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.

Journal publications

2017

A. Van Ombergen, Heine, L., Jillings, S., Roberts, E., Jeurissen, B., Van Rompaey, V., Mucci, V., Vanhecke, S., Sijbers, J., Vanhevel, F., Sunaert, S., Bahri, M. Ali, Parizel, P. M., Van de Heyning, P. H., Laureys, S. S. L., and Wuyts, F. L., “Altered functional brain connectivity in patients with visually induced dizziness”, NeuroImage: Clinical, vol. 14, pp. 538–545, 2017.
P. Van Dyck, Froeling, M., De Smet, E., Pullens, P., Torfs, M., Verdonck, P., Sijbers, J., Parizel, P. M., and Jeurissen, B., “Diffusion Tensor Imaging of the Anterior Cruciate Ligament Graft”, Journal of Magnetic Resonance Imaging, vol. 46, no. 5, pp. 1423–1432, 2017.
P. Pullens, Bladt, P., Sijbers, J., Maas, A. I. R., and Parizel, P. M., “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.
G. Ramos-Llordén, den Dekker, A. J., and Sijbers, J., “Partial Discreteness: a Novel Prior for Magnetic Resonance Image Reconstruction”, IEEE Transactions on Medical Imaging, vol. 36, no. 5, pp. 1041 - 1053, 2017.PDF icon Download paper (3.72 MB)
M. Mohammadian, Roine, T., Hirvonen, J., Kurki, T., Ala-Seppälä, H., Frantzén, J., Katila, A., Kyllönen, A., Maanpää, H. - R., Posti, J., Takala, R., Tallus, J., and Tenovuo, O., “High angular resolution diffusion-weighted imaging in mild traumatic brain injury”, NeuroImage: Clinical, vol. 13, pp. 174 - 180, 2017.PDF icon Download paper (848.3 KB)
G. Ramos-Llordén, den Dekker, A. J., Van Steenkiste, G., Jeurissen, B., Vanhevel, F., Van Audekerke, J., Verhoye, M., and Sijbers, J., “A unified Maximum Likelihood framework for simultaneous motion and T1 estimation in quantitative MR T1 mapping”, IEEE Transactions on Medical Imaging, vol. 36, no. 2, pp. 433 - 446, 2017.
G. Van Steenkiste, Poot, D. H. J., Jeurissen, B., den Dekker, A. J., Vanhevel, F., Parizel, P. M., and Sijbers, J., “Super-resolution T1 estimation: quantitative high resolution T1 mapping from a set of low resolution T1 weighted images with different slice orientations”, Magnetic Resonance in Medicine, vol. 77, no. 5, pp. 1818–1830, 2017.PDF icon Download paper (3.3 MB)

2016

J. Veraart, Novikov, D. S., Daan, C., Ades-Aron, B., Sijbers, J., and Fieremans, E., “Denoising of diffusion MRI using random matrix theory”, NeuroImage, vol. 142, pp. 384-396, 2016.PDF icon Download paper (4.53 MB)
G. Van Steenkiste, “Super-resolution estimation of quantitative MRI parameters”, University of Antwerp, 2016.PDF icon Download PhD thesis (7.56 MB)
S. De Santis, Assaf, Y., Jeurissen, B., Jones, D. K., and Roebroeck, A., “T1 relaxometry of crossing fibres in the human brain.”, NeuroImage, 2016.

Pages