Fluorescence lifetime tracking and imaging of single moving particles assisted by a low-photon-count analysis algorithm

  • Chen P
  • Kang Q
  • Niu J
  • et al.
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Abstract

Fluorescence lifetime imaging microscopy (FLIM) has been widely used in the field of biological research because of its high specificity, sensitivity, and quantitative ability in the sensing cellular microenvironment. The most commonly used FLIM technology is based on time-correlated single photon counting (TCSPC). Although the TCSPC method has the highest temporal resolution, the data acquisition time is usually long, and the imaging speed is slow. In this work, we proposed a fast FLIM technology for fluorescence lifetime tracking and imaging of single moving particles, named single particle tracking FLIM (SPT-FLIM). We used feedback-controlled addressing scanning and Mosaic FLIM mode imaging to reduce the number of scanned pixels and the data readout time, respectively. Moreover, we developed a compressed sensing analysis algorithm based on alternating descent conditional gradient (ADCG) for low-photon-count data. We applied the ADCG-FLIM algorithm on both simulated and experimental datasets to evaluate its performance. The results showed that ADCG-FLIM could achieve reliable lifetime estimation with high accuracy and precision in the case of a photon count less than 100. By reducing the photon count requirement for each pixel from, typically, 1000 to 100, the acquisition time for a single frame lifetime image could be significantly shortened, and the imaging speed could be improved to a great extent. On this basis, we obtained lifetime trajectories of moving fluorescent beads using the SPT-FLIM technique. Overall, our work offers a powerful tool for fluorescence lifetime tracking and imaging of single moving particles, which will promote the application of TCSPC-FLIM in biological research.

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Chen, P., Kang, Q., Niu, J., Jing, Y., Zhang, X., Yu, B., … Lin, D. (2023). Fluorescence lifetime tracking and imaging of single moving particles assisted by a low-photon-count analysis algorithm. Biomedical Optics Express, 14(4), 1718. https://doi.org/10.1364/boe.485729

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