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Multi-color Localization Microscopy of Single Membrane Proteins in Organelles of Live Mammalian Cells
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Real-time 3D single-molecule localization microscopy analysis using lookup tables.

Fabian Hauser1,2, Jaroslaw Jacak1,2

  • 1University of Applied Sciences, Upper Austria School of Medical Engineering and Applied Social Sciences, Garnisonstraße 21, 4020 Linz, Austria.

Biomedical Optics Express
|September 13, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel algorithm for rapid 3D single molecule localization microscopy image analysis. It enables real-time visualization and maintains fitting accuracy for improved microscopy workflows.

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Area of Science:

  • Microscopy
  • Biophysics
  • Image Analysis

Background:

  • 3D Single Molecule Localization Microscopy (3D-SMLM) is crucial for high-resolution biological imaging.
  • Real-time analysis of 3D-SMLM data is computationally demanding, limiting immediate feedback during experiments.
  • Accurate localization of individual fluorescent molecules is essential for reconstructing nanoscale structures.

Purpose of the Study:

  • To develop and validate a new algorithm for real-time analysis of 3D-SMLM images.
  • To achieve fast image processing with minimal loss in localization accuracy.
  • To integrate real-time fitting with experimental feedback for optimized emitter density.

Main Methods:

  • Implementation of a novel algorithm utilizing lookup-tables with discrete xyz-positions for rapid fitting.
  • Real-time visualization of microscopy data during image acquisition.
  • Development of a feedback loop controlling the activation laser pulse based on real-time fitting results.

Main Results:

  • The algorithm provides real-time analysis of 3D-SMLM images with a negligible impact on fitting accuracy.
  • Demonstrated performance on both simulated and experimentally acquired datasets.
  • Successful integration of real-time fitting with a feedback loop to maintain a constant number of emitters per frame.

Conclusions:

  • The developed algorithm significantly enhances the efficiency of 3D-SMLM data processing.
  • Real-time analysis and feedback control enable more dynamic and optimized microscopy experiments.
  • This approach facilitates faster insights from high-resolution imaging studies.