to journalArticlepeer-review

101 Scopus citations


We have conducted computer simulation and experimental studies on magnetoacoustic-tomography with magnetic induction (MAT-MI) for electrical impedance imaging. In MAT-MI, the object to be imaged is placed in a static magnetic field, while pulsed magnetic stimulation is applied in order to induce eddy current in the object. In the static magnetic field, the Lorentz force acts upon the eddy current and causes acoustic vibrations in the object. The propagated acoustic wave is then measured around the object to reconstruct the electrical impedance distribution. In the present simulation study, a two-layer spherical model is used. Parameters of the model such as sample size, conductivity values, strength of the static and pulsed magnetic field, are set to simulate features of biological tissue samples and feasible experimental constraints. In the forward simulation, the electrical potential and current density are solved using Poisson's equation, and the acoustic pressure is calculated as the forward solution. The electrical impedance distribution is then reconstructed from the simulated pressure distribution surrounding the sample. The present computer simulation results suggest that MAT-MI can reconstruct conductivity images of biological tissue with high spatial resolution and high contrast. The feasibility of MAT-MI in providing high spatial resolution images containing impedance-related information has also been demonstrated in a phantom experiment.

Original languageEnglish (US)
Article number16
Pages (from-to)323-330
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Issue number2
StatePublished - Feb 2007

Bibliographical note

Funding Information:
Manuscript received July 20, 2005, and revised June 3, 2006. This work was supported in part by the National Institutes of Health (NIH) under Grant RO1EB00178, Grant NSF-BES-0411898, and Grant NSF-BES-0411480, and in part by the Biomedical Engineering Institute of the University of Minnesota. The work of X. Li was supported in part by NIH Neuro-Physical-Computational Sciences Fellowship 1R90 DK71500-01. Asterisk indicates corresponding author.


  • Bioimpedance imaging
  • Electrical impedance
  • Electrical impedance tomography
  • Magnetoacoustic tomography


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