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J. Sijbers, den Dekker, A. J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Adaptive anisotropic noise filtering for magnitude MR data”, Magnetic Resonance Imaging, vol. 17, pp. 1533-1539, 1999.PDF icon Download full paper (366 KB)
J. Sijbers and den Dekker, A. J., “Maximum Likelihood estimation of signal amplitude and noise variance from MR data”, Magnetic Resonance in Medicine, vol. 51, pp. 586-594, 2004.PDF icon Download full paper (295.12 KB)
J. Sijbers, den Dekker, A. J., and Bos, R., “A likelihood ratio test for functional MRI data analysis to account for colored noise”, Lecture Notes in Computer Science, vol. 3708, pp. 538-546, 2005.PDF icon Download full paper (483.15 KB)
J. Sijbers and Postnov, A., “Reduction of ring artifacts in high resolution micro-CT reconstructions”, Physics in Medicine and Biology, vol. 49, pp. 247-253, 2004.
J. Sijbers and den Dekker, A. J., “Generalized likelihood Ratio tests for complex fMRI data: a simulation study”, IEEE Transactions on Medical Imaging, vol. 24, pp. 604-611, 2005.PDF icon Download paper (377.11 KB)
J. Sijbers, Poot, D. H. J., den Dekker, A. J., and Pintjens, W., “Automatic estimation of the noise variance from the histogram of a magnetic resonance image”, Physics in Medicine and Biology, vol. 52, pp. 1335-1348, 2007.PDF icon Download paper (297.18 KB)
J. Sijbers, den Dekker, A. J., Scheunders, P., and Van Dyck, D., “Maximum Likelihood estimation of Rician distribution parameters”, IEEE Transactions on Medical Imaging, vol. 17, pp. 357-361, 1998.PDF icon Download paper (106.26 KB)
J. Sijbers, den Dekker, A. J., Raman, E., and Van Dyck, D., “Parameter estimation from magnitude MR images”, International Journal of Imaging Systems and Technology, vol. 10, pp. 109-114, 1999.PDF icon Download paper (350.44 KB)
J. Sijbers, Scheunders, P., Bonnet, N., Van Dyck, D., and Raman, E., “Quantification and improvement of the signal-to-noise ratio in a magnetic resonance image acquisition procedure”, Magnetic Resonance Imaging, vol. 14, pp. 1157-1163, 1996.PDF icon Download paper (1.31 MB)
J. Sijbers, Verhoye, M., Scheunders, P., Van Der Linden, A., Van Dyck, D., and Raman, E., “Watershed based segmentation of 3D MR data for volume quantization”, Magnetic Resonance Imaging, vol. 15, pp. 679-688, 1997.PDF icon Download paper (3.18 MB)
J. Sijbers, Michiels, I., Verhoye, M., Van Audekerke, J., Van Der Linden, A., and Van Dyck, D., “Restoration of MR induced artifacts in simultaneously recorded MR/EEG data”, Magnetic Resonance Imaging, vol. 17, pp. 1383-1393, 1999.PDF icon Download paper (1.09 MB)
J. Sijbers, den Dekker, A. J., Van Audekerke, J., Verhoye, M., and Van Dyck, D., “Estimation of the noise in magnitude MR images”, Magnetic Resonance Imaging, vol. 16, pp. 87-90, 1998.PDF icon Download paper (64.9 KB)
M. Siqueira Pinto, Paolella, R., Billiet, T., Van Dyck, P., Guns, P. - J., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., “Harmonisation of Brain Diffusion MRI: Concepts and Methods”, Frontiers in Neuroscience , vol. 14, pp. 1-17, 2020.PDF icon Download paper (2.61 MB)
M. Siqueira Pinto, Winzeck, S., Kornaropoulos, E. N., Richter, S., Paolella, R., Correia, M. M., Glocker, B., Williams, G., Vik, A., Posti, J., Håberg, A. Kristine, Stenberg, J., Guns, P. - J., den Dekker, A. J., Menon, D. K., Sijbers, J., Van Dyck, P., and Newcombe, V. F. J., “Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study”, Journal of Neurotrauma, 2023.
N. Six, Renders, J., Sijbers, J., and De Beenhouwer, J., “Gauss-Newton-Krylov for Reconstruction of Polychromatic X-ray CT Images”, IEEE Transactions on Computational Imaging, vol. 7, pp. 1304-1313, 2021.
N. Six, De Beenhouwer, J., and Sijbers, J., “poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT”, Optics Express, vol. 27, no. 23, pp. 33427-33435, 2019.PDF icon Download paper (997.08 KB)
B. de Smit, McClure, M., Palenstijn, W. J., Sparling, I. E., and Wagon, S., “Through the Looking-Glass, and What the Quadratic Camera Found There”, The Mathematical Intelligencer, vol. 34, no. 3, pp. 30 - 34, 2012.
A. Smolders, Martino, D. F., Staeren, N., Scheunders, P., Sijbers, J., Goebel, R., and Formisano, E., “Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis”, Magnetic Resonance Imaging, vol. 25, pp. 860-868, 2007.PDF icon Download paper (658.36 KB)
J. Soons, Danckaers, F., Keustermans, W., Huysmans, T., Sijbers, J., Casselman, J. W., and Dirckx, J. J. J., “3D morphometric analysis of the human incudomallear complex using clinical cone-beam CT”, Hearing research, vol. 340, pp. 79-88, 2016.
K. Stanković, Booth, B. G., Danckaers, F., Burg, F., Vermaelen, P., Duerinck, S., Sijbers, J., and Huysmans, T., “Three-dimensional quantitative analysis of healthy foot shape: a proof of concept study”, Journal of Foot and Ankle Research, vol. 11, no. 8, pp. 1-13, 2018.PDF icon Download paper (2.24 MB)
K. Stanković, Huysmans, T., Danckaers, F., Sijbers, J., and Booth, B. G., “Subject-specific identification of three dimensional foot shape deviations using statistical shape analysis”, Expert Systems With Applications, vol. 151, no. 113372, pp. 1-11, 2020.
H. Struyfs, Van Hecke, W., Veraart, J., Sijbers, J., Slaets, S., De Belder, M., Wuyts, L., Peters, B., Sleegers, K., Robberecht, C., Van Broeckhoven, C., De Belder, F., Parizel, P. M., and Engelborghs, S., “Diffusion Kurtosis Imaging: a possible MRI biomarker for AD diagnosis?”, Journal of Alzheimer’s Disease, vol. 48, pp. 937-948, 2015.PDF icon Download paper (374.95 KB)
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.
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F. Tajdari, Huysmans, T., Yang, Y., and Song, Y., “Feature preserving non-rigid iterative weighted closest point and semi-curvature registration”, IEEE Transactions on Image Processing, 2022.
C. M. W. Tax, Jeurissen, B., Vos, S. B., Viergever, M. A., and Leemans, A., “Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data.”, NeuroImage, vol. 86, pp. 67-80, 2014.

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