Publications

Export 1075 results:
Author [ Type(Desc)] Year
Journal Article
R. Heylen and Scheunders, P., A multilinear mixing model for nonlinear spectral unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 1, pp. 240-251, 2016.
A. Dabravolski, Batenburg, K. J., and Sijbers, J., A Multiresolution Approach to Discrete Tomography Using DART, PLoS ONE, vol. 9, no. 9, 2014.PDF icon Download paper (6.13 MB)
A. Leemans, Sijbers, J., De Backer, S., Vandervliet, E., and Parizel, P. M., Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data, Magnetic Resonance in Medicine, vol. 55, pp. 1414-1423, 2006.
M. Van Dael, Verboven, P., Dhaene, J., Van Hoorebeke, L., Sijbers, J., and Nicolai, B., Multisensor X-ray inspection of internal defects in horticultural products, Postharvest Biology and Technology, vol. 128, pp. 33–43, 2017.
G. Thoonen, Mahmood, Z., Peeters, S., and Scheunders, P., Multisource classification of color and hyperspectral images using color attribute profiles and composite decision fusion, Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, vol. 5, pp. 510 - 521, 2012.
B. Jeurissen, Tournier, J. - D., Dhollander, T., Connelly, A., and Sijbers, J., Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data, NeuroImage, vol. 103, pp. 411–426, 2014.
P. Scheunders, A multivalued image wavelet representation based on multiscale fundamental forms, IEEE Transactions on Image Processing, vol. 11, pp. 568-575, 2002.
E. Janssens, De Beenhouwer, J., Van Dael, M., De Schryver, T., Van Hoorebeke, L., Verboven, P., Nicolai, B., and Sijbers, J., Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection, Measurement Science and Technology, vol. 29, no. 3, 2018.PDF icon Download paper (3.4 MB)
R. F. Kooy, Reyniers, E., Verhoye, M., Sijbers, J., Cras, P., Oostra, B. A., Willems, P. J., and Van Der Linden, A., Neuroanatomy of the fragile X knockout mouse brain studied using in vivo high resolution Magnetic Resonance Imaging (MRI), European Journal of Human Genetics, vol. 7, pp. 526-532, 1999.PDF icon ejhg99.pdf (261.08 KB)
H. K. Jenssen, Oberlander, B. C., De Beenhouwer, J., Sijbers, J., and Verwerft, M., Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor, Progress in Nuclear Energy, vol. 72, pp. 55-62, 2014.
S. Verwulgen, Lacko, D., Vleugels, J., Vaes, K., Danckaers, F., De Bruyne, G., and Huysmans, T., A new data structure and workflow for using 3D anthropometry in the design of wearable products, International Journal of Industrial Ergonomics, vol. 64, pp. 108 - 117, 2018.
J. Rajan, den Dekker, A. J., and Sijbers, J., A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test, Signal Processing, vol. 103, pp. 16-23, 2014.
J. Rajan, Poot, D. H. J., Juntu, J., and Sijbers, J., Noise measurement from magnitude MRI using local estimates of variance and skewness., Physics in medicine and biology, vol. 55, no. 16, pp. N441-9, 2010.PDF icon Download paper (219.85 KB)
B. Rasti, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., Noise reduction in hyperspectral imagery: overview and application, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
A. Karami, M.Yazdi,, and Zolghadre, A., Noise Reduction of Hyperspectral Images Using Kernel Nonnegative Tucker Decomposition, IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 3, 2011.
Y. Zhang, De Backer, S., and Scheunders, P., Noise-resistant wavelet-based Bayesian fusion of multispectral and hyperspectral images, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3834-3843, 2009.
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.
S. De Backer, Naud, A., and Scheunders, P., Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction, Pattern Recognition Letters, vol. 19, pp. 711-720, 1998.
R. Heylen, Andrejchenko, V., Zahiri, Z., Parente, M., and Scheunders, P., Nonlinear hyperspectral unmixing with graphical models, IEEE Transaction on Geoscience and Remote Sensing, 2019.
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.
R. Heylen, Burazerovic, D., and Scheunders, P., Nonlinear spectral unmixing by geodesic simplex volume maximization, IEEE Journal of Selected Topics in Signal Processing, vol. 5, pp. 534-542, 2011.
R. Heylen, Scheunders, P., Gader, P., and Rangarajan, A., Nonlinear unmixing by using different metrics in a linear unmixing chain, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015.
J. Rajan, Veraart, J., Van Audekerke, J., Verhoye, M., and Sijbers, J., Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images., Magnetic resonance imaging, vol. 30, no. 10, pp. 1512-8, 2012.
J. Rajan, Veraart, J., Van Audekerke, J., Verhoye, M., and Sijbers, J., Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images, Magnetic Resonance Imaging, vol. 30, no. 10, pp. 1512-1518, 2012.PDF icon Download full paper (1.11 MB)
P. V. Sudeep, Palanisamy, P., Kesavadas, C., Sijbers, J., den Dekker, A. J., and Rajan, J., A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps, Signal Image and Video Processing, vol. 11, no. 5, pp. 913-920, 2017.

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