MREIT conductivity imaging based on the local harmonic Bz algorithm: Animal experiments

Abstract

From numerous numerical and phantom experiments, MREIT conductivity imaging based on harmonic Bz algorithm shows that it could be yet another useful medical imaging modality. However, in animal experiments, the conventional harmonic Bz algorithm gives poor results near boundaries of problematic regions such as bones, lungs, and gas-filled stomach, and the subject boundary where electrodes are not attached. Since the amount of injected current is low enough for the safety for in vivo animal, the measured Bz data is defected by severe noise. In order to handle such problems, we use the recently developed local harmonic Bz algorithm to obtain conductivity images in our ROI(region of interest) without concerning the defected regions. Furthermore we adopt a denoising algorithm that preserves the ramp structure of Bz data, which informs of the location and size of anomaly. Incorporating these efficient techniques, we provide the conductivity imaging of post-mortem and in vivo animal experiments with high spatial resolution.