Universal inverse modeling of point spread functions for SMLM localization and microscope characterization

Area of Science:

• Microscopy
• Optical Imaging
• Computational Imaging

Background:

• Accurate point spread function (PSF) modeling is crucial for advanced microscopy techniques.
• Existing PSF models may not capture system-specific aberrations or sample characteristics.

Purpose of the Study:

• To introduce universal inverse modeling of point spread functions (uiPSF), a versatile toolbox for inferring accurate PSF models.
• To provide a framework applicable to diverse microscopy modalities and data types.

Main Methods:

• The uiPSF toolbox infers PSF models using image stacks of fluorescent beads or blinking fluorophores.
• The framework incorporates system- and sample-specific aberrations, bead size, and channel transformations.
• It is designed as a modular framework for broad applicability.

Main Results:

• Demonstrated successful application of uiPSF across various microscopy systems, including SMLM, 4Pi-SMLM, and lattice light-sheet microscopes.
• Validated the toolbox using both bead and single-molecule blinking data.
• Showcased the ability to model complex aberrations and channel-specific characteristics.

Conclusions:

• The uiPSF toolbox offers a universal and accurate method for PSF modeling in microscopy.
• This tool enhances the performance of critical imaging tasks like single-molecule localization and deconvolution.
• It provides a flexible solution for diverse imaging needs in super-resolution microscopy.