Polarization-dependent optical reflection ultrasonic detection

Xiaoyi Zhu; Zhiyu Huang; Guohe Wang; Wenzhao Li; Changhui Li

doi:10.1117/12.2251079

3 March 2017 Polarization-dependent optical reflection ultrasonic detection

Xiaoyi Zhu, Zhiyu Huang, Guohe Wang, Wenzhao Li, Changhui Li

Proceedings Volume 10064, Photons Plus Ultrasound: Imaging and Sensing 2017; 100641X (2017) https://doi.org/10.1117/12.2251079
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Although ultrasound transducers based on commercial piezoelectric-material have been widely used, they generally have limited bandwidth centered at the resonant frequency. Currently, several pure-optical ultrasonic detection methods have gained increasing interest due to their wide bandwidth and high sensitivity. However, most of them require customized components (such as micro-ring, SPR, Fabry-Perot film, etc), which limit their broad implementations. In this study, we presented a simple pure-optical ultrasound detection method, called “Polarization-dependent Reflection Ultrasonic Detection” (PRUD). It detects the intensity difference between two polarization components of the probe beam that is modulated by ultrasound waves. PRUD detect the two components by using a balanced detector, which effectively suppressed much of the unwanted noise. We have achieved the sensitivity (noise equivalent pressure) to be 1.7kPa, and this can be further improved. In addition, like many other pure-optical ultrasonic detection methods, PRUD also has a flat and broad bandwidth from almost zero to over 100MHz. Besides theoretical analysis, we did a phantom study by imaging a tungsten filament to demonstrate the performance of PRUD. We believe this simple and economic method will attract both researchers and engineers in optical and ultrasound fields.

Citation Download Citation

Xiaoyi Zhu, Zhiyu Huang, Guohe Wang, Wenzhao Li, and Changhui Li "Polarization-dependent optical reflection ultrasonic detection", Proc. SPIE 10064, Photons Plus Ultrasound: Imaging and Sensing 2017, 100641X (3 March 2017); https://doi.org/10.1117/12.2251079

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