The study on the inverse problem of applied current thermoacoustic imaging based on generative adversarial network

Applied Current Thermoacoustic Imaging (ACTAI) is a new imaging method which combines electromagnetic excitation with ultrasound imaging, and takes ultrasonic signal as medium and biological tissue conductivity as detection target. Taking the high contrast advantage of Electrical Impedance Tomography (EIT) and high resolution advantage of ultrasound imaging, ACTAI has broad application prospects in the field of biomedical imaging. Although ACTAI has high excitation efficiency and strong detectable Signal-to-Noise Ratio, yet while under low frequency electromagnetic excitation, it is still a big challenge to reconstruct a high-resolution image of target conductivity. This paper proposes a new method for reconstructing conductivity based on Generative Adversarial Network, and it consists of three main steps: firstly, use Wiener filtering deconvolution to restore the electrical signal output by the ultrasonic probe to a real acoustic signal. Then obtain the initial acoustic source image with filtered backprojection technology. Finally, match the conductivity image with the initial sound source image, which are used as training samples for generating the adversarial network to establish a deep learning model for conductivity reconstruction. After theoretical analysis and simulation research, it is found that by introducing machine learning, the new method can dig out the inverse problem solving model contained in the data, which further reconstruct a high-resolution conductivity image and has strong anti-interference characteristics. The new method provides a new way to solve the problem of conductivity reconstruction in Applied Current Thermoacoustic Imaging.

STUDY OF ACOUSTIC SOURCE EXCITED BY PULSED MAGNETIC FIELD

In magnetoacoustic tomography with magnetic induction and magnetically mediated thermoacoustic imaging, tissues are exposed to an alternating field, generating magnetoacoustic and thermoacoustic effects in the tissues. This study aimed to investigate the relationship between magnetoacoustic and thermoacoustic effects in a low-conductivity object put in a Gauss-pulsed alternating magnetic field. First, the derivations of the magnetic flux density and electric field strength induced by a Gauss-pulsed current flowing through the coil based on the theory of electromagnetic field were examined. Second, the analytical solution of the magnetic field was studied by simulation. To validate the accuracy of the analytical solution, the analytical solution and the numerical simulation of the magnetic flux density were compared. It shows that the analytical solution coincides with the numerical simulation well. Then, based on the theoretical analysis of the acoustic source generation, numerical studies were conducted to simulate pressures excited by magnetoacoustic and thermoacoustic effects in low-conductivity objects similar to tissues in the Gauss-pulsed magnetic field. The thermoacoustic effect played a leading role in low-conductivity objects placed in the Gauss-pulsed magnetic field, and the magnetoacoustic effect could be ignored. This study provided the theoretical basis for further research on magnetoacoustic tomography with magnetic induction and magnetically mediated thermoacoustic imaging for pathological tissues.

Investigation of artifacts by mapping SAR in thermoacoustic imaging

Microwave-induced thermoacoustic imaging (MI-TAI) remains one of the focus of attention among biomedical imaging modalities over the last decade. However, the transmission and distribution of microwave inside bio-tissues are complicated, thus result in severe artifacts. In this study, to reveal the underlying mechanisms of artifacts, we deeply investigate the distribution of specific absorption rate (SAR) inside tissue-mimicking phantoms with varied morphological features using both mathematical simulations and corresponding experiments. Our simulated results, which are confirmed by the associated experimental results, show that the SAR distribution highly depends on the geometries of the imaging targets and the polarizing features of the microwave. In addition, we propose the potential mechanisms including Mie-scattering, Fabry-Perot-feature, small curvature effect to interpret the diffraction effect in different scenarios, which may provide basic guidance to predict and distinguish the artifacts for TAI in both fundamental and clinical studies.