Measuring localization performance of super-resolution algorithms on very active samples.

Area of Science:

• Biophysics
• Optical Microscopy
• Computational Imaging

Background:

• Super-resolution fluorescence imaging, particularly single-molecule localization microscopy (SMLM), requires precise algorithms for identifying and localizing single fluorophore emissions.
• Applications like 3D, time-resolved, or cluster imaging often involve high densities of fluorophores, posing challenges for existing algorithms.

Purpose of the Study:

• To develop an analytic tool for evaluating the performance and quality of SMLM algorithms.
• To investigate the limitations of common SMLM algorithms when applied to samples with high fluorophore density.

Main Methods:

• Development of a novel analytic tool to assess localization microscopy algorithm performance.
• Testing of common SMLM algorithms, including dSTORM and rapidSTORM, using simulated and experimental data with varying fluorophore densities.

Main Results:

• Common SMLM algorithms exhibit performance degradation in samples with high fluorophore density.
• Computational precision limits the acceptable density of concurrently active fluorophores to 0.6 per square micrometer for dSTORM and rapidSTORM.
• The number of successfully localized fluorophores per frame is restricted to 0.2 per square micrometer.

Conclusions:

• Existing SMLM algorithms face significant challenges in accurately localizing fluorophores at high densities.
• The findings highlight critical limitations in computational precision for current single-molecule localization microscopy techniques.
• The developed analytic tool can aid in assessing algorithm robustness and guiding future algorithm development for dense SMLM applications.