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

2005

J. Sijbers, A J. den Dekker, and R. Bos, "A likelihood ratio test for functional MRI data analysis to account for colored noise", Lecture Notes in Computer Science, vol. 3708, pp. 538-546, September, 2005. PDF icon Download full paper (483.15 KB)
A J. den Dekker, and J. Sijbers, "Implications of the Rician distribution for fMRI generalized likelihood ratio tests", Magnetic Resonance Imaging, vol. 23, no. 9, pp. 953-959, 2005. PDF icon Download full paper (467.24 KB)

2004

J. Sijbers, and A J. den Dekker, "Maximum Likelihood estimation of signal amplitude and noise variance from MR data", Magnetic Resonance in Medicine, vol. 51, no. 3, pp. 586-594, 2004. PDF icon Download full paper (295.12 KB)

2000

1999

J. Sijbers, A J. den Dekker, E. Raman, and D. Van Dyck, "Parameter estimation from magnitude MR images", International Journal of Imaging Systems and Technology, vol. 10, no. 2, pp. 109-114, 1999. PDF icon Download full paper (356.36 KB)
J. Sijbers, A J. den Dekker, M. Verhoye, A. Van Der Linden, and D. Van Dyck, "Adaptive anisotropic noise filtering for magnitude MR data", Magnetic Resonance Imaging, vol. 17, no. 10, pp. 1533-1539, 1999. PDF icon Download full paper (366 KB)

Pages