Abstract
In this paper the recent Magnetic resonance electrical impedance imaging (MREIT) technique is used to image non-invasively the three-dimensional continuous conductivity distribution of the head tissues. With the feasibility of the human head being rotated twice in the magnetic resonance imaging (MRI) system, a continuous conductivity reconstruction MREIT algorithm based on two components of the measured magnetic flux density is introduced. The reconstructed conductivity image could be obtained through solving iter- atively a non-linear matrix equation. According to the present algorithm of using two magnetic flux den- sity components, numerical simulations were per- formed on a concentric three-sphere and realistic human head model (consisting of the scalp, skull and brain) with the uniform and non-uniform isotropic target conductivity distributions. Based on the algorithm, the reconstruction of scalp and brain conductivity ratios could be figured out even under the condition that only one current is injected into the brain. The present results show that the three-dimensional continuous conductivity reconstruction method with two magnetic flux density components for the realistic head could get better results than the method with only one magnetic flux density component. Given the skull conductivity ratio, the relative errors of scalp and brain conductivity values were reduced to less than 1% with the uniform conductivity distribution and less than 6.5% with the non-uniform distribution for different noise levels. Furthermore, the algorithm also shows fast convergence and improved robustness against noise.
Highlights
Knowledge of the electrical conductivity distribution in the human body is of great importance in many biomedical applications
A non-invasive Magnetic Resonance Electrical Impedance Tomography (MREIT) imaging modality has been developed to reconstruct high-resolution conductivity distribution images for the biological issues. In this new imaging modality, electrical impedance tomography (EIT) is combined with magnetic resonancecurrent density imaging (MR-CDI) techniques to solve the well-known ill-posedness of the image reconstruction problem in traditional EIT
In order to test the performance of the reconstruction algorithm using two magnetic flux density components, numerical simulations were performed on a concentric three-layer realistic human head model to estimate the continuous conductivity values σ =
Summary
Knowledge of the electrical conductivity distribution in the human body is of great importance in many biomedical applications. It has been proved that information about the vivo tissue conductivity values improves the solution accuracy of bioelectrical field problems [1]. A non-invasive Magnetic Resonance Electrical Impedance Tomography (MREIT) imaging modality has been developed to reconstruct high-resolution conductivity distribution images for the biological issues. In this new imaging modality, electrical impedance tomography (EIT) is combined with magnetic resonancecurrent density imaging (MR-CDI) techniques to solve the well-known ill-posedness of the image reconstruction problem in traditional EIT. Zhang [2] proposed an image reconstruction algorithm using internal current density and peripheral voltage measurement to reconstruct static conductivity images which initiated the development on the theory of MREIT
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