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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
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Optimized molecule detection in localization microscopy with selected false positive probability.

Miroslav Hekrdla1, David Roesel2, Niklas Hansen2,3

  • 1J. Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences, Prague, Czechia. miroslav.hekrdla@jh-inst.cas.cz.

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|January 11, 2025
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Summary
This summary is machine-generated.

We developed an optimized molecule detection method for single-molecule localization microscopy (SMLM). This approach controls false positives and minimizes false negatives for robust, reproducible SMLM data analysis.

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Area of Science:

  • Biophysics
  • Microscopy
  • Computational Biology

Background:

  • Single-molecule localization microscopy (SMLM) enables super-resolution imaging.
  • Accurate molecule detection is critical for SMLM data analysis.
  • Current detection methods suffer from uncontrolled false positives and lack standardization, leading to artifacts and hindering reproducibility.

Purpose of the Study:

  • To develop an optimized molecule detection method for SMLM.
  • To provide quantitative control over false positive detections.
  • To enhance the robustness and reproducibility of SMLM data analysis.

Main Methods:

  • Combined probabilistic thresholding with theoretically optimal filtering.
  • Utilized a theoretically optimal Poisson matched filter as a benchmark.
  • Evaluated existing filtering methods against the optimal filter.

Main Results:

  • The optimized method enables quantitative control over false positive detections.
  • Optimal filtering minimizes false negative detections.
  • The approach provides robust, single-parameter, and user-unbiased molecule detection.

Conclusions:

  • The developed method minimizes artifacts in SMLM analysis.
  • This approach significantly improves the reproducibility of SMLM data.
  • This advancement is crucial for reliable super-resolution microscopy.