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

2018

G. Ramos-Llordén, “Improved MRI Relaxometry through Statistical Signal Processing”, University of Antwerp, Antwerp, 2018.PDF icon Download thesis (19.25 MB)
H. Zivari Adab, Chalavi, S., Beets, I., Gooijers, J., Leunissen, I., Cheval, B., Collier, Q., Sijbers, J., Jeurissen, B., Swinnen, S. P., and Boisgontier, M., “White matter microstructural organization of interhemispheric pathways predicts different stages of bimanual coordination learning in young and older adults”, European Journal of Neuroscience , vol. 47, no. 5, pp. 446–459, 2018.
Q. Collier, Veraart, J., Jeurissen, B., Vanhevel, F., Pullens, P., Parizel, P. M., den Dekker, A. J., and Sijbers, J., “Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach”, Magnetic Resonance in Medicine, vol. 80, no. 2, pp. 802-813, 2018.PDF icon Download paper (1.93 MB)
J. Praet, Manyakov, N., Muchene, L., Mai, Z., Terzopoulos, V., De Backer, S., Torremans, A., Guns, P. - J., Van De Casteele, T., Bottelbergs, A., Van Broeck, B., Sijbers, J., Smeets, D., Shkedy, Z., Bijnens, L., Pemberton, D., Schmidt, M., Van Der Linden, A., and Verhoye, M., “Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology.”, Alzheimer's Research & Therapy , vol. 10, no. 1, pp. 1-16, 2018.
F. Calamante, Jeurissen, B., Smith, R. E., Tournier, J. - D., and Connelly, A., “The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density”, Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2738–2744, 2018.

2017

J. P. M. Kenney, McPhilemy, G., Scanlon, C., Najt, P., McInerney, S., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Hallahan, B., McDonald, C., and Cannon, D. M., “The arcuate fasciculus network and verbal deficits in psychosis”, Translational Neuroscience, vol. 8, no. 1, pp. 117-126, 2017.
T. Roine, “Improved reliability of fiber orientation estimation and graph theoretical analysis of structural brain networks with diffusion MRI”, University of Antwerp, 2017.
P. V. Sudeep, Palanisamy, P., Kesavadas, C., Sijbers, J., den Dekker, A. J., and Rajan, J., “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.
J. Hamaide, De Groof, G., Van Steenkiste, G., Jeurissen, B., Van Audekerke, J., Naeyaert, M., Van Ruijssevelt, L., Cornil, C., Sijbers, J., Verhoye, M., and Van Der Linden, A., “ 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.
A. Van Ombergen, Wuyts, F. L., Jeurissen, B., Sijbers, J., Vanhevel, F., Jillings, S., Parizel, P. M., Sunaert, S., Van de Heyning, P. H., Dousset, V., Laureys, S. S. L., and Demertzi, A., “Intrinsic connectivity reduces in vestibular-related regions after first-time exposure to short-term gravitational alterations”, Scientific Reports, vol. 7, no. 3061, 2017.PDF icon Download paper (3.47 MB)

Pages