Universal inverse modelling of point spread functions for SMLM localization and microscope characterization.
Journal
bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187
Informations de publication
Date de publication:
26 Oct 2023
26 Oct 2023
Historique:
pubmed:
14
11
2023
medline:
14
11
2023
entrez:
14
11
2023
Statut:
epublish
Résumé
The point spread function (PSF) of a microscope describes the image of a point emitter. Knowing the accurate PSF model is essential for various imaging tasks, including single molecule localization, aberration correction and deconvolution. Here we present uiPSF (universal inverse modelling of Point Spread Functions), a toolbox to infer accurate PSF models from microscopy data, using either image stacks of fluorescent beads or directly images of blinking fluorophores, the raw data in single molecule localization microscopy (SMLM). The resulting PSF model enables accurate 3D super-resolution imaging using SMLM. Additionally, uiPSF can be used to characterize and optimize a microscope system by quantifying the aberrations, including field-dependent aberrations, and resolutions. Our modular framework is applicable to a variety of microscope modalities and the PSF model incorporates system or sample specific characteristics, e.g., the bead size, depth dependent aberrations and transformations among channels. We demonstrate its application in single or multiple channels or large field-of-view SMLM systems, 4Pi-SMLM, and lattice light-sheet microscopes using either bead data or single molecule blinking data.
Identifiants
pubmed: 37961269
doi: 10.1101/2023.10.26.564064
pmc: PMC10634843
pii:
doi:
Types de publication
Preprint
Langues
eng
Subventions
Organisme : NIGMS NIH HHS
ID : R01 GM140284
Pays : United States
Organisme : NCATS NIH HHS
ID : R13 TR001278
Pays : United States
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