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Homographically generated light sheets for the microscopy of large specimens
We compare the performance of linear and nonlinear methods for aligning the excitation and detection planes throughout volumes of large specimens in digitally scanned light sheet microscopy. An effective nonlinear method involves the registration of four corner extrema of the imaging volume via a pr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Optical Society of America
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862512/ https://www.ncbi.nlm.nih.gov/pubmed/29444047 http://dx.doi.org/10.1364/OL.43.000663 |
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author | Russell, Craig T. Rees, Eric J. Kaminski, Clemens F. |
author_facet | Russell, Craig T. Rees, Eric J. Kaminski, Clemens F. |
author_sort | Russell, Craig T. |
collection | PubMed |
description | We compare the performance of linear and nonlinear methods for aligning the excitation and detection planes throughout volumes of large specimens in digitally scanned light sheet microscopy. An effective nonlinear method involves the registration of four corner extrema of the imaging volume via a projective transform. We show that this improves the light collection efficiency of the commonly used three-point affine registration by an average of 42% over a typical specimen volume. Accurate illumination/detection registration methods are now pertinent to biological research in view of current trends towards imaging large or expanded samples, at depth, with diffraction limited resolution. |
format | Online Article Text |
id | pubmed-5862512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Optical Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-58625122018-04-12 Homographically generated light sheets for the microscopy of large specimens Russell, Craig T. Rees, Eric J. Kaminski, Clemens F. Opt Lett Article We compare the performance of linear and nonlinear methods for aligning the excitation and detection planes throughout volumes of large specimens in digitally scanned light sheet microscopy. An effective nonlinear method involves the registration of four corner extrema of the imaging volume via a projective transform. We show that this improves the light collection efficiency of the commonly used three-point affine registration by an average of 42% over a typical specimen volume. Accurate illumination/detection registration methods are now pertinent to biological research in view of current trends towards imaging large or expanded samples, at depth, with diffraction limited resolution. Optical Society of America 2018-02-06 /pmc/articles/PMC5862512/ /pubmed/29444047 http://dx.doi.org/10.1364/OL.43.000663 Text en Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/) . Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. 0146-9592/18/040663-04 |
spellingShingle | Article Russell, Craig T. Rees, Eric J. Kaminski, Clemens F. Homographically generated light sheets for the microscopy of large specimens |
title | Homographically generated light sheets for the microscopy of large specimens |
title_full | Homographically generated light sheets for the microscopy of large specimens |
title_fullStr | Homographically generated light sheets for the microscopy of large specimens |
title_full_unstemmed | Homographically generated light sheets for the microscopy of large specimens |
title_short | Homographically generated light sheets for the microscopy of large specimens |
title_sort | homographically generated light sheets for the microscopy of large specimens |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862512/ https://www.ncbi.nlm.nih.gov/pubmed/29444047 http://dx.doi.org/10.1364/OL.43.000663 |
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