Large-FOV 3D localization microscopy by spatially variant point spread function generation

Area of Science:

• Optical microscopy
• Super-resolution imaging
• Biophysics

Background:

• Accurate point spread function (PSF) characterization is essential for high-performance localization microscopy (LM).
• Traditional LM often assumes a spatially invariant PSF, which limits performance in large field-of-view (FOV) imaging.
• Accounting for spatially variant PSFs is critical for advanced LM applications.

Purpose of the Study:

• To introduce an accurate and fast principal components analysis-based field-dependent 3D PSF generator and localizer (PPG3D).
• To enable high-fidelity super-resolution imaging over large FOVs in 3D single-molecule localization microscopy (SMLM).

Main Methods:

• Development of PPG3D, a novel algorithm utilizing principal components analysis for PSF generation.
• Validation through simulations and experimental 3D SMLM imaging.
• Comparison with existing shift-variant PSF generators.

Main Results:

• PPG3D demonstrates effectiveness in super-resolution imaging of cellular structures (mitochondria, microtubules) with high fidelity over large FOVs.
• Achieved a threefold improvement in accuracy compared to a standard shift-variant PSF generator.
• PPG3D is approximately 100 times faster than existing PSF generators in image plane-based interpolation mode.

Conclusions:

• PPG3D provides an accurate and efficient solution for handling spatially variant PSFs in 3D SMLM.
• The user-friendliness and speed of PPG3D suggest broad applicability in SMLM and other imaging modalities.
• This method enhances the capability of localization microscopy for large-scale biological imaging.