A new denoising technique in magnetic resonance electrical impedance tomography

In this paper, we propose a new denoising technique in magnetic resonance electrical impedance tomography (MREIT). MREIT is a new biomedical image modality, which can provide high resolution cross-sectional conductivity images of an electrically conducting object robustly. In MREIT technique, the conductivity distribution can be reconstructed based on the measurement data of the internal magnetic flux density, which is induced by an externally injected current through a pair of surface electrodes. The harmonic B_z algorithm is a well-known image reconstruction algorithm in MREIT, and its effective application relies on the stable computation of the Laplacian operation of the measurement data. Hence, a denoising technique is necessary in order to eliminate the noise in the measurement data and compute its Laplacian operation stably. Based on the mollification method, a new denoising technique is proposed. Its efficiency is shown by a numerical experiment finally.