title: Evaluation of q-space sampling strategies for the diffusion magnetic resonance imaging.
abstract: We address the problem of efficient sampling of the diffusion space for the Diffusion Magnetic Resonance Imaging (dMRI) modality. While recent scanner improvements enable the acquisition of more and more detailed images, it is still unclear which q-space sampling strategy gives the best performance. We evaluate several q-space sampling distributions by an approach based on the approximation of the MR signal by a series expansion of Spherical Harmonics and Laguerre-Gaussian functions. With the help of synthetic experiments, we identify a subset of sampling distributions which leads to the best reconstructed data.
authors.affiliation: GREYC (CNRS UMR 6072), 6 Bd Maréchal Juin, 14050 Caen Cedex, France.
authors.forename: Haz-Edine
authors.initials: HE
authors.lastname: Assemlal
authors.forename: David
authors.initials: D
authors.lastname: Tschumperlé
authors.forename: Luc
authors.initials: L
authors.lastname: Brun
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted