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2019-04-18

Low-Power Microwave Induced Thermoacoustic Imaging: Experimental Study and Hybrid FEM Modeling

By Ryan Jacobs, Mohand Alzuhiri, Mark Golkowski, and Yiming Deng
Progress In Electromagnetics Research C, Vol. 91, 265-277, 2019
doi:10.2528/PIERC18100101

Abstract

Microwave induced thermoacoustic imaging (TAI) is a hybrid imaging technique combining microwaves and ultrasound waves to achieve both superior spatial resolution and high image contrast. Here, we present results from a hybrid finite element model and an experimental setup using a microwavem peak power of less than 5 kW (average power of only 4.5 W), significantly less than for comparable imaging performance in previous works. Microwave pulses with a duration less than 1 μs are used to excite ultrasound waves with a frequency higher than 1 MHz. Experimental measurements show agreement with simulation results using hybrid finite element modeling capturing microwave heating and acoustic wave propagation. Simulations suggest targets with a conductivity of approximately 0.9 S/m yield the strongest thermoacoustic signatures. Both B-mode images and time-reversal based reconstructed images are obtained and clearly demonstrate the enhanced contrast and high resolution by exploiting the dielectric absorption properties of microwaves and the sub-millimeter resolution of ultrasound. The use of a time reversal algorithm on recorded data demonstrates the effectiveness of TAI for biomedical applications. Standing wave patterns are identified in targets and their relation to the target characteristics and their effect on the resulted images are investigated. The novelty of this work is in lowering the microwave average power while still being able to detect induced acoustic signals, along with developing a numerical model to provide an insight into the imaging process and analyze anomalies in image reconstruction.

Citation


Ryan Jacobs, Mohand Alzuhiri, Mark Golkowski, and Yiming Deng, "Low-Power Microwave Induced Thermoacoustic Imaging: Experimental Study and Hybrid FEM Modeling," Progress In Electromagnetics Research C, Vol. 91, 265-277, 2019.
doi:10.2528/PIERC18100101
http://jpier.org/PIERC/pier.php?paper=18100101

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