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Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
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Superresolution localization methods.

Alexander R Small1, Raghuveer Parthasarathy

  • 1Department of Physics and Astronomy, California State Polytechnic University, Pomona, California 91768.

Annual Review of Physical Chemistry
|November 27, 2013
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Summary
This summary is machine-generated.

This review surveys fluorophore localization algorithms used in superresolution microscopy. It compares algorithm complexity, performance, and applicability for nanoscale imaging, offering practical advice for users.

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Area of Science:

  • Biophysics
  • Optical Microscopy
  • Computational Imaging

Background:

  • Superresolution localization microscopy achieves nanoscale imaging using fluorescent probes and position-determining algorithms.
  • Localization algorithms vary significantly in principles, complexity, and accuracy, impacting image resolution.

Purpose of the Study:

  • To review and compare various fluorophore localization algorithms for superresolution microscopy.
  • To discuss fundamental limits of localization precision and practical considerations for algorithm users.

Main Methods:

  • Survey of localization microscopy principles.
  • Examination of different families of fluorophore localization algorithms.
  • Comparison of algorithms based on complexity, performance, and applicability.

Main Results:

  • Localization algorithms differ in their requirements for experimental data and optimization for specific scenarios.
  • Consideration of algorithms for oriented dipoles, 3D localization, and overlapping emitters.
  • Identification of practical advice and open questions for algorithm users.

Conclusions:

  • Understanding algorithm characteristics is crucial for selecting appropriate methods in superresolution imaging.
  • The review provides a comparative analysis to guide researchers in applying localization microscopy techniques.
  • Further research is needed to address limitations and develop advanced localization algorithms.