Microwave-induced thermo-acoustic tomography (MITAT) is a promising technique with great potential in biomedical imaging. It has both the high contrast of the microwave imaging and the high resolution of the ultrasoun...Microwave-induced thermo-acoustic tomography (MITAT) is a promising technique with great potential in biomedical imaging. It has both the high contrast of the microwave imaging and the high resolution of the ultrasound imaging. In this paper, the proportional relationship between the absorbed microwave energy distribution and the induced ultrasound source distribution is derived. Further, the time reversal mirror (TRM) technique based on the pseudo-spectral time domain (PSTD) method is applied to MITAT system. The simulation results show that high contrast and resolution can be achieved by the TRM technique based on PSTD method even for the received signals with very low signal-to-noise ratio (SNR) and the model parameter with random fluctuation.展开更多
基金Supported by the National Natural Science Foundation of China(Grant No.60771042)the National Hi-Tech Research and Development Program("863"Project)(Grant No.2007AA12Z159)+2 种基金111Project(Grant No.B07046)SiChuan Excellent Youth Foun-dation(Grant No.08ZQ026-039)Program for New Century Excellent Talents in University of China and Program for Changjiang Scholars
文摘Microwave-induced thermo-acoustic tomography (MITAT) is a promising technique with great potential in biomedical imaging. It has both the high contrast of the microwave imaging and the high resolution of the ultrasound imaging. In this paper, the proportional relationship between the absorbed microwave energy distribution and the induced ultrasound source distribution is derived. Further, the time reversal mirror (TRM) technique based on the pseudo-spectral time domain (PSTD) method is applied to MITAT system. The simulation results show that high contrast and resolution can be achieved by the TRM technique based on PSTD method even for the received signals with very low signal-to-noise ratio (SNR) and the model parameter with random fluctuation.