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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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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. |
format | Online Article Text |
id | pubmed-10634843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
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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