Conductivity and permittivity image reconstruction at the larmor frequency using MRI

Yizhuang Song, Jin Keun Seo

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


This paper presents a new method of providing both conductivity (θ) and permittivity (-) images at the MR Larmor frequency in magnetic resonance electrical property tomography (MREPT), a relatively new MR-based electrical tissue property imaging modality. In MREPT, the RF coil of the MR scanner is used to feed a sinusoidal current at the Larmor frequency, ε/2π (approximately 128 MHz for a 3 Tesla MRI machine), to an imaging object within the MR scanner. Inside the object, this injection current induces a time-harmonic magnetic field, H = (Hx,Hy,Hz), that is influenced by the body's admittivity distribution, δ = θ + iε, via Maxwell's equations. Currently, the positive rotating field, H + = (Hx + iHy)/2, is the only measurable quantity which can be obtained from B1 mapping techniques. The inverse problem of MREPT is to reconstruct δ from the H+ data. Existing MREPT reconstruction methods use the local homogeneity assumption (δ = 0) to simplify the relation between δ and H+, so that the admittivity is proportional to the ratio of the Laplacian 2H+ to H+. However, the conventional reconstruction method based on this local homogeneity assumption gives rise to serious reconstruction errors at large |δ||δ|. Hence, the major issue in MREPT is to find a reconstruction formula without assuming the local homogeneity condition. The proposed method removes the assumption of ( θ θx δ, θ θy δ) = 0 (but still requires θ θz δ ? 0). We have found an exact relation between δ and H+, so that δ is a solution of a semilinear elliptic PDE with coefficients depending only upon H+. Numerical simulations show that the proposed method successfully reconstructs discontinuous admittivities.

Original languageEnglish
Pages (from-to)2262-2280
Number of pages19
JournalSIAM Journal on Applied Mathematics
Issue number6
Publication statusPublished - 2013

All Science Journal Classification (ASJC) codes

  • Applied Mathematics


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