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dc.contributor.author
Ioanas, Horea-Ioan
dc.contributor.author
Marks, Markus
dc.contributor.author
Garin, Clément M.
dc.contributor.author
Dhenain, Marc
dc.contributor.author
Yanik, Mehmet Fatih
dc.contributor.author
Rudin, Markus
dc.date.accessioned
2020-01-28T11:30:59Z
dc.date.available
2020-01-27T15:05:41Z
dc.date.available
2020-01-28T11:30:59Z
dc.date.issued
2019-06-12
dc.identifier.other
10.1101/667980
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/394461
dc.identifier.doi
10.3929/ethz-b-000394461
dc.description.abstract
Large-scale research integration is contingent on seamless access to data in standardized formats. Standards enable researchers to understand external experiment structures, pool results, and apply homogeneous preprocessing and analysis workflows. Particularly, they facilitate these features without the need for numerous potentially confounding compatibility add-ons. In small animal magnetic resonance imaging, an overwhelming proportion of data is acquired via the ParaVision software of the Bruker Corporation. The original data structure is predominantly transparent, but fundamentally incompatible with modern pipelines. Additionally, it sources metadata from free-field operator input, which diverges strongly between laboratories and researchers. In this article we present an open-source workflow which automatically converts and reposits data from the ParaVision structure into the widely supported and openly documented Brain Imaging Data Structure (BIDS). Complementing this workflow we also present operator guidelines for appropriate ParaVision data input, and a programmatic walk-through detailing how preexisting scans with uninterpretable metadata records can easily be made compliant after the acquisition.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Cold Spring Harbor Laboratory
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
fMRI
en_US
dc.subject
MRI
en_US
dc.subject
Standardization
en_US
dc.subject
Repositing
en_US
dc.subject
Data structures
en_US
dc.subject
Small animal imaging
en_US
dc.subject
Mouse
en_US
dc.subject
Rat
en_US
dc.subject
Mouse lemur
en_US
dc.subject
Rodent
en_US
dc.subject
Primate
en_US
dc.subject
Biomedical engineering
en_US
dc.subject
FOSS
en_US
dc.subject
BIDS
en_US
dc.subject
Bruker
en_US
dc.subject
ParaVision
en_US
dc.subject
Operator guidelines
en_US
dc.subject
Python
en_US
dc.subject
Bash
en_US
dc.title
An Automated Open-Source Workflow for Standards-Compliant Integration of Small Animal Magnetic Resonance Imaging Data
en_US
dc.type
Working Paper
dc.rights.license
Creative Commons Attribution 4.0 International
ethz.journal.title
bioRxiv
ethz.size
11 p.
en_US
ethz.publication.place
Cold Spring Harbor, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02533 - Institut für Neuroinformatik / Institute of Neuroinformatics::09474 - Yanik, Mehmet Fatih / Yanik, Mehmet Fatih
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02533 - Institut für Neuroinformatik / Institute of Neuroinformatics::09474 - Yanik, Mehmet Fatih / Yanik, Mehmet Fatih
en_US
ethz.date.deposited
2020-01-27T15:05:48Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-01-28T11:31:10Z
ethz.rosetta.lastUpdated
2020-02-15T23:53:28Z
ethz.rosetta.versionExported
true
ethz.COinS
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