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Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
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Related Experiment Video

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Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells
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Published on: February 9, 2012

Segmentation-guided photon pooling enables robust single-cell analysis and fast fluorescence lifetime imaging

Kayvan Samimi1, Danielle E Desa1, Xiaotian Zhang2

  • 1Morgridge Institute for Research, Madison, Wisconsin, United States.

Journal of Biomedical Optics
|July 3, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a fast, label-free method using region-of-interest (ROI) photon pooling for fluorescence lifetime imaging microscopy (FLIM). This technique significantly speeds up data acquisition for live cells while maintaining metabolic information.

Keywords:
NADHautofluorescence imagingdecay fittingfluorescence lifetime imaging microscopylifetime estimationphoton pooling

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Area of Science:

  • Biophotonics and advanced microscopy techniques.
  • Cellular metabolism and live-cell imaging.

Background:

  • Fluorescence lifetime imaging microscopy (FLIM) offers label-free, noninvasive probing of cellular metabolic states.
  • Low absorption and quantum yields of endogenous fluorophores necessitate long acquisition times for accurate analysis.

Purpose of the Study:

  • To develop and validate a computationally efficient "region-of-interest" (ROI) photon pooling method to accelerate FLIM acquisition and analysis.
  • To compare the accuracy and precision of ROI photon pooling against standard FLIM fitting techniques.

Main Methods:

  • Characterization of ROI photon pooling accuracy using fluorescence standards.
  • Testing the method's ability to recover fluorescence lifetimes from single cells and large regions with low photon counts.
  • Application to dynamic live samples and comparison with conventional pixel-level analysis.

Main Results:

  • Accurate single-cell metabolic information extracted in as little as 1-second scanning periods.
  • FLIM mosaics acquired 15 times faster than conventional methods.
  • Comparable fluorescence lifetimes obtained with ROI photon pooling versus standard methods requiring longer integration times.

Conclusions:

  • ROI photon pooling enables rapid FLIM acquisition from live, dynamic samples with low photon budgets.
  • The technique preserves cell-level or ROI-level lifetime information at the cost of intra-ROI spatial resolution.
  • This computationally light method is compatible with standard analysis software and does not require machine learning.