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Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection

As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain hi...

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Autores principales: Gürsoy, Doğa, Hong, Young P., He, Kuan, Hujsak, Karl, Yoo, Seunghwan, Chen, Si, Li, Yue, Ge, Mingyuan, Miller, Lisa M., Chu, Yong S., De Andrade, Vincent, He, Kai, Cossairt, Oliver, Katsaggelos, Aggelos K., Jacobsen, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5603591/
https://www.ncbi.nlm.nih.gov/pubmed/28924196
http://dx.doi.org/10.1038/s41598-017-12141-9
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author Gürsoy, Doğa
Hong, Young P.
He, Kuan
Hujsak, Karl
Yoo, Seunghwan
Chen, Si
Li, Yue
Ge, Mingyuan
Miller, Lisa M.
Chu, Yong S.
De Andrade, Vincent
He, Kai
Cossairt, Oliver
Katsaggelos, Aggelos K.
Jacobsen, Chris
author_facet Gürsoy, Doğa
Hong, Young P.
He, Kuan
Hujsak, Karl
Yoo, Seunghwan
Chen, Si
Li, Yue
Ge, Mingyuan
Miller, Lisa M.
Chu, Yong S.
De Andrade, Vincent
He, Kai
Cossairt, Oliver
Katsaggelos, Aggelos K.
Jacobsen, Chris
author_sort Gürsoy, Doğa
collection PubMed
description As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography.
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spelling pubmed-56035912017-09-20 Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection Gürsoy, Doğa Hong, Young P. He, Kuan Hujsak, Karl Yoo, Seunghwan Chen, Si Li, Yue Ge, Mingyuan Miller, Lisa M. Chu, Yong S. De Andrade, Vincent He, Kai Cossairt, Oliver Katsaggelos, Aggelos K. Jacobsen, Chris Sci Rep Article As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography. Nature Publishing Group UK 2017-09-18 /pmc/articles/PMC5603591/ /pubmed/28924196 http://dx.doi.org/10.1038/s41598-017-12141-9 Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Gürsoy, Doğa
Hong, Young P.
He, Kuan
Hujsak, Karl
Yoo, Seunghwan
Chen, Si
Li, Yue
Ge, Mingyuan
Miller, Lisa M.
Chu, Yong S.
De Andrade, Vincent
He, Kai
Cossairt, Oliver
Katsaggelos, Aggelos K.
Jacobsen, Chris
Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
title Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
title_full Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
title_fullStr Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
title_full_unstemmed Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
title_short Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
title_sort rapid alignment of nanotomography data using joint iterative reconstruction and reprojection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5603591/
https://www.ncbi.nlm.nih.gov/pubmed/28924196
http://dx.doi.org/10.1038/s41598-017-12141-9
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