Phase-based computational adaptive optics enables artifact-free super-resolution microscopy.

Area of Science:

• Biomedical Engineering
• Optical Microscopy
• Computational Imaging

Background:

• Adaptive optics (AO) enhances microscopy resolution and signal-to-noise ratio.
• Current AO methods require complex hardware and can cause phototoxicity, limiting widespread use.
• There is a need for accessible AO solutions in biological imaging.

Purpose of the Study:

• To introduce ∅CAO, a computational phase-based AO technique.
• To enable aberration correction in 3D fluorescence microscopy without specialized optics or training data.
• To improve the accessibility and scalability of AO for life sciences.

Main Methods:

• Utilized phase transfer functions in the frequency domain for aberration correction.
• Developed a computational approach for post-acquisition image correction.
• Applied the technique to diverse imaging modalities like wide-field and structured illumination microscopy.

Main Results:

• Achieved substantial improvements in image fidelity and resolution.
• Demonstrated robust performance under noisy imaging conditions.
• Successfully corrected optical aberrations in biological specimens, including C. elegans and plant tissues.

Conclusions:

• ∅CAO provides a scalable and accessible solution for high-resolution biological imaging.
• The computational, phase-based approach overcomes limitations of traditional AO hardware.
• Facilitates broader adoption of advanced AO techniques in life science research.