Cargando…

A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source

Tomographic datasets collected at synchrotrons are becoming very large and complex, and, therefore, need to be managed efficiently. Raw images may have high pixel counts, and each pixel can be multidimensional and associated with additional data such as those derived from spectroscopy. In time-resol...

Descripción completa

Detalles Bibliográficos
Autores principales: Atwood, Robert C., Bodey, Andrew J., Price, Stephen W. T., Basham, Mark, Drakopoulos, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424489/
https://www.ncbi.nlm.nih.gov/pubmed/25939626
http://dx.doi.org/10.1098/rsta.2014.0398
_version_ 1782370334265049088
author Atwood, Robert C.
Bodey, Andrew J.
Price, Stephen W. T.
Basham, Mark
Drakopoulos, Michael
author_facet Atwood, Robert C.
Bodey, Andrew J.
Price, Stephen W. T.
Basham, Mark
Drakopoulos, Michael
author_sort Atwood, Robert C.
collection PubMed
description Tomographic datasets collected at synchrotrons are becoming very large and complex, and, therefore, need to be managed efficiently. Raw images may have high pixel counts, and each pixel can be multidimensional and associated with additional data such as those derived from spectroscopy. In time-resolved studies, hundreds of tomographic datasets can be collected in sequence, yielding terabytes of data. Users of tomographic beamlines are drawn from various scientific disciplines, and many are keen to use tomographic reconstruction software that does not require a deep understanding of reconstruction principles. We have developed Savu, a reconstruction pipeline that enables users to rapidly reconstruct data to consistently create high-quality results. Savu is designed to work in an ‘orthogonal’ fashion, meaning that data can be converted between projection and sinogram space throughout the processing workflow as required. The Savu pipeline is modular and allows processing strategies to be optimized for users' purposes. In addition to the reconstruction algorithms themselves, it can include modules for identification of experimental problems, artefact correction, general image processing and data quality assessment. Savu is open source, open licensed and ‘facility-independent’: it can run on standard cluster infrastructure at any institution.
format Online
Article
Text
id pubmed-4424489
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher The Royal Society Publishing
record_format MEDLINE/PubMed
spelling pubmed-44244892015-06-13 A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source Atwood, Robert C. Bodey, Andrew J. Price, Stephen W. T. Basham, Mark Drakopoulos, Michael Philos Trans A Math Phys Eng Sci Articles Tomographic datasets collected at synchrotrons are becoming very large and complex, and, therefore, need to be managed efficiently. Raw images may have high pixel counts, and each pixel can be multidimensional and associated with additional data such as those derived from spectroscopy. In time-resolved studies, hundreds of tomographic datasets can be collected in sequence, yielding terabytes of data. Users of tomographic beamlines are drawn from various scientific disciplines, and many are keen to use tomographic reconstruction software that does not require a deep understanding of reconstruction principles. We have developed Savu, a reconstruction pipeline that enables users to rapidly reconstruct data to consistently create high-quality results. Savu is designed to work in an ‘orthogonal’ fashion, meaning that data can be converted between projection and sinogram space throughout the processing workflow as required. The Savu pipeline is modular and allows processing strategies to be optimized for users' purposes. In addition to the reconstruction algorithms themselves, it can include modules for identification of experimental problems, artefact correction, general image processing and data quality assessment. Savu is open source, open licensed and ‘facility-independent’: it can run on standard cluster infrastructure at any institution. The Royal Society Publishing 2015-06-13 /pmc/articles/PMC4424489/ /pubmed/25939626 http://dx.doi.org/10.1098/rsta.2014.0398 Text en http://creativecommons.org/licenses/by/4.0/ © 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Atwood, Robert C.
Bodey, Andrew J.
Price, Stephen W. T.
Basham, Mark
Drakopoulos, Michael
A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source
title A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source
title_full A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source
title_fullStr A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source
title_full_unstemmed A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source
title_short A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source
title_sort high-throughput system for high-quality tomographic reconstruction of large datasets at diamond light source
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4424489/
https://www.ncbi.nlm.nih.gov/pubmed/25939626
http://dx.doi.org/10.1098/rsta.2014.0398
work_keys_str_mv AT atwoodrobertc ahighthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT bodeyandrewj ahighthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT pricestephenwt ahighthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT bashammark ahighthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT drakopoulosmichael ahighthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT atwoodrobertc highthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT bodeyandrewj highthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT pricestephenwt highthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT bashammark highthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource
AT drakopoulosmichael highthroughputsystemforhighqualitytomographicreconstructionoflargedatasetsatdiamondlightsource