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    Super-resolution microscopy requires precise drift correction for high-quality images. This study introduces relative localization precision to evaluate drift correction methods for super-resolution localization microscopy (SRLM).

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    Area of Science:

    • Optical microscopy
    • Biophysics
    • Image processing

    Background:

    • Super-resolution localization microscopy (SRLM) significantly enhances optical imaging resolution.
    • SRLM requires extensive image acquisition, making it susceptible to system drift.
    • Existing drift correction methods lack clear performance evaluation for SRLM.

    Purpose of the Study:

    • To investigate the impact of drift correction precision on SRLM imaging quality.
    • To establish a framework for selecting appropriate drift correction methods for specific SRLM experiments.

    Main Methods:

    • Theoretical analysis of the relationship between drift correction, localization, and position estimation precision.
    • Computer simulations to model and evaluate drift correction performance.
    • Introduction of the concept of relative localization precision.

    Main Results:

    • Quantified the relationship between drift correction precision and localization precision.
    • Demonstrated how drift affects overall position estimation precision in SRLM.
    • Validated the utility of relative localization precision for method selection.

    Conclusions:

    • Drift correction is critical for achieving high-resolution images in SRLM.
    • Relative localization precision provides a quantitative metric for evaluating drift correction efficacy.
    • This work aids researchers in selecting optimal drift correction strategies for their SRLM applications.