Zilpelwar Sharvari, Sie Edbert J, Postnov Dmitry, Chen Anderson Ichun, Zimmermann Bernhard, Marsili Francesco, Boas David A, Cheng Xiaojun
Department of Electrical and Computer Engineering, Boston University, MA 02215, USA.
Neurophotonics Center, Department of Biomedical Engineering, Boston University, MA 02215, USA.
Biomed Opt Express. 2022 Nov 17;13(12):6533-6549. doi: 10.1364/BOE.472263. eCollection 2022 Dec 1.
We introduce a dynamic speckle model (DSM) to simulate the temporal evolution of fully developed speckle patterns arising from the interference of scattered light reemitted from dynamic tissue. Using this numerical tool, the performance of laser speckle contrast imaging (LSCI) or speckle contrast optical spectroscopy (SCOS) systems which quantify tissue dynamics using the spatial contrast of the speckle patterns with a certain camera exposure time is evaluated. We have investigated noise sources arising from the fundamental speckle statistics due to the finite sampling of the speckle patterns as well as those induced by experimental measurement conditions including shot noise, camera dark and read noise, and calibrated the parameters of an analytical noise model initially developed in the fundamental or shot noise regime that quantifies the performance of SCOS systems using the number of independent observables (NIO). Our analysis is particularly focused on the low photon flux regime relevant for human brain measurements, where the impact of shot noise and camera read noise can become significant. Our numerical model is also validated experimentally using a novel fiber based SCOS (fb-SCOS) system for a dynamic sample. We have found that the signal-to-noise ratio (SNR) of fb-SCOS measurements plateaus at a camera exposure time, which marks the regime where shot and fundamental noise dominates over camera read noise. For a fixed total measurement time, there exists an optimized camera exposure time if temporal averaging is utilized to improve SNR. For a certain camera exposure time, photon flux value, and camera noise properties, there exists an optimized speckle-to-pixel size ratio (s/p) at which SNR is maximized. Our work provides the design principles for any LSCI or SCOS systems given the detected photon flux and properties of the instruments, which will guide the experimental development of a high-quality, low-cost fb-SCOS system that monitors human brain blood flow and functions.
我们引入了一种动态散斑模型(DSM),以模拟由动态组织重新发射的散射光干涉产生的完全发展的散斑图案的时间演变。使用这个数值工具,评估了激光散斑对比成像(LSCI)或散斑对比光谱学(SCOS)系统的性能,这些系统在特定相机曝光时间下利用散斑图案的空间对比度来量化组织动力学。我们研究了由于散斑图案的有限采样而产生的基本散斑统计噪声源,以及由实验测量条件引起的噪声源,包括散粒噪声、相机暗噪声和读取噪声,并校准了最初在基本或散粒噪声 regime 中开发的分析噪声模型的参数,该模型使用独立可观测量(NIO)的数量来量化 SCOS 系统的性能。我们的分析特别关注与人类大脑测量相关的低光子通量 regime,在该 regime 中,散粒噪声和相机读取噪声的影响可能变得显著。我们还使用一种新颖的基于光纤的 SCOS(fb-SCOS)系统对动态样本进行了实验验证。我们发现,fb-SCOS 测量的信噪比(SNR)在相机曝光时间达到平稳,这标志着散粒噪声和基本噪声超过相机读取噪声的 regime。对于固定的总测量时间,如果利用时间平均来提高 SNR,则存在一个优化的相机曝光时间。对于特定的相机曝光时间、光子通量值和相机噪声特性,存在一个优化的散斑与像素尺寸比(s/p),在该比值下 SNR 最大化。我们的工作为给定检测到的光子通量和仪器特性的任何 LSCI 或 SCOS 系统提供了设计原则,这将指导监测人类大脑血流和功能的高质量、低成本 fb-SCOS 系统的实验开发。