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

2009

C. A. Sage, Van Hecke, W., Peeters, R. R., Sijbers, J., Robberecht, W., Parizel, P. M., Marchal, G., Leemans, A., and Sunaert, S., “Quantitative diffusion tensor imaging in amyotrophic lateral sclerosis: revisited.”, Human brain mapping, vol. 30, no. 11, pp. 3657-75, 2009.
D. H. J. Poot, “Advances in the reconstruction and statistical processing of Magnetic Resonance images”, 2009.PDF icon Download thesis (6.18 MB)
W. Van Hecke, “Improved Processing for Diffusion Tensor Magnetic Resonance Images for Coregistration, Atlas Construction, and Voxel Based Analysis”, University of Antwerp, Antwerp, 2009.PDF icon Download thesis (35.03 MB)
W. Van Hecke, Sijbers, J., De Backer, S., Poot, D. H. J., Parizel, P. M., and Leemans, A., “On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods”, NeuroImage, vol. 46, pp. 692-707, 2009.PDF icon Download paper (4.14 MB)
A. J. den Dekker, Poot, D. H. J., Bos, R., and Sijbers, J., “Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study”, IEEE Transactions on Medical Imaging, vol. 28, pp. 287-296, 2009.

2008

W. Van Hecke, Sijbers, J., D'Agostino, E., Maes, F., De Backer, S., Vandervliet, E., Parizel, P. M., and Leemans, A., “On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain”, NeuroImage, vol. 43, pp. 69-80, 2008.PDF icon Download paper (3.34 MB)
W. Van Hecke, Leemans, A., Sijbers, J., Vandervliet, E., Van Goethem, J., and Parizel, P. M., “A tracking based DTI segmentation method for the detection of diffusion-related changes of the cervical spinal cord with aging”, Journal of Magnetic Resonance Imaging, vol. 27, pp. 978-991, 2008.PDF icon Download paper (4.4 MB)
T. Boumans, Vignal, C., Smolders, A., Sijbers, J., Verhoye, M., Van Audekerke, J., and Van Der Linden, A., “Functional magnetic resonance imaging in zebra finch discerns the neural substrate involved in segregation of conspecific song from background noise”, Journal of Neurophysiology, vol. 99, pp. 931-938, 2008.PDF icon Download full paper (832.59 KB)

2007

A. Smolders, “Data-driven methods for the analysis of time-resolved mental chronometry fMRI data sets”, 2007.PDF icon Download thesis (3.79 MB)
P. M. Parizel, Van Rompaey, V., Loock, V. R., Van Hecke, W., Van Goethem, J., Leemans, A., and Sijbers, J., “Influence of User-Defined Parameters on Diffusion Tensor Tractography of the Corticospinal Tract”, The Neuroradiology Journal, pp. 139-147, 2007.

Pages