Dynamic fluorescence lifetime sensing with CMOS single-photon avalanche diode arrays and deep learning processors.

Dynamic fluorescence lifetime sensing with CMOS single-photon avalanche diode arrays and deep learning processors.
复制标题

使用CMOS单光子雪崩二极管阵列和深度学习处理器进行动态荧光寿命检测。

DOI:
10.1364/boe.425663
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发表时间:
2021-06-01
影响因子:
3.4
通讯作者:
Uei Li DD
Uei Li DD
中科院分区:
医学2区
文献类型:
--
作者:
Xiao D;Zang Z;Sapermsap N;Wang Q;Xie W;Chen Y;Uei Li DD

文献摘要

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测量快速移动的细胞或颗粒的荧光寿命在生物医学科学中具有广泛的应用。本文提出了一种基于时间相关单光子计数(TCSPC)原理的动态荧光寿命传感(DFLS)系统。它集成了一个CMOS 192 × 128单光子雪崩二极管(SPAD)阵列,提供了巨大的光子计数吞吐量,没有堆积效应。我们还提出了一种量化卷积神经网络(QCNN)算法,并设计了一个现场可编程门阵列嵌入式处理器的荧光寿命测定。该处理器采用简单的架构,在精度、分析速度和功耗方面具有无与伦比的优势。它可以解决荧光寿命对干扰噪声。我们使用荧光染料和荧光团标记的微球评估DFLS系统。该系统可以在SPAD传感器的单个曝光周期内有效地测量荧光寿命,为便携式时间分辨设备铺平了道路,并在各种应用中显示出潜力。
Measuring fluorescence lifetimes of fast-moving cells or particles have broad applications in biomedical sciences. This paper presents a dynamic fluorescence lifetime sensing (DFLS) system based on the time-correlated single-photon counting (TCSPC) principle. It integrates a CMOS 192 × 128 single-photon avalanche diode (SPAD) array, offering an enormous photon-counting throughput without pile-up effects. We also proposed a quantized convolutional neural network (QCNN) algorithm and designed a field-programmable gate array embedded processor for fluorescence lifetime determinations. The processor uses a simple architecture, showing unparallel advantages in accuracy, analysis speed, and power consumption. It can resolve fluorescence lifetimes against disturbing noise. We evaluated the DFLS system using fluorescence dyes and fluorophore-tagged microspheres. The system can effectively measure fluorescence lifetimes within a single exposure period of the SPAD sensor, paving the way for portable time-resolved devices and shows potential in various applications.