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Poster

The “hMRI Toolbox” for quantitative imaging & in vivo histology using MRI

MPS-Authors
/persons/resource/persons192472

Leutritz,  Tobias
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19943

Reimer,  Enrico
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons147461

Weiskopf,  Nikolaus
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;

External Resource

http://hdl.handle.net/2268/225361
(Postprint)

Fulltext (restricted access)
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Fulltext (public)

POSTER_hMRI_HBM2018.pdf
(Postprint), 732KB

Supplementary Material (public)
There is no public supplementary material available
Citation

Philips, C., Balteau, E., Leutritz, T., Lutti, A., Callaghan, M. F., Draganski, B., et al. (2018). The “hMRI Toolbox” for quantitative imaging & in vivo histology using MRI. Poster presented at 2018 OHBM ANNUAL MEETING, Singapore.


Cite as: https://hdl.handle.net/21.11116/0000-0002-BDA4-0
Abstract
Quantitative magnetic resonance imaging (qMRI) finds increasing application in
neuroscience and clinical research due to its greater specificity and its sensitivity
to microstructural properties of brain tissue, such as myelin, iron and water
concentration. We introduce the “hMRI Toolbox”, an easy-to-use open-source
tool for generating and processing quantitative MRI data. This toolbox is
embedded in the SPM framework, profiting from the high accuracy spatial
registration in common space and the variety of available statistical analyses.
It allows the estimation of quantitative MRI maps, precisely longitudinal
(R 1 =1/T 1 ) and transverse (R 2 *=1/T 2 *) relaxation rates, proton density (PD) and
magnetization transfer (MT), followed by spatial registration in common space
for statistical analysis. It also offers flexibility for calculation of novel MRI
biomarkers of tissue microstructure.
The hMRI toolbox can be downloaded from http://hmri.info.
The Readme.md and Wiki of the Git repository provide :
• reference documentation, including installation instructions,
example dataset, tutorial and detailed description of the
functionalities implemented;
• a link to a pre-print paper describing the hMRI toolbox.