优化散斑对比光学谱学噪声校准，提升脑血流测量精度
Optimized cerebral blood flow measurement in speckle contrast optical spectroscopy via refinement of noise calibration
- 基于优化框架自适应修正噪声校准，降低误差
- 信号阈值从97降至26电子/像素，提升低信号下可靠性
- 适合深部组织检测，尤其在远源-探测器距离下
散斑对比光学谱学（SCOS）是一种非侵入、低成本的脑血流（CBF）监测方法。但精确提取CBF需精准的噪声预标定，否则会因噪声误差导致测量失真，尤其在整体信号水平较低时。主要误差源于相机与光子噪声相关的残余散斑对比度波动，其时间特性与脑血容量（CBV）波形相似。本文提出一种优化框架，通过自适应细化噪声校准，降低CBF-CBV波形相关性，从而抑制伪影。在10名受试者上的验证表明，该方法将1920x1200像素的SCOS系统可靠CBF信号阈值从97电子/像素降至26电子/像素。这一改进使在大源-探测器距离下的深层组织检测中，实现更准确、更鲁棒的CBF测量。
原文摘要 · Abstract (English)
Speckle contrast optical spectroscopy (SCOS) offers a non-invasive and cost-effective method for monitoring cerebral blood flow (CBF). However, extracting accurate CBF from SCOS necessitates precise noise pre-calibration. Errors from this can degrade CBF measurement fidelity, particularly when the overall signal level is low. Such errors primarily stem from residual speckle contrast associated with camera and shot noise, whose fluctuations exhibit a temporal structure that mimics cerebral blood volume (CBV) waveforms. We propose an optimization-based framework that performs an adaptive refinement of noise calibration, mitigating the CBV-mimicking artifacts by reducing the CBF-CBV waveform correlation. Validated on 10 human subjects, our approach effectively lowered the signal threshold for reliable CBF signal from 97 to 26 electrons per pixel for a 1920x1200 pixels SCOS system. This improvement enables more accurate and robust CBF measurements in SCOS, especially at large source-detector (SD) distances for deeper tissue interrogation.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。