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  Nighres: Processing tools for high-resolution neuroimaging

Huntenburg, J. M., Steele, C., & Bazin, P.-L. (2018). Nighres: Processing tools for high-resolution neuroimaging. GigaScience, 7(7): giy082. doi:10.1093/gigascience/giy082.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0001-BF08-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0003-94B5-9
Genre: Journal Article

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 Creators:
Huntenburg, Julia M.1, 2, Author           
Steele, Christopher3, 4, Author           
Bazin, Pierre-Louis3, 5, 6, Author           
Affiliations:
1Max Planck Research Group Neuroanatomy and Connectivity, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_1356546              
2Neurocomputation and Neuroimaging Unit, FU Berlin, Germany, ou_persistent22              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
4Cerebral Imaging Center, Douglas Mental Health University Institute, McGill University, Montréal, QC, Canada, ou_persistent22              
5Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_634550              
6Department of Psychology, University of Amsterdam, the Netherlands, ou_persistent22              

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Free keywords: Neuroimaging in Python; High-resolution MRI; Ultra-high field MRI; Laminar MRI; Python Java integration
 Abstract: With recent improvements in human magnetic resonance imaging (MRI) at ultra-high fields, the amount of data collected per subject in a given MRI experiment has increased considerably. Standard image processing packages are often challenged by the size of these data and dedicated methods are needed to leverage their extraordinary spatial resolution. Here we introduce a flexible Python toolbox which implements a set of advanced techniques for high-resolution neuroimaging. With these tools, segmentation and laminar analysis of cortical MRI data can be performed at resolutions up to 500 μm in reasonable times. Comprehensive online documentation makes the toolbox easy to use and install. An extensive developer’s guide encourages contributions of other researchers that will help to accelerate progress in the promising field of high-resolution neuroimaging.

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Language(s): eng - English
 Dates: 2018-06-262018-06-272018-06-292018-07-04
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1093/gigascience/giy082
PMC: PMC6065481
PMID: 29982501
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Funding program : Google Summer of Code 2017 Program
Funding organization : Google
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Funding organization : International Neuroinformatics Coordinating Facility (INCF)

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Title: GigaScience
Source Genre: Journal
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Publ. Info: London : BioMed Central
Pages: - Volume / Issue: 7 (7) Sequence Number: giy082 Start / End Page: - Identifier: ISSN: 2047-217X
CoNE: https://pure.mpg.de/cone/journals/resource/2047-217X