Abstract
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.
Highlights
The fluorescence lifetime (FL) indicates the average time a molecule stays excited state before returning to the ground state [1]
We developed a dynamic fluorescence lifetime sensing (DFLS) system with a 192×128-pixel array CMOS single-photon avalanche diode (SPAD) sensor (QuantiCAM) [22] and a deep learning (DL) hardware processor
We developed a quantized convolutional neural network (QCNN) specified for embedded hardware devices like field-programmable gate array (FPGA) to accurately reconstruct the lifetime from low signal-to-noise ratio (SNR) data with complex noise features
Summary
The fluorescence lifetime (FL) indicates the average time a molecule stays excited state before returning to the ground state [1]. FL delivers better quantitative analysis because it is less susceptible to fluorochromes’ excitation/emission spectra and concentration variations. It can distinguish tagged fluorochromes on specified cells from background signals (such as autofluorescence) or unbounded fluorochromes. FLIM instruments have been significantly enhanced, they are still too slow for 3D cellular imaging, endoscopy, and observing fast-moving particles or cells. For applications such as monitoring dynamic changes in a large cell population, high-throughput drug screening, or transient biological dynamics, measuring fast FL variations still poses a significant challenge on current FL-based systems
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