Quantification of blood flow index in diffuse correlation spectroscopy using long short-term memory architecture
Quantification of blood flow index in diffuse correlation spectroscopy using long short-term memory architecture
复制标题
使用长短期记忆架构量化漫相关光谱中的血流指数
DOI：
10.1364/boe.423777
复制
发表时间：
2021-07-01
影响因子：
3.4
通讯作者：
Zhao, Jing
中科院分区：
文献类型：
--
作者：
Li, Zhe;Ge, Qisi;Zhao, Jing
漫射相关光谱学（DCS）是一种非侵入性技术，通过测量多重散射光的时间强度波动来获取血流信息。血流指数（BFI），特别是它的变化被证明是近似成正比的绝对血流量。我们调查并评估了长短期记忆（LSTM）架构在DCS中量化BFI的效用。建立幻体和体内实验，测量归一化强度自相关函数数据。所提出的LSTM结构提高了精度，缩短了计算时间。结果支持使用所提出的LSTM架构对DCS中的BFI进行量化的概念。这种方法对于持续实时监测血流特别有用。(c)根据OSA开放获取出版协议的条款，2021年美国光学学会
Diffuse correlation spectroscopy (DCS) is a noninvasive technique that derives blood flow information from measurements of the temporal intensity fluctuations of multiply scattered light. Blood flow index (BFI) and especially its variation was demonstrated to be approximately proportional to absolute blood flow. We investigated and assessed the utility of a long short-term memory (LSTM) architecture for quantification of BFI in DCS. Phantom and in vivo experiments were established to measure normalized intensity autocorrelation function data. Improved accuracy and faster computational time were gained by the proposed LSTM architecture. The results support the notion of using proposed LSTM architecture for quantification of BFI in DCS. This approach would be especially useful for continuous real-time monitoring of blood flow. (c) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement