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Related Experiment Video

Updated: May 13, 2025

Three-Dimensional Imaging of Tumor-Bearing Tissue Using the Iterative Bleaching Extends Multiplexity Approach
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Fourier-Based 3D Multistage Transformer for Aberration Correction in Multicellular Specimens.

Thayer Alshaabi, Daniel Milkie, Gaoxiang Liu

    Research Square
    |April 16, 2025
    PubMed
    Summary
    This summary is machine-generated.

    We developed AOViFT, a machine learning tool that corrects optical aberrations in high-resolution microscopy. This AI-powered approach simplifies imaging, making advanced techniques more accessible for biological research.

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    Area of Science:

    • Microscopy
    • Biophysics
    • Machine Learning

    Background:

    • Optical aberrations degrade image quality in high-resolution tissue imaging.
    • Conventional adaptive optics (AO) solutions are complex, costly, and slow for large-scale aberration correction.

    Purpose of the Study:

    • To introduce AOViFT (Adaptive Optical Vision Fourier Transformer), a novel machine learning framework for aberration sensing and correction.
    • To reduce the computational cost and complexity associated with aberration correction in microscopy.

    Main Methods:

    • Developed a 3D multistage Vision Transformer operating on Fourier domain embeddings.
    • Implemented AOViFT for aberration inference and restoration of diffraction-limited performance.
    • Validated the framework on live gene-edited zebrafish embryos.

    Main Results:

    • AOViFT achieved aberration correction with reduced computational cost, training time, and memory footprint compared to traditional methods.
    • Demonstrated successful correction of spatially varying aberrations using both hardware (deformable mirror) and software (post-acquisition deconvolution) approaches.
    • Validated performance on live biological samples, showcasing its practical applicability.

    Conclusions:

    • AOViFT offers an efficient, AI-driven solution for correcting optical aberrations in microscopy.
    • The framework simplifies experimental workflows by eliminating the need for guide stars and wavefront sensing hardware.
    • AOViFT lowers technical barriers, enhancing accessibility to high-resolution volumetric microscopy for diverse biological applications.