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P. Scheunders, “A genetic Lloyd-Max image quantization algorithm”, Pattern Recognition Letters, vol. 17, pp. 547-556, 1996.
P. Scheunders and Driesen, J., “Least squares interband denoising of color and multispectral images”, in Proc. ICIP2004, IEEE International Conference on Image Processing, 24-27 october, Singapore, 2004, pp. 985-988.
P. Scheunders, “Multiscale Edge Representation Applied to Image Fusion”, in Proc. Wavelet Applications in Signal and Image Processing VIII, 2000, pp. 894-901.
P. Scheunders, De Backer, S., Pizurica, A., Huysmans, B., and Philips, W., “Bayesian Wavelet-based Denoising of Multicomponent Images”, in Proceedings Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, 9-12 september, Vol. 6763-OK (12 pages), 2007.
P. Scheunders and Sijbers, J., “Multiscale watershed segmentation of multivalued images”, in Proc. ICPR02, International Conference on Pattern Recognition, Quebec, Canada, 2002, vol. 3, pp. 855-858.
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 and De Backer, S., “Joint quantization and error-diffusion of color images using competitive learning”, in Proc. IEEE Conference on Image Processing , Santa Barbara, 26-29 october, 1997, pp. 811-814.
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, 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 Sijbers, J., “Multiscale anisotropic filtering of color images”, in Proceedings of the IEEE International Conference on Image Processing, Thessaloniki, Greece, 2001, vol. 3, pp. 170-173.
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, “Comparison of clustering algorithms applied to colour image quantization”, Pattern Recognition Letters, vol. 18, pp. 1379-1384, 1997.
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.
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.
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)
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, 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.
K. Rafiezadeh Shahi, “Unsupervised machine/deep learning mapping (clustering) for single/multi-source remote sensing data ”, 2023.
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)

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