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Related Experiment Video

Updated: Jun 3, 2026

Test Samples for Optimizing STORM Super-Resolution Microscopy
16:52

Test Samples for Optimizing STORM Super-Resolution Microscopy

Published on: September 6, 2013

Comparison between SOFI and STORM.

Stefan Geissbuehler, Claudio Dellagiacoma, Theo Lasser

    Biomedical Optics Express
    |March 18, 2011
    PubMed
    Summary
    This summary is machine-generated.

    Super-resolution microscopy using stochastic optical fluctuation imaging (SOFI) offers a robust alternative to localization-based methods like PALM/STORM. SOFI provides consistent performance across various blinking behaviors and is suitable for high-speed live-cell imaging.

    Keywords:
    (100.6640) Super-resolution(180.2520) Fluorescence microscopy

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    Imaging Intermediate Filaments and Microtubules with 2-dimensional Direct Stochastic Optical Reconstruction Microscopy

    Published on: March 6, 2018

    Area of Science:

    • Biophysics
    • Microscopy
    • Optical Imaging

    Background:

    • Super-resolution microscopy techniques enable imaging beyond the diffraction limit of light.
    • Stochastically blinking emitters are crucial for achieving super-resolution with methods like PALM and STORM.
    • Analyzing temporal fluctuations offers an alternative approach to super-resolution imaging.

    Purpose of the Study:

    • To compare the performance of localization-based super-resolution algorithms (PALM/STORM) with fluctuation-based methods (SOFI).
    • To evaluate the applicability of these techniques for live-cell imaging.
    • To assess the impact of probe blinking behavior on super-resolution capabilities.

    Main Methods:

    • Acquisition of image sequences from stochastically blinking emitters using a standard wide-field fluorescence microscope.
    • Application of high-precision localization algorithms (e.g., PALM, STORM) for single-molecule analysis.
    • Analysis of temporal fluctuation statistics using the Super-resolution Optical Fluctuation Imaging (SOFI) method.

    Main Results:

    • Localization-based methods achieve higher resolution but are limited by strict probe blinking requirements, hindering live-cell applications.
    • SOFI demonstrates consistent performance across diverse photo-switching kinetics and provides insights into blinking statistics.
    • SOFI is effective even in low signal-to-noise ratio (SNR) conditions, indicating its potential for high-speed imaging.

    Conclusions:

    • SOFI is a versatile super-resolution technique that overcomes limitations of localization-based methods, particularly for live-cell imaging.
    • The robustness of SOFI to varying blinking behaviors makes it a more adaptable tool for biological research.
    • SOFI's suitability for low SNR and high-speed acquisition positions it as a promising technique for dynamic biological processes.