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采用外差全息检测的傅里叶域扩散相关光谱技术。

Fourier domain diffuse correlation spectroscopy with heterodyne holographic detection.

作者信息

James Edward, Powell Samuel

机构信息

Department of Medical Physics & Biomedical Engineering, University College London, London, WC1E 6BT, UK.

Faculty of Engineering, The University of Nottingham, University Park, Nottingham, NG7 2RD, UK.

出版信息

Biomed Opt Express. 2020 Oct 28;11(11):6755-6779. doi: 10.1364/BOE.400525. eCollection 2020 Nov 1.

Abstract

We present a new approach to diffuse correlation spectroscopy which overcomes the limited light throughput of single-mode photon counting techniques. Our system employs heterodyne holographic detection to allow parallel measurement of the power spectrum of a fluctuating electric field across thousands of modes, at the shot noise limit, using a conventional sCMOS camera. This yields an order of magnitude reduction in detector cost compared to conventional techniques, whilst also providing robustness to the effects of ambient light and an improved signal-to-noise ratio during experiments. We demonstrate a GPU-accelerated holographic demodulation system capable of processing the incoming data (79.4 M pixels per second) in real-time, and a novel Fourier domain model of diffuse correlation spectroscopy which permits the direct recovery of flow parameters from the measured data. Our detection and modelling strategy are rigorously validated by modulating the Brownian component of an optical tissue phantom, demonstrating absolute measurements of the Brownian diffusion coefficient in excellent agreement with conventional methods. We further demonstrate the feasibility of our system through measurement of pulsatile flow rates measured in the human forearm.

摘要

我们提出了一种用于扩散相关光谱学的新方法,该方法克服了单模光子计数技术光通量有限的问题。我们的系统采用外差全息检测,能够在散粒噪声极限下,使用传统的科学互补金属氧化物半导体(sCMOS)相机,对数千个模式下波动电场的功率谱进行并行测量。与传统技术相比,这使得探测器成本降低了一个数量级,同时还能抵御环境光的影响,并在实验过程中提高信噪比。我们展示了一种能够实时处理输入数据(每秒7940万像素)的GPU加速全息解调系统,以及一种新颖的扩散相关光谱学傅里叶域模型,该模型允许从测量数据中直接恢复流动参数。通过调制光学组织模型的布朗分量,我们严格验证了我们的检测和建模策略,证明了对布朗扩散系数的绝对测量结果与传统方法高度一致。我们还通过测量人体前臂的脉动流速,进一步证明了我们系统的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e048/7687971/cf897924d952/boe-11-11-6755-g001.jpg

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