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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.

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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.

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.

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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.

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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., “Determination of volumetric abundance of intimate mixture using Bayesian MCMC”, IEEE Sensors Journal, pp. 1-1, 2024.

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F. Schmidt, Koirala, B., and Andrieu, F., “Validation of abundance determination of granular mixture using radiative transfer and Bayesian MCMC”, EPSC2024. 2024.

exhibit_17_validation_of_abundance_determination_of_granular_mixture_using_radiative_transfer_and_bayesian_mcmc.pdf (977.09 KB)

P. Scheunders, “A genetic Lloyd-Max image quantization algorithm”, Pattern Recognition Letters, vol. 17, pp. 547-556, 1996.

P. Scheunders and De Backer, S., “Multispectral image fusion and merging using multiscale fundamental forms”, in Proc. ICIP01, IEEE International Conference on Image Processing, Thessaloniki, Greece, 2001, pp. 902-905.

P. Scheunders, “Denoising of multispectral images using wavelet thresholding”, in Proc. SPIE conference on Image and Signal Processing for Remote Sensing IX, part of the International Symposium on Remote Sensing, Barcelona, Spain, 2003, pp. 28-35.

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, 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, “Multivalued image segmentation based on first fundamental form”, in Proc. ICIAP, International Conference on Image Analysis and Processing, Palermo, Italy, 2001, pp. 185-190.

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, 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, “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, “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, “Comparison of clustering algorithms applied to colour image quantization”, Pattern Recognition Letters, vol. 18, pp. 1379-1384, 1997.

P. Scheunders, “Wavelet thresholding of multispectral images”, in Proc. ACIVS03, Andvanced Concepts for intelligent vision systems , Ghent, 2003, pp. 255-259.

P. Scheunders and De Backer, S., “High-dimensional clustering using frequency sensitive competitive learning”, Pattern Recognition, vol. 32, pp. 193-202, 1999.

P. Scheunders, “Local mapping for multispectral image visualisation”, Image and Vision Computing, vol. 19, pp. 971-978, 2001.

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