Conductivity and current density image reconstruction using harmonic Bz algorithm in magnetic resonance electrical impedence tomography

Suk Hoon Oh, Byung Il Lee, Eung Je Woo, Soo Yeol Lee, Min Hyoung Cho, Ohin Kwon, Jin Keun Seo

Research output: Contribution to journalArticlepeer-review

171 Citations (Scopus)


Magnetic resonance electrical impedance tomography (MREIT) is to provide cross-sectional images of the conductivity distribution σ of a subject. While injecting current into the subject, we measure one component Bz of the induced magnetic flux density B = (Bx, By, Bz,) using an MRI scanner. Based on the relation between ∇2Bz and ∇σ, the harmonic Bz algorithm reconstructs an image of σ using the measured Bz data from multiple imaging slices. After we obtain σ, we can reconstruct images of current density distributions for any given current injection method. Following the description of the harmonic Bz algorithm, this paper presents reconstructed conductivity and current density images from computer simulations and phantom experiments using four recessed electrodes injecting six different currents of 26 mA. For experimental results, we used a three-dimensional saline phantom with two polyacrylamide objects inside. We used our 0.3 T (tesla) experimental MRI scanner to measure the induced Bz. Using the harmonic Bz algorithm, we could reconstruct conductivity and current density images with 82 × 82 pixels. The pixel size was 0.6 × 0.6 mm2. The relative L2 errors of the reconstructed images were between 13.8 and 21.5% when the signal-to-noise ratio (SNR) of the corresponding MR magnitude images was about 30. The results suggest that in vitro and in vivo experimental studies with animal subjects are feasible. Further studies are requested to reduce the amount of injection current down to less than 1 mA for human subjects.

Original languageEnglish
Pages (from-to)3101-3116
Number of pages16
JournalPhysics in medicine and biology
Issue number19
Publication statusPublished - 2003 Oct 7

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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