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    This study introduces a single-pixel compressive sensing architecture for microscopy, reducing data acquisition by 10x and overcoming scattering limitations. An adaptive sampling method further enhances speed and compression for advanced imaging.

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    Area of Science:

    • Optics and Photonics
    • Biomedical Imaging
    • Signal Processing

    Background:

    • Conventional widefield temporal focusing microscopes face limitations due to fluorescence signal scattering.
    • High data acquisition rates in microscopy can be computationally demanding and slow.

    Purpose of the Study:

    • To develop a novel microscopy architecture for reduced data acquisition and improved performance.
    • To overcome scattering limitations inherent in current widefield temporal focusing microscopy techniques.

    Main Methods:

    • Exploitation of a single-pixel compressive sensing architecture.
    • Implementation of an adaptive sampling scheme to optimize data acquisition.
    • Simultaneous data reduction and mitigation of scattering effects.

    Main Results:

    • Achieved a 10× reduction in acquired data compared to the Nyquist rate.
    • Successfully alleviated limitations caused by fluorescence signal scattering.
    • Demonstrated further improvements in compression and speed using an adaptive sampling scheme.

    Conclusions:

    • The single-pixel compressive sensing architecture offers significant advantages for microscopy.
    • The adaptive sampling scheme enhances the efficiency and applicability of this novel approach.
    • This method provides a promising solution for high-speed, high-resolution imaging in scattering media.