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

2022

V. Anania, Collier, Q., Veraart, J., Buikema, A. Eline, Vanhevel, F., Billiet, T., Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model”, NeuroImage, vol. 256, p. 119219, 2022.
D. Giraldo, “Computational anatomy strategies for characterization of brain patterns associated with Alzheimer's disease”, 2022.PDF icon Download PhD thesis (25.92 MB)
A. Doroshin, Jillings, S., Jeurissen, B., Tomilovskaya, E., Pechenkova, E. V., Nosikova, I., Rumshiskaya, A., Litvinova, L., Rukavishnikov, I., De Laet, C., Schoenmaekers, C., Sijbers, J., Laureys, S. S. L., Petrovichev, V., Van Ombergen, A., Annen, J., Sunaert, S., Parizel, P. M., Sinitsyn, V., Eulenburg, Pzu, Osipowicz, K., and Wuyts, F. L., “Brain Connectometry Changes in Space Travelers After Long-Duration Spaceflight”, Front. Neural Circuits, vol. 16, 2022.
G. Barisano, Sepehrband, F., Collins, H. R., Jillings, S., Jeurissen, B., Taylor, A. J., Schoenmaekers, C., De Laet, C., Rukavishnikov, I., Nosikova, I., Rumshiskaya, A., Annen, J., Sijbers, J., Laureys, S. S. L., Van Ombergen, A., Petrovichev, V., Sinitsyn, V., Pechenkova, E. V., Grishin, A., Eulenburg, Pzu, Law, M., Sunaert, S., Parizel, P. M., Tomilovskaya, E., Roberts, D., and Wuyts, F. L., “The effect of prolonged Spaceflight on Cerebrospinal Fluid and Perivascular Spaces of Astronauts and Cosmonauts”, PNAS, vol. 119, no. 17, 2022.

2021

B. Jeurissen and Szczepankiewicz, F., “Multi-tissue spherical deconvolution of tensor-valued diffusion MRI.”, Neuroimage, vol. 245, p. 118717, 2021.
D. Giraldo, Sijbers, J., and Romero, E., “Quantification of cognitive impairment to characterize heterogeneity of patients at risk of developing Alzheimer's disease dementia”, Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring, vol. 13, no. 1, p. e12237, 2021.
E. Ribeiro Sabidussi, Klein, S., Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., “Recurrent Inference Machines as inverse problem solvers for MR relaxometry”, Medical Image Analysis, vol. 74, pp. 1-11, 2021.PDF icon Download paper (2.26 MB)
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.
M. Naeyaert, “Strategies for efficient acquisition and reconstruction of structural and quantitative MRI”, 2021.
H. R. P. Park, Verhelst, H., Quak, M., Jeurissen, B., and Krebs, R. M., “Associations between different white matter properties and reward-based performance modulation”, Brain Structure and Function, 2021.

Pages