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Magneto-acousto-electrical tomography (MAET), a combination of ultrasoundimaging and electrical impedance tomography (EIT), offers both high resolution(in comparison to EIT) and high contrast (in comparison to ultrasound imaging).It is used to map the internal conductivity distribution of an imaging object.However, conductivity reconstruction in MAET is a challenge, so conventionalMAET is mainly devoted to mapping the conductivity interface. This is primarilybecause integration byparts is used in the theory derivation, and thesimplified measurement formula suggests the voltage is proportional to theconductivity gradient, which leads to an error in the measurement formula. Inthis study, the measurement signal is expressed as the convolution of acousticvelocity and conductivity distribution without using integration by parts,which retains the low-frequency term in the measurement signal. Based on theconvolution formula, we subsequently propose a direct conductivityreconstruction scheme with deconvolution by utilizing the low-frequencycomponent. We verify the proposed method based on two two-dimension models andquantify the L2 errors of reconstructed conductivity. Besides, we analyzefactors influencing the reconstructed accuracy such as reconstructedregularization parameter ultrasound frequency, and noise. We also demonstratethat the spatial resolution is not influenced by the duration of excitationultrasound. With the contributions of the proposed method, conductivity imagingappears to be feasible for application to the early diagnosis in the future.

Direct reconstruction of tissue conductivity with deconvolution in magneto-acousto-electrical tomography (MAET): theory and numerical simulation