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Live-SIMBA: an ImageJ plug-in for the universal and accelerated single molecule-guided Bayesian localization super

Hongjia Li1,2,3, Fan Xu4,3, Shan Gao1,2

  • 1High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences, No. 6 Kexueyuan South Road, Haidian District, Beijing, 100190, China.

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Summary

We developed Live-SIMBA, a new ImageJ plugin for super-resolution microscopy. This tool enhances live-cell imaging analysis by accelerating computation and enabling real-time visualization without special datasets.

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Area of Science:

  • Live-cell super-resolution fluorescence microscopy
  • Nanoscale imaging of cellular dynamics

Background:

  • Super-resolution microscopy enables nanoscale observation of live cells.
  • Single molecule-guided Bayesian localization super resolution microscopy (SIMBA) offers good spatial and temporal resolution using standard equipment.
  • Existing SIMBA methods have limitations including dataset requirements, slow computation, and lack of real-time visualization.

Purpose of the Study:

  • To develop a universal and accelerated SIMBA ImageJ plugin for live-cell time-series analysis.
  • To overcome limitations of existing SIMBA techniques for improved live-cell super-resolution imaging.

Main Methods:

  • Developed Live-SIMBA, an ImageJ plugin integrating SIMBA principles.
  • Implemented an intensity-based sampling algorithm to eliminate dual-channel dataset requirements.
  • Utilized multi-core parallel computing for accelerated calculations and incorporated adjustable background estimation and distance-threshold filtering for enhanced signal resolution.

Main Results:

  • Live-SIMBA circumvents the need for dual-channel datasets.
  • Achieved significantly accelerated computation speeds via parallel processing.
  • Improved resolution of weak signals and provided real-time visualization capabilities.

Conclusions:

  • Live-SIMBA offers an improved, accelerated, and user-friendly approach to live-cell super-resolution imaging.
  • The plugin enhances fidelity of reconstructed structures and demonstrates extended capabilities for nanoscale analysis in living cells.