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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)
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)
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)
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., “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., “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 thresholding of multivalued images”, IEEE Transactions on Image Processing, vol. 13, pp. 475-483, 2004.
P. Scheunders, De Clerck, N., and Wille, J., “Computerized image storage and analysis of contracting cardiac myocytes”, Journal of Computer Assisted Microscopy, vol. 6, pp. 77-83, 1994.
P. Scheunders, “A genetic Lloyd-Max image quantization algorithm”, Pattern Recognition Letters, vol. 17, pp. 547-556, 1996.
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, “A genetic c-means clustering algorithm applied to color image quantization”, Pattern Recognition, vol. 30, pp. 859-866, 1997.
P. Scheunders, “Comparison of clustering algorithms applied to colour image quantization”, Pattern Recognition Letters, vol. 18, pp. 1379-1384, 1997.
P. Scheunders, Livens, S., Van de Wouwer, G., Vautrot, P., and Van Dyck, D., “Wavelet-based texture analysis”, Intern. Journal on Computer Science and Information Management, vol. 1, pp. 22-34, 1998.
P. Scheunders, “Joint quantization and error-diffusion of color images using competitive learning”, Journal of the IEE Proceedings, Vision, Image and Signal Processing, vol. 14, pp. 137-140, 1998.
P. Scheunders, De Backer, S., and Naud, A., “Non-linear mapping for feature extraction”, Lecture Notes in Computer Science, vol. 1451, pp. 823-830, 1998.
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, “Local mapping for multispectral image visualisation”, Image and Vision Computing, vol. 19, pp. 971-978, 2001.
P. Scheunders and De Backer, S., “High-dimensional clustering using frequency sensitive competitive learning”, Pattern Recognition, vol. 32, pp. 193-202, 1999.
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, “An orthogonal wavelet representation of multivalued images”, IEEE Transactions on Image Processing, vol. 12, pp. 718-725, 2003.
J. Sanctorum, Sijbers, J., and De Beenhouwer, J., “Virtual grating approach for Monte Carlo simulations of edge illumination-based x-ray phase contrast imaging”, Optics Express, vol. 31, no. 21, pp. 38695-38708, 2022.PDF icon Download paper (2.95 MB)

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