Conductivity image reconstruction for two-dimensional MREIT model based on Matlab PDE-tool
Magnetic resonance electrical impedance tomography (MREIT) is to provide cross-sectional images of the conductivity distribution of a subject. However, the MREIT model at its early stage has technique difficulties in clinical applications mainly due to the requirement of subject rotations for obtaining all of the three components of the induced magnetic flux density. Lately, a new MREIT algorithm so called the harmonic-Bz algorithm has been proposed. In this new algorithm, we need to measure only one of component of the magnetic flux density to reconstruct the conductivity images without subject rotation. After introducing the harmonic-Bz algorithm in MREIT, this paper presents an image reconstruction technique based on Matlab PDE-tool and the Moore-Penrose pseudo inverse method in two dimensional case. Numerical simulations with added white Gaussian random noise confirmed its ability to reconstruct the conductivity images in MREIT.