TimVanMourik
commented
5 years ago Hi @ChristophePhillips, I’m happy to tell you that we’d like to host your presentation as a lightning talk in the OSR in the Collaborative research session. This will be a talk of 5 minutes + 5 minutes of questions. We can unfortunately not offer you a slot in your preferred session as the ‘new advances’ session had many applicants yet limited availability. We hope this session is ok for you and would like to ask you if in your presentation you could briefly reflect on the session topic: the collaborative nature of your project.
We’ll update the program in the ReadMe.md shortly. We’d much appreciate it if you could submit slides and other presentation material to the presentations folder by means of a Pull Request to this repository, preferably but not necessarily before the presentation.
ChristophePhillips
Title
The hMRI-toolbox: A toolbox for quantitative MRI and in vivo histology using MRI (hMRI).
Presentor and Affiliation
Christophe Phillips
GIGA in silico medicine & GIGA Cyclotron Research Centre in vivo imaging. GIGA Institute, University of Liège, Belgium.
Martina Callaghan
Welcome Centre for Human Neuroimaging, University College London, UK.
Collaborators
The development of the hMRI-toolbox is an international collaborative effort including the following sites and developers:
Github Link (if applicable)
hMRI-toolboxAbstract (max. 200 words):
Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration (Weiskopf et al., 2015).
The hMRI-toolbox is an easy-to-use open-source and flexible tool, for qMRI data handling and processing. It 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 saturation) (Weiskopf et al., 2013), followed by spatial registration in common space for statistical analysis (Draganski et al., 2011).
The qMRI maps generated by the toolbox can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. They are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers (Mohammadi et al., 2015). The hMRI toolbox is therefore the first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction.
Preferred Session
Demo: New advances in open neuroimaging methodsAdditional Context
Embedded in the Statistical Parametric Mapping (SPM) framework, it can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps, and it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences.
For a reference on the scientific background, methods and concepts please use this NeuroImage paper and cite it when publishing results compiled with the hMRI-toolbox. A conference poster is also available here.