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 in vitro 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 in vivo measurement of pulsatile flow rates measured in the human forearm.

中文翻译：

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带有外差全息检测的傅里叶域扩散相关光谱

我们提出了一种新的扩散相关光谱方法，该方法克服了单模光子计数技术的有限光通量。我们的系统采用外差全息检测技术，使用传统的sCMOS相机，可以在散粒噪声极限下，并行测量跨数千种模式的波动电场的功率谱。与传统技术相比，这可将检测器成本降低一个数量级，同时还提供了对环境光影响的鲁棒性和体外测试期间改进的信噪比实验。我们演示了一个GPU加速的全息解调系统，该系统能够实时处理传入数据（每秒7940万像素），以及一种新颖的扩散相关光谱的傅立叶域模型，该模型可以从测量数据中直接恢复流量参数。我们的检测和建模策略通过调制光学组织体模的布朗分量进行了严格验证，证明了布朗扩散系数的绝对测量结果与传统方法极为吻合。我们通过在人体前臂中测量脉动流速的体内测量进一步证明了我们系统的可行性。