Department of Physics, Beijing University of Chemical Technology, Beijing, 100029, China.
State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing, 100084, China.
Sci Rep. 2019 Mar 13;9(1):4328. doi: 10.1038/s41598-019-40919-6.
Noninvasive light focusing and imaging through a scattering medium can be achieved by wavefront shaping using the photoacoustic signal as feedback. Unfortunately, the signal to noise ratio (SNR) of the traditional photoacoustic method is very low, which limits the wavefront shaping focusing speed and intensity. In this paper, we propose a completely new photoacoustic-signal-extraction method which combines wavelet denoising and correlation detection. With this method, the SNR of the photoacoustic signal reaches 25.2, 6.5 times higher than that of the unprocessed photoacoustic signal. Moreover, we achieve the simultaneous multipoint focusing, which is crucial for improving the speed of scanning imaging. The superior performance of the proposed method was experimentally demonstrated in extracting and denoising the photoacoustic signals deeply buried in noise, one critical step in in vivo photoacoustic imaging.
通过使用光声信号作为反馈的波前整形，可以实现通过散射介质的非侵入性光聚焦和成像。不幸的是，传统光声方法的信噪比（SNR）非常低，这限制了波前整形聚焦的速度和强度。在本文中，我们提出了一种完全新颖的光声信号提取方法，该方法结合了小波去噪和相关检测。使用这种方法，光声信号的 SNR 达到 25.2，比未经处理的光声信号高 6.5 倍。此外，我们实现了同时多点聚焦，这对于提高扫描成像速度至关重要。该方法在提取和去噪深度埋藏在噪声中的光声信号方面的优越性能在体内光声成像的一个关键步骤中得到了实验验证。
