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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, den Dekker, A. J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Adaptive anisotropic noise filtering for magnitude MR data”, in Proceedings of SPIE Medical Imaging, San Diego, USA, 1999, vol. 3661, pp. 1418-1425.
J. Sijbers and den Dekker, A. J., “The performance of generalized likelihood ratio tests for complex functional MRI data in the presence of phase model misspecification”, in European Society of Magnetic Resonance in Medicine (ESMRMB), Copenhagen, Denmark, 2004, p. 96.
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., Scheunders, P., Raman, E., and Van Dyck, D., “Unbiased signal estimation in magnitude MR images”, in Proceedings of the European Society for Magnetic Resonance in Medicine and Biology, Brussels, Belgium, 1997, vol. 2, p. 174.
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)
J. Sijbers and den Dekker, A. J., “Mapping a polyhedron onto a sphere: application to Fourier descriptors”, in 22nd Benelux Meeting on Systems and Control, Lommel, Belgium, 2003.
J. Sijbers, Michiels, I., Van Audekerke, J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Restoration of EEG signals distorted during simultaneous MR acquisitions”, in Proceedings of the International Society of Magnetic Resonance in Medicine, Denver CO, USA, 2000, p. 118.
K. Rafiezadeh Shahi, “Unsupervised machine/deep learning mapping (clustering) for single/multi-source remote sensing data ”, 2023.
B. Shafieizargar, Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept”, ISMRM-Benelux, vol. 12. 2020.
B. Shafieizargar, Byanju, R., Sijbers, J., Klein, S., den Dekker, A. J., and Poot, D. H. J., “Systematic review of reconstruction techniques for accelerated quantitative MRI”, Magnetic Resonance in Medicine, vol. 90, no. 3, pp. 1172-1208, 2023.PDF icon Download paper (2.91 MB)
B. Shafieizargar, Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept”, International Society for Magnetic Resonance in Medicine (ISMRM), vol. 28. 2020.
B. Shafieizargar, Jeurissen, B., Poot, D. H. J., den Dekker, A. J., and Sijbers, J., “Multi-contrast multi-shot EPI for accelerated diffusion MRI”, in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021, pp. 3869-3872.
B. Shafieizargar, Jeurissen, B., Poot, D. H. J., Van Audekerke, J., Verhoye, M., den Dekker, A. J., and Sijbers, J., “Accelerated multi-shot diffusion weighted imaging with joint estimation of diffusion and phase parameters”, Magn Reson Mater Phy, vol. 34. pp. S57-S58, 2021.
B. Shafieizargar, Jeurissen, B., Poot, D. H. J., Klein, S., Van Audekerke, J., Verhoye, M., den Dekker, A. J., and Sijbers, J., “ADEPT: Accurate Diffusion EPI with multi-contrast shoTs”, Magnetic Resonance in Medicine, vol. 89, no. 1, pp. 396-410, 2023.PDF icon Download paper (5.82 MB)
L. Serbruyns, Leunissen, I., Huysmans, T., Cuypers, K., Meesen, R. L., van Ruitenbeek, P., Sijbers, J., and Swinnen, S. P., “Subcortical volumetric changes across the adult lifespan: subregional thalamic atrophy accounts for age-related sensorimotor performance declines”, Cortex, vol. 65, pp. 128-138, 2015.PDF icon paper (1.35 MB)
S. Sekar, Jonckers, E., Verhoye, M., Willems, R., Veraart, J., Van Audekerke, J., Couto, J., Giugliano, M., Wuyts, K., Dedeurwaerdere, S., Sijbers, J., Mackie, C., Ver Donck, L., Steckler, T., and Van Der Linden, A., “Subchronic memantine induced concurrent functional disconnectivity and altered ultra-structural tissue integrity in the rodent brain: revealed by multimodal MRI.”, Psychopharmacology, vol. 227, no. 3, pp. 479-91, 2013.
H. Segers, Palenstijn, W. J., Batenburg, K. J., and Sijbers, J., “Segmentation of MR Images by k-space distance minimization: a proof of concept”, ESMRMB CONGRESS 2012: 29th Annual Scientific Meeting, vol. 25, no. 1. pp. 63-64, 2012.PDF icon Download abstract (221.41 KB)
H. Segers, Palenstijn, W. J., Batenburg, K. J., and Sijbers, J., “Discrete Tomography in MRI: a proof of concept”, Proc. Intl. Soc. Mag. Reson. Med, vol. 21. p. 2662, 2013.
H. Segers, Palenstijn, W. J., Batenburg, K. J., and Sijbers, J., “Discrete Tomography in MRI: a Simulation Study”, Fundamenta Informaticae, vol. 125, no. 3-4, pp. 223-237, 2013.
P. Scheunders and De Backer, S., “Fusion and merging of multispectral images using multiscale fundamental forms”, Journal of the Optical Society of America A, vol. 18, pp. 2468-2477, 2001.
P. Scheunders, Duijster, A., and Zhang, Y., “Wavelet-based Multi/Hyperspectral Image Restoration and Fusion”, in Signal and Image Processing for Remote Sensing, C. H. Chen, Ed. Taylor and Francis, 2012, pp. 505-523.
P. Scheunders, “A genetic approach towards optimal color image quantization”, in Proc. ICIP'96, IEEE Internat. Conference on Image Processing , III, Lausanne, september 16-19, 1996, pp. 1031-1034.
P. Scheunders, Tuia, D., and Moser, G., “Contributions of Machine Learning to Remote Sensing Data Analysis”, in Comprehensive Remote Sensing, vol. 2, 2018, pp. 199-243.
P. Scheunders, “A wavelet representation of multispectral images; in: Frontiers of Remote Sensing Information Processing”, C. H. Chen, Ed. World Scientific, 2003, pp. 197-224.

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