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Abstract #2288

Quantitative MRI made easy with qMRLab

Tanguy DUVAL1, Ilana R Leppert1,2, Jean-François Cabana3, Mathieu Boudreau2, Ian Gagnon1, Gabriel Berestovoy 1, Julien Cohen-Adad1,4, and Nikola Stikov1,5

1NeuroPoly Lab, Polytechnique Montreal, Montreal, QC, Canada, 2Montreal Neurological Institute, McGill University, Montreal, QC, Canada, 3Centre Hospitalier de l’Université de Montréal, Montreal, QC, Canada, 4Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada, 5Montreal Heart Institute, Montreal, QC, Canada

Quantitative MR (qMR) methods exist for most MRI sequences (e.g. diffusion, magnetization transfer, inversion recovery). All these methods have a similar methodology: a biophysical model (i.e. an analytical equation), that relates the MRI contrast to some microstructural and physical features, is used to fit experimental data. Although open-source software packages are available online for certain qMR techniques, there does not exist a single stand-alone platform that can implement and compare a wide range of quantitative MRI methods. With qMRLab, we propose an open-source, MATLAB-based, object-oriented software with separate modules for each technique. We envision qMRLab as a standard platform with a growing list of contributors, where the qMR community can replicate and cross-validate a wide range of qMR methods. qMRLab includes a user-friendly graphical user interface (GUI), batch scripts examples, and qMR datasets. The software can be used to fit and check the quality of qMR data, to optimize protocols, compare fitting models, and simulate the effects of various model assumptions.

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