Functional imaging method of biological electrical characteristics based on magneto-acoustic effect gives valuable information of tissue in early tumor diagnosis, therein time and frequency characteristics analysis of magneto-acoustic signal is important in image reconstruction. This paper proposes wave summing method based on Green function solution for acoustic source of magneto-acoustic effect. Simulations and analysis under quasi 1D transmission condition are carried out to time and frequency characteristics of magneto-acoustic signal of models with different thickness. Simulation results of magneto-acoustic signal were verified through experiments. Results of the simulation with different thickness showed that time-frequency characteristics of magneto-acoustic signal reflected thickness of sample. Thin sample, which is less than one wavelength of pulse, and thick sample, which is larger than one wavelength, showed different summed waveform and frequency characteristics, due to difference of summing thickness. Experimental results verified theoretical analysis and simulation results. This research has laid a foundation for acoustic source and conductivity reconstruction to the medium with different thickness in magneto-acoustic imaging.
Magnetoacoustic tomography (MAT) has some advantages such as high sensitivity and high spatial resolution. The generating mechanism of acoustic source is the research foundation of forward and inverse problems. Acoustic signals were respectively simulated by using monopole and dipole radiation theory in the experimental conditions, then the differences between their acoustic pressures were discussed, and furthermore the contrast and validation were conducted by physical experiments in this study. The physical experimental results showed that acoustic waveform of MAT had a certain directivity and therefore they indicated that dipole model showed higher approximation to the real facts than monopole model. It can be well concluded that this research has cardinal significance for the accurate algorithm of MAT.