Analysis of reconstruction performance of magnetic resonance conductivity tensor imaging (MRCTI) using simulated measurements

Magnetic resonance conductivity tensor imaging (MRCTI) was proposed recently to produce electrical conductivity images of anisotropic tissues. Similar to magnetic resonance electrical impedance tomography (MREIT), MRCTI uses magnetic field and boundary potential measurements obtained utilizing magnetic resonance imaging techniques. MRCTI reconstructs tensor images of anisotropic conductivity whereas MREIT reconstructs isotropic conductivity images. In this study, spatial resolution and linearity of five recently proposed MRCTI algorithms are evaluated using simulated measurements gathered from three different computer models. The results show that all five algorithms have quite similar reconstruction performances. Since the AB$_{z}$S algorithm is easier to apply compared to the other four algorithms it can be said to be the best algorithm among the five algorithms.