Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a biomedical imaging technique used to visualize detailed internal structures. The Quantitative MRI group of the Vision Lab develops novel reconstruction, processing and analysis algorithms to process anatomical, functional or diffusion-weighted MRI data. These methods rely on profound knowledge of the MR imaging principles. The core competence of the group is quantitative, statistical parameter estimation, which is the basis for developing novel techniques for image reconstruction, image denoising, higher order diffusion parameter estimation (DTI, DKI, ...), and fiber tractography.
People
Journal publications
2017
“The arcuate fasciculus network and verbal deficits in psychosis”, Translational Neuroscience, vol. 8, no. 1, pp. 117-126, 2017. ,
“Improved reliability of fiber orientation estimation and graph theoretical analysis of structural brain networks with diffusion MRI”, University of Antwerp, 2017. ,
“A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps”, Signal Image and Video Processing, vol. 11, no. 5, pp. 913-920, 2017. ,
“ Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging”, NeuroImage, vol. 146, pp. 789-803, 2017. ,
“Intrinsic connectivity reduces in vestibular-related regions after first-time exposure to short-term gravitational alterations”, Scientific Reports, vol. 7, no. 3061, 2017.
Download paper (3.47 MB) ,

“The effect of spaceflight and microgravity on the human brain”, Journal of Neurology, vol. 246, no. 1, pp. 18-22, 2017. ,
“Altered functional brain connectivity in patients with visually induced dizziness”, NeuroImage: Clinical, vol. 14, pp. 538–545, 2017. ,
“Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft”, Journal of Magnetic Resonance Imaging, vol. 46, no. 5, pp. 1423–1432, 2017. ,
“A safe, cheap and easy-to-use isotropic diffusion phantom for clinical and multicenter studies”, Medical Physics, vol. 44, no. 3, pp. 1063–1070, 2017. ,
“Partial Discreteness: a Novel Prior for Magnetic Resonance Image Reconstruction”, IEEE Transactions on Medical Imaging, vol. 36, no. 5, pp. 1041 - 1053, 2017.
Download paper (3.72 MB) ,
