Study on 3-D Acoustic Imaging for Human Thorax Based on Contrast Source Inversion

In this article, we study a 3-D acoustic imaging algorithm that can reconstruct compressibility, attenuation, and density simultaneously based on the contrast source inversion (CSI) method. This is a nonlinear and ill-posed inverse problem. To deal with the nonlinearity, we introduce two asymmetrical contrast sources that are functions of the contrasts and the total field. In this case, the scattered field and the total field are linear with the two contrast sources, and the two contrast sources are also linear with the two contrasts; thus, the nonlinearity is partially alleviated. To mitigate the ill-posedness of this inverse problem, we apply a multifrequency, multitransmitter, and multireceiver setting. Besides, to ensure the robustness of the algorithm, two multiplicative regularization terms are introduced as additional constraints. The reconstruction of those acoustic parameters can be achieved by alternately updating the contrast sources and the contrasts from the knowledge of the pressure field. Numerical studies show good reconstruction of compressibility, attenuation, and density of the synthetic thorax model, which validates the feasibility of imaging human thorax using low-frequency ultrasound.