The application of a wavelet filtering method in magneto-acousto-electrical tomography

Abstract

Magneto-acousto-electrical tomography (MAET), which couples ultrasound imaging with electrical impedance tomography, is an electrical property imaging method which is expected to have a wide range of clinical applications, including the early detection of breast and liver cancers. Obviously, as a coupled imaging method, how to improve the signal-to-noise ratio (SNR) is a key issue in the imaging process. In this paper, a wavelet filtering method is introduced into MAET, which includes the filtering effect of the db6 wavelet, and its filtering effect at different decomposition levels. At the same time, based on the Lorentz reciprocity theorem, the wave equation satisfied by the detected voltage obtained by electrode was deduced. We also built an experimental platform to acquire signals by keeping the position of the target unchanged and moving the ultrasound transducer along the trajectory of a circular arc. The experimental results show that the wavelet filtering scheme proposed in this paper improves the SNR of the detected signal of 15.1 dB, and the images of electrical properties of the phantom and pork from isolated tissues were realized by the filtered signal of the db6 wavelet and time reversal method, which reflects the interface of electrical conductivity change of tissues. This scanning method, of fixing the target body and rotating the transducer, can effectively reduce the error and noise caused by the movement of the detection electrodes in the experiment. The filtering technique and imaging algorithm proposed in this paper have improved the SNR and contrast of the images. Thus, the images of the low conductivity phantom with 0.2 S m−1 and isolated tissue were obtained, which indicates that the MAET has good prospects in clinical applications.