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

Sheng Liu1,2, Jianwei Chen3,4, Jonas Hellgoth2,5

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Summary

We developed a universal inverse modeling of point spread functions (uiPSF) toolbox. This tool accurately models microscope point spread functions from various imaging data for enhanced microscopy applications.

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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.