Multi-modal ultra-high resolution structural 7-Tesla MRI data repository

Birte U. Forstmann; Max C. Keuken; Andreas Schafer; Pierre Louis Bazin; Anneke Alkemade; Robert Turner

doi:10.1038/sdata.2014.50

Multi-modal ultra-high resolution structural 7-Tesla MRI data repository

Birte U. Forstmann, Max C. Keuken, Andreas Schafer, Pierre Louis Bazin, Anneke Alkemade, Robert Turner

School of Medicine

Research output: Contribution to journal › Article › peer-review

40 Scopus citations

Abstract

Structural brain data is key for the understanding of brain function and networks, i.e., connectomics. Here we present data sets available from the 'atlasing of the basal ganglia (ATAG)' project, which provides ultra-high resolution 7 Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. The ATAG data set includes whole-brain and reduced field-of-view MP2RAGE and T2∗-weighted scans of the subcortex and brainstem with ultra-high resolution at a sub-millimeter scale. The data can be used to develop new algorithms that help building high-resolution atlases both relevant for the basic and clinical neurosciences. Importantly, the present data repository may also be used to inform the exact positioning of electrodes used for deep-brain-stimulation in patients with Parkinson's disease and neuropsychiatric diseases.

Original language	English (US)
Article number	140050
Journal	Scientific Data
Volume	1
DOIs	https://doi.org/10.1038/sdata.2014.50
State	Published - Dec 9 2014

ASJC Scopus subject areas

Statistics and Probability
Information Systems
Education
Computer Science Applications
Statistics, Probability and Uncertainty
Library and Information Sciences

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10.1038/sdata.2014.50

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title = "Multi-modal ultra-high resolution structural 7-Tesla MRI data repository",

abstract = "Structural brain data is key for the understanding of brain function and networks, i.e., connectomics. Here we present data sets available from the 'atlasing of the basal ganglia (ATAG)' project, which provides ultra-high resolution 7 Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. The ATAG data set includes whole-brain and reduced field-of-view MP2RAGE and T2∗-weighted scans of the subcortex and brainstem with ultra-high resolution at a sub-millimeter scale. The data can be used to develop new algorithms that help building high-resolution atlases both relevant for the basic and clinical neurosciences. Importantly, the present data repository may also be used to inform the exact positioning of electrodes used for deep-brain-stimulation in patients with Parkinson's disease and neuropsychiatric diseases.",

author = "Forstmann, {Birte U.} and Keuken, {Max C.} and Andreas Schafer and Bazin, {Pierre Louis} and Anneke Alkemade and Robert Turner",

note = "Funding Information: We thank Domenica Wilfling and Elisabeth Wladimirov for taking such good care of all our participants. This research line is financially supported by the European Research Council (BUF).",

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doi = "10.1038/sdata.2014.50",

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AU - Keuken, Max C.

AU - Schafer, Andreas

AU - Bazin, Pierre Louis

AU - Alkemade, Anneke

AU - Turner, Robert

N1 - Funding Information: We thank Domenica Wilfling and Elisabeth Wladimirov for taking such good care of all our participants. This research line is financially supported by the European Research Council (BUF).

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N2 - Structural brain data is key for the understanding of brain function and networks, i.e., connectomics. Here we present data sets available from the 'atlasing of the basal ganglia (ATAG)' project, which provides ultra-high resolution 7 Tesla (T) magnetic resonance imaging (MRI) scans from young, middle-aged, and elderly participants. The ATAG data set includes whole-brain and reduced field-of-view MP2RAGE and T2∗-weighted scans of the subcortex and brainstem with ultra-high resolution at a sub-millimeter scale. The data can be used to develop new algorithms that help building high-resolution atlases both relevant for the basic and clinical neurosciences. Importantly, the present data repository may also be used to inform the exact positioning of electrodes used for deep-brain-stimulation in patients with Parkinson's disease and neuropsychiatric diseases.

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Multi-modal ultra-high resolution structural 7-Tesla MRI data repository

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