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

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...

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Autores principales: Liu, Sheng, Chen, Jianwei, Hellgoth, Jonas, Müller, Lucas-Raphael, Ferdman, Boris, Karras, Christian, Xiao, Dafei, Lidke, Keith A., Heintzmann, Rainer, Shechtman, Yoav, Li, Yiming, Ries, Jonas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634843/
https://www.ncbi.nlm.nih.gov/pubmed/37961269
http://dx.doi.org/10.1101/2023.10.26.564064
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author Liu, Sheng
Chen, Jianwei
Hellgoth, Jonas
Müller, Lucas-Raphael
Ferdman, Boris
Karras, Christian
Xiao, Dafei
Lidke, Keith A.
Heintzmann, Rainer
Shechtman, Yoav
Li, Yiming
Ries, Jonas
author_facet Liu, Sheng
Chen, Jianwei
Hellgoth, Jonas
Müller, Lucas-Raphael
Ferdman, Boris
Karras, Christian
Xiao, Dafei
Lidke, Keith A.
Heintzmann, Rainer
Shechtman, Yoav
Li, Yiming
Ries, Jonas
author_sort Liu, Sheng
collection PubMed
description 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.
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spelling pubmed-106348432023-11-13 Universal inverse modelling of point spread functions for SMLM localization and microscope characterization Liu, Sheng Chen, Jianwei Hellgoth, Jonas Müller, Lucas-Raphael Ferdman, Boris Karras, Christian Xiao, Dafei Lidke, Keith A. Heintzmann, Rainer Shechtman, Yoav Li, Yiming Ries, Jonas bioRxiv Article 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. Cold Spring Harbor Laboratory 2023-10-26 /pmc/articles/PMC10634843/ /pubmed/37961269 http://dx.doi.org/10.1101/2023.10.26.564064 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Article
Liu, Sheng
Chen, Jianwei
Hellgoth, Jonas
Müller, Lucas-Raphael
Ferdman, Boris
Karras, Christian
Xiao, Dafei
Lidke, Keith A.
Heintzmann, Rainer
Shechtman, Yoav
Li, Yiming
Ries, Jonas
Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
title Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
title_full Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
title_fullStr Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
title_full_unstemmed Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
title_short Universal inverse modelling of point spread functions for SMLM localization and microscope characterization
title_sort universal inverse modelling of point spread functions for smlm localization and microscope characterization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634843/
https://www.ncbi.nlm.nih.gov/pubmed/37961269
http://dx.doi.org/10.1101/2023.10.26.564064
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