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Automated sensorless single-shot closed-loop adaptive optics microscopy with feedback from computational adaptive

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    This summary is machine-generated.

    Computational adaptive optics (CAO) simulates deformable mirror states, reducing image acquisition for aberration correction in scattering samples. This method enhances optical coherence microscopy performance in dynamic biological imaging.

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    Area of Science:

    • Biomedical Optics
    • Microscopy
    • Optical Engineering

    Background:

    • Traditional wavefront-sensor adaptive optics (AO) struggles with scattering samples.
    • Sensorless AO requires extensive image acquisition, unsuitable for dynamic samples.

    Purpose of the Study:

    • To present a computational adaptive optics (CAO) technique for aberration correction.
    • To overcome limitations of sensor-based and traditional sensorless AO methods.

    Main Methods:

    • Simulating deformable mirror states using CAO instead of physical measurements.
    • Estimating optimal wavefront by minimizing an image metric via CAO.
    • Translating the optimized CAO pattern to a physical deformable mirror.

    Main Results:

    • Demonstrated CAO-based AO on spectral-domain optical coherence microscopy.
    • Achieved real-time depth-wise aberration correction.
    • Enabled single-shot volumetric aberration correction and extended depth-of-focus.

    Conclusions:

    • The CAO technique reduces image acquisition compared to sensorless AO.
    • It combines advantages of both computational and hardware-based AO.
    • This method improves AO performance in scattering and dynamic samples.