Ultrahigh accuracy imaging modality for super-localization microscopy
Ultrahigh accuracy imaging modality for super-localization microscopy
Super-localization microscopy encompasses techniques that depend on the accurate localization of individual molecules from generally low-light images. The obtainable localization accuracies, however, are ultimately limited by the image detector's pixelation and noise. We present the ultrahigh accuracy imaging modality (UAIM), which allows users to obtain accuracies approaching the accuracy that is achievable only in the absence of detector pixelation and noise, and which we found can experimentally provide a >200% accuracy improvement over conventional low-light imaging.
335-338
Chao, Jerry
550e20b0-8365-42e3-a6fc-1048eb8c2e47
Ram, Sripad
559bd560-3817-4e53-8c7a-2f08e4518412
Ward, E. Sally
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
April 2013
Chao, Jerry
550e20b0-8365-42e3-a6fc-1048eb8c2e47
Ram, Sripad
559bd560-3817-4e53-8c7a-2f08e4518412
Ward, E. Sally
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
Chao, Jerry, Ram, Sripad, Ward, E. Sally and Ober, Raimund J.
(2013)
Ultrahigh accuracy imaging modality for super-localization microscopy.
Nature Methods, 10 (4), .
(doi:10.1038/nmeth.2396).
Abstract
Super-localization microscopy encompasses techniques that depend on the accurate localization of individual molecules from generally low-light images. The obtainable localization accuracies, however, are ultimately limited by the image detector's pixelation and noise. We present the ultrahigh accuracy imaging modality (UAIM), which allows users to obtain accuracies approaching the accuracy that is achievable only in the absence of detector pixelation and noise, and which we found can experimentally provide a >200% accuracy improvement over conventional low-light imaging.
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Accepted/In Press date: 18 January 2013
e-pub ahead of print date: 3 March 2013
Published date: April 2013
Identifiers
Local EPrints ID: 423642
URI: http://eprints.soton.ac.uk/id/eprint/423642
ISSN: 1548-7091
PURE UUID: f6bd799e-5184-46a4-905a-2e675dcdeb2b
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Date deposited: 27 Sep 2018 16:30
Last modified: 18 Mar 2024 03:48
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Author:
Jerry Chao
Author:
Sripad Ram
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