Publications

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J. Morez, Sijbers, J., Vanhevel, F., and Jeurissen, B., “Constrained spherical deconvolution of non-spherically sampled diffusion MRI data”, Human Brain Mapping, vol. 42, pp. 521–538, 2020.PDF icon Download paper (5.87 MB)
S. Mukunthan, Vleugels, J., Huysmans, T., and De Bruyne, G., “Latent Heat Loss of a Virtual Thermal Manikin for Evaluating the Thermal Performance of Bicycle Helmets”, in Advances in Human Factors in Simulation and Modeling, Cham, 2019, pp. 66–78.
S. Mukunthan, Kuklane, K., Huysmans, T., and De Bruyne, G., “A Comparison Between Physical and Virtual Experiments of Convective Heat Transfer Between Head and Bicycle Helmet”, in 8th International Conference on Applied Human Factors and Ergonomics (AHFE 2017), Los Angeles, California, USA, 2017.
S. Mukunthan, Vleugels, J., Huysmans, T., Mayor, T. Sotto, and De Bruyne, G., “A 3D Printed Thermal Manikin Head for Evaluating Helmets for Convective and Radiative Heat Loss”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) Volume VII, 2019, vol. VII, pp. 592–602.
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M. Naeyaert, Aelterman, J., Golkov, V., Cremers, D., Pizurica, A., Sijbers, J., and Verhoye, M., “Accelerating in vivo fast spin echo high angular resolution diffusion imaging with an isotropic resolution in mice through compressed sensing”, Magnetic Resonance in Medicine, vol. 85, no. 3, pp. 1397-1413, 2021.
M. Naeyaert, Aelterman, J., Van Audekerke, J., Claes, K., Van Der Linden, A., Sijbers, J., and Verhoye, M., “Optimization of Compressed Sensing/RARE Combining Acquisition Schemes”, European Society for Magnetic Resonance in Medicine and Biology, vol. 25, no. 1. pp. 513-514, 2012.
M. Naeyaert, Roose, D., Mai, Z., Keliris, A. J., Sijbers, J., Van Der Linden, A., and Verhoye, M., “Normalized Averaged Range (nAR), a Robust Quantification Method for MPIO-content”, Journal of Magnetic Resonance, vol. 300, pp. 18-27, 2019.
M. Naeyaert, Golkov, V., Cremers, D., Sijbers, J., and Verhoye, M., “Faster and better HARDI using FSE and holistic reconstruction”, International Society for Magnetic Resonance in Medicine (ISMRM) Annual Meeting. 2021.
M. Naeyaert, “Strategies for efficient acquisition and reconstruction of structural and quantitative MRI”, 2021.
G. Nagels, Vandervliet, E., Van Hecke, W., Engelborghs, S., hooghe, M. B. D., Cras, P., Parizel, P. M., and De Deyn, P. P., “fMRI during PASAT and PVSAT in mild MS, moderate MS and normal volunteers.”, in 22nd Congress of the European Committee for, Madrid, Spain, 2006.
J. Nam, Mysore, G. J., Ganseman, J., Lee, K., and Abel, J. S., “A super-resolution spectrogram using coupled PLCA”, in INTERSPEECH, Makuhari, Japan, 2010, pp. 1696-1699.
T. Nath, Liu, G., Weyn, B., Hassan, B., De Backer, S., and Scheunders, P., “Tracking for Quantifying Social Network of Drosophila Melanogaster”, in 15th Computer Analysis of Images and Patterns (CAIP), 2013, vol. 8048, pp. 539–545.
T. Nath, G.Liu,, Weyn, B., Hassan, B., De Backer, S., and Scheunders, P., “Automated Social behaviour Recognition At Low Resolution”, in 22nd IEEE - International Conference of Pattern Recognition (ICPR), 2014.
M. Nauwynck, Bazrafkan, S., Van Heteren, A., De Beenhouwer, J., and Sijbers, J., “Ring Artifact Reduction in Sinogram Space Using Deep Learning”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (2.49 MB)
E. Nazemi, Six, N., Iuso, D., De Samber, B., Sijbers, J., and De Beenhouwer, J., “Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction”, Applied Sciences, vol. 11, no. 7, 2021.PDF icon Download paper (4.96 MB)
Z. H. Nezhad, Karami, A., Heylen, R., and Scheunders, P., “Fusion of Hyperspectral and Multispectral Images Using Spectral Unmixing and Sparse Coding”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 9, no. 6, pp. 2377-2389, 2016.
Z. H. Nezhad, Karami, A., Heylen, R., and Scheunders, P., “Superresolution Of Hyperspectral Images Using Spectral Unmixing And Sparse Regularization”, in IGARSS 2016, Beijing China, 2016.
V. Nguyen, Sanctorum, J., Van Wassenbergh, S., Dirckx, J. J. J., Sijbers, J., and De Beenhouwer, J., “Geometry Calibration of a Modular Stereo Cone-Beam X-ray CT System”, Journal of Imaging, vol. 7, no. 54, pp. 1-12, 2021.PDF icon Download paper (4.2 MB)
A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “Analytic derivatives of scaling motion-compensated projection operators for dynamic computed tomography”, in e-Journal of Nondestructive Testing, 2022, vol. 27 (3), pp. 1-5.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., “A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system”, Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 252-265, 2020.
A. - T. Nguyen, Renders, J., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “An accelerated motion-compensated iterative reconstruction technique for dynamic computed tomography”, in Proc. SPIE 12242, Developments in X-Ray Tomography XIV, 122421F, San Diego, CA, United States, 2022.
A. - T. Nguyen, Renders, J., Iuso, D., Maris, Y., Soete, J., Wevers, M., Sijbers, J., and De Beenhouwer, J., “MIRT: a simultaneous reconstruction and affine motion compensation technique for four dimensional computed tomography (4DCT)”. arXiv.org e-Print archive, 2024.PDF icon siam_mirt.pdf (2.85 MB)
A. - T. Nguyen, Renders, J., Sijbers, J., and De Beenhouwer, J., “Reconstruction with rigid motion correction technique in CT imaging: A simulation and application study”, Workshop on Scientific Computing and Applications. Vietnam Institute for Advanced Study in Mathematics (VIASM), Hanoi, Vietnam, 2024.PDF icon wsca2024.pdf (110.08 KB)PDF icon wsca2024_slides.pdf (2.75 MB)
H. Q. Nguyen, Nguyen, B. T., Dong, T. Q., Ngo, D. T., and Nguyen, A. - T., “Deep Q-Learning with Multiband Sensing for Dynamic Spectrum Access”, in IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), Seoul, Korea, 2018.
A. - T. Nguyen, “Signal compression using compressed sensing and best k-term approximation: An overview”, Viettel R&D Institute, Hanoi, Vietnam, 2018.PDF icon csbkta.pdf (636.54 KB)

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