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Updated: Jan 1, 2026

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors
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Jointly super-resolved and optically sectioned Bayesian reconstruction method for structured illumination microscopy.

Yann Lai-Tim, Laurent M Mugnier, François Orieux

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    |December 28, 2019
    PubMed
    Summary
    This summary is machine-generated.

    BOSSA-SIM, a new Structured Illumination Microscopy (SIM) method, achieves super-resolution and optical sectioning for moving biological samples. This unsupervised Bayesian framework effectively reconstructs in-focus details from complex imaging data.

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    Super-resolution Imaging of the Cytokinetic Z Ring in Live Bacteria Using Fast 3D-Structured Illumination Microscopy f3D-SIM

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    Area of Science:

    • Microscopy and Imaging Technologies
    • Biophysics
    • Computational Imaging

    Background:

    • Structured Illumination Microscopy (SIM) combines super-resolution (SR) and optical sectioning (OS) in wide-field microscopy.
    • SIM illuminates samples with patterned light at various orientations and positions, followed by image reconstruction.
    • Current methods often struggle with dynamic samples, limiting applications in live biological imaging.

    Purpose of the Study:

    • To introduce BOSSA-SIM, a versatile SIM reconstruction method for simultaneous SR and OS.
    • To enable high-quality imaging of moving specimens, particularly in in vivo retinal imaging.
    • To develop a fully unsupervised Bayesian framework for robust SIM reconstruction.

    Main Methods:

    • Developed BOSSA-SIM, a general-purpose SIM reconstruction algorithm.
    • Employed a 2-layer object model (in-focus and defocused layers) within a Bayesian framework.
    • Utilized an unsupervised approach for image reconstruction, eliminating the need for manual parameter tuning.

    Main Results:

    • BOSSA-SIM successfully achieved joint super-resolution and optical sectioning of the in-focus layer.
    • The method demonstrated effective reconstruction of moving objects, validated by simulations across various noise levels.
    • Quantitative performance assessment showed favorable comparison against a state-of-the-art reconstruction technique.

    Conclusions:

    • BOSSA-SIM offers a powerful, unsupervised solution for simultaneous SR and OS in SIM.
    • The method is applicable to dynamic biological samples, advancing in vivo imaging capabilities.
    • Validation on experimental data confirms the practical utility and performance of BOSSA-SIM.