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Single-molecule localization software applied to photon counting imaging.

Liisa M Hirvonen, Tiffany Kilfeather, Klaus Suhling

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    Summary
    This summary is machine-generated.

    Single-molecule localization software effectively identifies photon events in photon counting imaging. This approach offers excellent event recognition and low noise, improving imaging resolution.

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    Area of Science:

    • Optics and Imaging Science
    • Biophysics
    • Microscopy Techniques

    Background:

    • Photon counting imaging traditionally uses simple hardware-based algorithms for centroiding.
    • Superresolution fluorescence microscopy employs advanced iterative algorithms for single-molecule localization.

    Purpose of the Study:

    • To investigate the applicability of single-molecule localization software for photon event localization in photon counting imaging.
    • To compare the performance of established single-molecule localization algorithms with traditional photon counting methods.

    Main Methods:

    • Applied established single-molecule localization software (QuickPALM, rapidSTORM, ThunderSTORM) to photon counting imaging data.
    • Utilized a microchannel-plate-based intensified camera system for data acquisition.
    • Evaluated photon event recognition, fixed pattern noise, and resolution of microchannel plate pores.

    Main Results:

    • Single-molecule localization software packages demonstrated effective photon event recognition.
    • Low levels of fixed pattern noise were observed.
    • High-resolution imaging of microchannel plate pores was achieved.

    Conclusions:

    • Single-molecule localization software is suitable for enhancing photon event localization in photon counting imaging.
    • This software-based approach offers advantages over traditional hardware-based methods, improving image quality and detail.