WIAS Preprint No. 2527, (2018)

hMRI -- A toolbox for using quantitative MRI in neuroscience and clinical research


  • Balteau, Evelyne
  • Tabelow, Karsten
    ORCID: 0000-0003-1274-9951
  • Ashburner, John
  • Callaghan, Martina F.
  • Draganski, Bogdan
  • Helms, Gunther
  • Kherif, Ferath
  • Leutritz, Tobias
  • Lutti, Antoine
  • Phillips, Christophe
  • Reimer, Enrico
  • Ruthotto, Lars
  • Seif, Maryam
  • Weiskopf, Nikolaus
  • Ziegler, Gabriel
  • Mohammadi, Siawoosh


  • Quantitative MRI, in-vivo histology, microstructure, Multi-Parameter Mapping, relaxometry, SPM toolbox




Quantitative magnetic resonance imaging (qMRI) finds increasing application in neuroscience and clinical research due to its sensitivity to micro-structural properties of brain tissue, e.g. axon, myelin, iron and water concentration. We introduce the hMRI--toolbox, an easy-to-use open-source tool for handling and processing of qMRI data presented together with an example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD and magnetisation transfer MT) that can be used for calculation of standard and novel MRI biomarkers of tissue microstructure as well as improved delineation of subcortical brain structures. Embedded in the Statistical Parametric Mapping (SPM) framework, it can be readily combined with existing SPM tools for estimating diffusion MRI parameter maps and benefits from the extensive range of available tools for high-accuracy spatial registration and statistical inference. As such the hMRI--toolbox provides an efficient, robust and simple framework for using qMRI data in neuroscience and clinical research.

Appeared in

  • NeuroImage, (2018), published online on 21.01.2019, under the new title: hMRI -- A toolbox for quantitative MRI in neuroscience and clinical research, DOI 10.1016/j.neuroimage.2019.01.029 .

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