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Example dataset for the hMRI toolbox

Callaghan, MF; Lutti, A; Ashburner, J; Balteau, E; Corbin, N; Draganski, B; Helms, G; ... Weiskopf, N; + view all (2019) Example dataset for the hMRI toolbox. Data Brief , 25 , Article 104132. 10.1016/j.dib.2019.104132. (In press). Green open access

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Abstract

The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner's transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI – A toolbox for quantitative MRI in neuroscience and clinical research [1].

Type: Article
Title: Example dataset for the hMRI toolbox
Location: Netherlands
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.dib.2019.104132
Publisher version: https://doi.org/10.1016/j.dib.2019.104132
Language: English
Additional information: Published by Elsevier Inc. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
Keywords: hMRI, hMRI toolbox, qMRI, Quantitative MRI, Analysis tools, qMRI software
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10077788
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