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A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
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    Area of Science:

    • Microscopy
    • Superresolution Imaging
    • Computational Imaging

    Background:

    • Structured illumination microscopy (SIM) typically requires numerous raw frames for reconstruction.
    • Previous SIM algorithms often record redundant spatial frequency data.
    • Faster and gentler superresolution imaging techniques are needed.

    Purpose of the Study:

    • To introduce a theoretical framework for widefield SIM reconstruction using fewer than nine raw frames.
    • To enable faster and gentler superresolution imaging by avoiding redundant data acquisition.
    • To investigate the impact of sample movement and frame count on reconstruction quality.

    Main Methods:

    • Developed a novel theoretical framework for SIM reconstruction.
    • Applied the framework in silico and in vitro.
    • Numerically explored the effects of sample movement and frame reduction.
    • Compared SIM performance against deconvolution microscopy.

    Main Results:

    • The proposed scheme reconstructs SIM images from fewer raw frames, avoiding redundant spatial frequency components.
    • Achieved a doubling of frame rates through computational reconstruction modifications.
    • Identified a limit where deconvolution microscopy surpasses SIM in performance based on sample movement and frame count.

    Conclusions:

    • A new computational approach allows for faster and gentler widefield SIM.
    • Optimizing frame acquisition and reconstruction is crucial for superresolution imaging.
    • Deconvolution microscopy may be preferable to SIM under specific conditions of sample movement and reduced frame rates.