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

2011

Z. Mai, Rajan, J., Verhoye, M., and Sijbers, J., “Robust edge-directed interpolation of magnetic resonance images”, Physics in medicine and biology, vol. 56, pp. 7287-7303, 2011.PDF icon Download paper (1.3 MB)
B. Jeurissen, Leemans, A., Jones, D. K., Tournier, J. - D., and Sijbers, J., “Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution”, Human Brain Mapping, vol. 32, no. 3, pp. 461 - 479, 2011.
J. Veraart, Poot, D. H. J., Van Hecke, W., Blockx, I., Van Der Linden, A., Verhoye, M., and Sijbers, J., “More accurate estimation of diffusion tensor parameters using diffusion kurtosis imaging”, Magnetic Resonance in Medicine, vol. 65, pp. 138-145, 2011.PDF icon Download paper (387.31 KB)
Z. Mai, Hanel, R., Batenburg, K. J., Verhoye, M., Scheunders, P., and Sijbers, J., “Bias field reduction by localized Lloyd-Max quantization”, Magnetic Resonance Imaging, vol. 29, no. 4, pp. 536-545, 2011.
P. Fillard, Descoteaux, M., Goh, A., Gouttard, S., Jeurissen, B., Malcolm, J., Ramirez-Manzanares, A., Reisert, M., Sakaie, K., Tensaouti, F., Yo, T. - S., Mangin, J. - F., and Poupon, C., “Quantitative Evaluation of 10 Tractography Algorithms on a Realistic Diffusion MR Phantom”, NeuroImage, vol. 56, pp. 220-234, 2011.
J. Veraart, Van Hecke, W., and Sijbers, J., “Constrained Maximum Likelihood Estimation of the Diffusion Kurtosis Tensor Using a Rician Noise Model”, Magnetic Resonance in Medicine, vol. 66, pp. 678-686, 2011.PDF icon Download paper (712.6 KB)
W. Van Hecke, Leemans, A., Sage, C. A., Veraart, J., Sijbers, J., and Sunaert, S., “The effect of template selection on diffusion tensor voxel based analysis results”, NeuroImage, vol. 55, pp. 566-573, 2011.
J. Rajan, Jeurissen, B., Verhoye, M., Van Audekerke, J., and Sijbers, J., “Maximum likelihood estimation based denoising of magnetic resonance images using restricted local neighborhoods”, Physics in Medicine and Biology, vol. 56, pp. 5221-5234, 2011.PDF icon Download full paper (643.93 KB)
J. Veraart, Leergaard, T. B., Antonsen, B. T., Van Hecke, W., Blockx, I., Jeurissen, B., Jiang, Y., Van Der Linden, A., Johnson, A. G., Verhoye, M., and Sijbers, J., “Population-averaged diffusion tensor imaging atlas of the Sprague Dawley rat brain”, NeuroImage, vol. 58, no. 4, pp. 975-983, 2011.
R. Delgado Y Palacios, Adriaan, C., Kim, H., Verhoye, M., Poot, D. H. J., Jouke, D., Van Audekerke, J., Benveniste, H., Sijbers, J., Wiborg, O., and Van Der Linden, A., “Magnetic resonance imaging and spectroscopy reveal differential hippocampal changes in anhedonic and resilient subtypes of the chronic mild stress rat model”, Biological psychiatry, vol. 70, pp. 449-457, 2011.

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