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  Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI

Keuken, M., Bazin, P.-L., Crown, L., Hootsmans, J., Laufer, A., Müller-Axt, C., et al. (2014). Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI. NeuroImage, 94, 40-46. doi:10.1016/j.neuroimage.2014.03.032.

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 Creators:
Keuken, Max1, Author
Bazin, Pierre-Louis2, 3, Author           
Crown, L.1, Author
Hootsmans, J.1, Author
Laufer, A.1, Author
Müller-Axt, Christa1, Author           
Sier, R.1, Author
van der Putten, E. J.1, Author
Schäfer, Andreas2, Author           
Turner, Robert2, Author           
Forstmann, Birte U.1, Author           
Affiliations:
1Cognitive Science Center Amsterdam, University of Amsterdam, the Netherlands, ou_persistent22              
2Department Neurophysics, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634550              
3Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_634549              

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Free keywords: Anatomical atlas; Basal Ganglia; Subthalamic Nucleus; Substantia Nigra; Red Nucleus
 Abstract: Functional magnetic resonance imaging (MRI) data are usually registered into standard anatomical space. However, standard atlases, such as LPBA40, the Harvard-Oxford atlas, FreeSurfer, and the Jülich cytoarchitectonic maps all lack important detailed information about small subcortical structures like the Substantia nigra and Subthalamic nucleus. Here we introduce a new subcortical probabilistic atlas based on ultra-high resolution in-vivo anatomical imaging from 7 Tesla MRI. The atlas includes six important but elusive subcortical nuclei: the striatum, the globus pallidus internal and external segment (GPi/e), the subthalamic nucleus, the substantia nigra, and the red nucleus. With a sample of 30 young subjects and carefully cross-validated delineation protocols, our atlas is able to capture the anatomical variability within healthy populations for each of the included structures at an unprecedented level of detail. All the generated probabilistic atlases are registered to MNI standard space and are publicly available.

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Language(s): eng - English
 Dates: 2014-03-102014-03-172014-07-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neuroimage.2014.03.032
PMID: 24650599
Other: Epub 2014
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 94 Sequence Number: - Start / End Page: 40 - 46 Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166