Study on Joint Inversion Algorithm of Acoustic and Electromagnetic Data in Biomedical Imaging

Abstract

In this paper, we study a joint inversion algorithm to reconstruct acoustic and electromagnetic (EM) data in biomedical imaging. This algorithm is based on contrast source inversion algorithm. We define contrast source and contrast functions in both acoustics and EMs, respectively, and apply two reciprocal regularization operators to link acoustic and EM inversion. By minimizing the cost function using the conjugate gradient method, we can simultaneously reconstruct compressibility, attenuation, permittivity, and conductivity of different human tissues. Numerical experiments show that acoustic and EM inversion can compensate each other and achieve a better reconstruction than individual inversion. Besides, the joint inversion method is particularly sensitive to compressibility and conductivity and thus may be used to monitor air and water contents in human thorax as well as other applications in biomedicine.