Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement

Nuo Gao, S. A. Zhu, Bin He

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

Abstract

We have developed a new algorithm for magnetic resonance electrical impedance tomography (MREIT), which uses only one component of the magnetic flux density to reconstruct the electrical conductivity distribution within the body. The radial basis function (RBF) network and simplex method are used in the present approach to estimate the conductivity distribution by minimizing the errors between the 'measured' and model-predicted magnetic flux densities. Computer simulations were conducted in a realistic-geometry head model to test the feasibility of the proposed approach. Single-variable and three-variable simulations were performed to estimate the brain-skull conductivity ratio and the conductivity values of the brain, skull and scalp layers. When SNR = 15 for magnetic flux density measurements with the target skull-to-brain conductivity ratio being 1/15, the relative error (RE) between the target and estimated conductivity was 0.0737 ± 0.0746 in the single-variable simulations. In the three-variable simulations, the RE was 0.1676 ± 0.0317. Effects of electrode position uncertainty were also assessed by computer simulations. The present promising results suggest the feasibility of estimating important conductivity values within the head from noninvasive magnetic flux density measurements.

Original languageEnglish (US)
Pages (from-to)2675-2687
Number of pages13
JournalPhysics in Medicine and Biology
Volume50
Issue number11
DOIs
StatePublished - Jun 7 2005

Fingerprint

Dive into the research topics of 'Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement'. Together they form a unique fingerprint.

Cite this