Conductivity Reconstruction of Human Head Tissues by Means of MREIT

Abstract

This paper focuses on the inhomogeneous conductivity reconstruction of human head tissues by means of magnetic resonance electrical impedance tomography (MREIT). MREIT is a recently introduced and non-invasive conductivity imaging modality that combines Current Density Imaging (CDI) and traditional Electrical Impedance Tomography (EIT) techniques. MREIT, designed to deal with the well-known ill-posed problem in traditional EIT, has been applied to reconstruct the conductivities of human head tissues. We have developed two realistic geometry finite element method (FEM) head models, with five tissues including the scalp, skull, CSF, gray matter and white matter, based on the hexahedral element and the tetrahedral element, respectively. The J-substitution MREIT algorithm is used in our simulation for its easy realization. The present simulation results show that the MREIT algorithm combined with the realistic geometry FEM head model can reconstruct the inhomogeneous human head tissue conductivity distributions with higher accuracy. Our work so far suggests that the proposed MREIT algorithms can provide useful conductivity information for solving the EEG/MEG forward/inverse problems, and for further investigations on human head tissues using MREIT.