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Related Experiment Video

Updated: Aug 31, 2025

Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells
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Computational Photon Counting Using Multithreshold Peak Detection for Fast Fluorescence Lifetime Imaging Microscopy.

Janet E Sorrells1,2, Rishyashring R Iyer2,3, Lingxiao Yang2,3

  • 1Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.

ACS Photonics
|August 23, 2022
PubMed
Summary
This summary is machine-generated.

Computational photon counting with a hybrid photodetector enables faster imaging by accurately distinguishing multiple photons. This advanced method improves fluorescence lifetime imaging microscopy (FLIM) for biological samples.

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Area of Science:

  • Biophotonics
  • Microscopy
  • Cell Biology

Background:

  • Time-resolved photon counting methods, including fluorescence lifetime imaging microscopy (FLIM), are limited by finite detector bandwidth, restricting acquisition speed.
  • Faster imaging is crucial for studying dynamic biological processes, such as cell apoptosis and organism movement.

Purpose of the Study:

  • To develop and validate a computational photon counting method to overcome the speed limitations of traditional FLIM.
  • To enable accurate characterization of biological samples at higher photon rates than previously possible.

Main Methods:

  • Utilized a hybrid photodetector coupled with multithreshold peak detection to count multiple photon arrivals within the detector response time.
  • Applied computational photon counting to digitized detector output at high sampling rates.
  • Demonstrated the method on freely moving *C. elegans* and human breast cancer cells undergoing apoptosis.

Main Results:

  • The multithreshold peak detection method successfully distinguished up to five photon counts per digitized point.
  • Achieved accurate characterization of sample intensity and fluorescence lifetime at photon rates up to 223% higher than previous computational photon counting FLIM systems.
  • Validated the method's performance in dynamic biological imaging scenarios.

Conclusions:

  • This novel computational photon counting approach significantly enhances the speed and capability of FLIM.
  • The method provides a powerful tool for high-speed, quantitative imaging of biological samples, particularly in studies of dynamic cellular events.