Abstract
Due to the acoustic source distribution and limited bandwidth ultrasound measurement, the dominant ultrasound signals always come from the boundary of the electrical conductivity in magneto-acoustic tomography with magnetic induction (MAT-MI). To make full use of the strong boundary ultrasound signals, a system matrix is built which shows the relationship between the electrical conductivity and the ultrasound signals. By analyzing the singular values of the system matrix, the necessary signal to noise ratio(SNR) level is estimated in this study. An inverse procedure based on the truncated singular value decomposition(TSVD) method is presented to improve the quality of the reconstructed MAT-MI image. Simulation results show that the reconstructed conductivity images by using the new algorithm match better than that of the back-projection algorithm. Both the simulation results and the experiment results prove the reconstructed image is close to the original conductivity distribution when the more singular values are used in the inverse procedure. Meanwhile, as the number of singular values increases, the effect of noise will be enhanced in the reconstructed image. The proposed reconstruction algorithm can improve the quality of the reconstruction image for a low SNR system. Moreover, the system matrix based reconstruction algorithm proposed in this work will help to analyze the physical process and to obtain accurate high-resolution reconstructions for MAT-MI.
Highlights
Previous studies have shown that the electrical conductivity of biological tissue is an important parameter for disease detection
In Magneto-acoustic tomography with magnetic induction (MAT-MI), the magnetic field, induced eddy current and acoustic pressure are the functions of time and space, according to the electromechanical coupling mechanism of electrical, magnetic and acoustic fields in biological tissue, the acoustic pressure distribution is expressed by the following wave equation (1) [15]:
We proposed a TSVD based image reconstruction algorithm in which the desired information of the conductivity distribution was directly associated with the ultrasound signals
Summary
Previous studies have shown that the electrical conductivity of biological tissue is an important parameter for disease detection. It is hard to find a relationship between the conductivity distribution and ultrasound signals This causes the information from ultrasound signals are not fully used by the current models. To address these problems, a system model to describe the relationship between detected ultrasound signals and the reconstructed conductivity distribution should be build up. System model based algorithms can be used to compensate the loss of information and get information from the signals with lower SNR by incorporating the detectors geometry in model matrix This concept has been used in the reconstruction of magnetic resonance imaging(MRI) and computed tomography(CT) in order to reduce the radiation dose and the scan time [11], [12]. Quantitative and qualitative results indicate that the proposed method can be a proper option when we face a low SNR MAT-MI system
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
