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J. Sijbers and den Dekker, A. J., “Generalized likelihood ratio test for complex fMRI data”, in SPIE Medical Imaging: Physiology, Function, and Structure from Medical Images, San Diego, California, USA, 2004, vol. 5369, pp. 652-663.PDF icon Download full paper (251.15 KB)
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, Van Der Linden, A., Scheunders, P., Van Audekerke, J., Raman, E., and Van Dyck, D., “Semi-automatic mouse cerebellum extraction from 3D magnetic resonance data”, in Proceedings of the International Society for Magnetic Resonance in Medicine, New York, USA, 1996, vol. 3, p. 1585.
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, 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, 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., 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.
F. Schmidt, Koirala, B., and Andrieu, F., “Validation of abundance determination of granular mixture using radiative transfer and Bayesian MCMC”, EPSC2024. 2024.PDF icon exhibit_17_validation_of_abundance_determination_of_granular_mixture_using_radiative_transfer_and_bayesian_mcmc.pdf (977.09 KB)
F. Schmidt, Koirala, B., and Andrieu, F., “Determination of volumetric abundance of intimate mixture using Bayesian MCMC”, IEEE Sensors Journal, pp. 1-1, 2024.PDF icon Download paper (2.8 MB)
P. Scheunders, “Wavelet-based enhancement and denoising using multiscale structure tensor”, in Proceedings of the IEEE International Conference on Image Processing, Rochester NY, 2002, pp. 569-572.
P. Scheunders, “Bayesian techniques for multi/hyperspectral image processing”, in 4th IEEE Conference on Industrial Electronics and Applications, Xi’an, China, May 25-27, 2009, pp. 1-10.
P. Scheunders, Van Hove, H., and Livens, S., “On the local optimality of image quantizers”, in Proc. ICPR'96 IEEE Internat. Conference on Pattern Recognition,, D, pp. 664-668, Vienna, august 25-30, 1996, pp. 664-668.
P. Scheunders, “A multivalued image wavelet representation based on multiscale fundamental forms”, IEEE Transactions on Image Processing, vol. 11, pp. 568-575, 2002.
P. Scheunders and De Backer, S., “Wavelet denoising of multicomponent images, using Gaussian Scale Mixture models and a noise-free image as priors”, IEEE Transactions on Image Processing, vol. 16, pp. 1865-1872, 2007.
P. Scheunders, “Multispectral image fusion using local mapping techniques”, in Proc. ICPR2000, International Conference on Pattern Recognition, Barcelona, Spain, september 3-7, 2000, pp. 311-314.
P. Scheunders, “Wavelet thresholding of multispectral images”, in Proc. ACIVS03, Andvanced Concepts for intelligent vision systems , Ghent, 2003, pp. 255-259.
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.

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