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Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
Sheng Liu1, Jianwei Chen2,3, Jonas Hellgoth4
1Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM, USA.
Biorxiv : the Preprint Server for Biology
|November 14, 2023
Summary
Accurate microscope point spread function (PSF) models are crucial for super-resolution imaging. The uiPSF toolbox infers precise PSF models from microscopy data, enabling advanced 3D super-resolution imaging and system characterization.
Area of Science:
- Microscopy
- Optical Imaging
- Computational Biology
Background:
- The point spread function (PSF) models how a microscope images a point source, critical for image analysis.
- Accurate PSF models are essential for single molecule localization microscopy (SMLM), deconvolution, and aberration correction.
- Existing methods may lack universality or require specific data types for PSF inference.
Conclusions:
- The uiPSF toolbox provides a universal and accurate method for PSF model inference in microscopy.
- Accurate PSF modeling significantly enhances 3D super-resolution imaging capabilities and microscope characterization.
- The framework's modularity and applicability to diverse systems make it a valuable tool for optical imaging research.
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