Publications

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Thesis
S. De Backer, “Unsupervised Pattern Recognition - Dimensionality Reduction and Classification”, University of Antwerp, Antwerp, 2002.
Journal Article
A. Duijster, Scheunders, P., and De Backer, S., “Wavelet-Based EM Algorithm for Multispectral-Image Restoration”, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3892-3898, 2009.
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.
W. Van den Broek, Verbeeck, J., Schryvers, D., De Backer, S., and Scheunders, P., “Tomographic Spectroscopic Imaging; an experimental proof of concept”, Ultramicroscopy, vol. 109, pp. 296-303, 2009.
S. De Backer and Scheunders, P., “Texture segmentation by frequency-sensitive elliptical competitive learning”, Image and Vision Computing, vol. 19, pp. 639-648, 2001.
G. Liu, Nath, T., Guo, Z., Linneweber, G., Claeys, A., Li, J., Bengochea, M., De Backer, S., Weyn, B., Sneyders, M., Nicasy, H., Yu, P., Scheunders, P., and Hassan, B., “A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila”, Plos Computational Biology, vol. 14, no. 8, p. e1006410, 2018.
W. Van Hecke, Leemans, A., D'Agostino, E., De Backer, S., Vandervliet, E., Parizel, P. M., and Sijbers, J., “Nonrigid Coregistration of Diffusion Tensor Images Using a Viscous Fluid Model and Mutual Information”, IEEE Transactions on Medical Imaging, vol. 26, pp. 1598-1612, 2007.PDF icon Download paper (1.85 MB)
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.
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.
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.
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.
A. Duijster, De Backer, S., and Scheunders, P., “Multicomponent image restoration, an experimental study”, Lecture Notes in Computer Science, vol. 4633, pp. 58-68, 2007.
S. De Backer, Cornelissen, F., Lemeire, J., Nuydens, R., Meert, T., Schelkens, P., and Scheunders, P., “Mosiacing of Fibered Fluorescence Microscopy Video”, Lecture notes in Computer Science, vol. 5259, pp. 915-923, 2008.
P. Kempeneers, Zarco-Tejada, P. J., North, P. R. J., De Backer, S., Delalieux, S., Sepulcre-Canto, G., Morales, F., van Aardt, J., Sagardoy, R., Coppin, P., and Scheunders, P., “Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery”, International Journal of Remote Sensing, vol. 29, pp. 5093-5111, 2008.
J. Juntu, Sijbers, J., De Backer, S., Rajan, J., and Van Dyck, D., “A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images”, Journal of Magnetic Resonance Imaging, vol. 31, pp. 680–689, 2010.PDF icon Download paper (300.61 KB)
P. Scheunders and De Backer, S., “High-dimensional clustering using frequency sensitive competitive learning”, Pattern Recognition, vol. 32, pp. 193-202, 1999.
S. Yu, De Backer, S., and Scheunders, P., “Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery”, Pattern Recognition Letters, vol. 23, pp. 183-190, 2002.
P. Kempeneers, De Backer, S., Debruyn, W., and Scheunders, P., “Generic Wavelet-Based Hyperspectral Classification Applied to Vegetation Stress Detection”, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, pp. 610-614, 2005.
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.
J. Praet, Manyakov, N., Muchene, L., Mai, Z., Terzopoulos, V., De Backer, S., Torremans, A., Guns, P. - J., Van De Casteele, T., Bottelbergs, A., Van Broeck, B., Sijbers, J., Smeets, D., Shkedy, Z., Bijnens, L., Pemberton, D., Schmidt, M., Van Der Linden, A., and Verhoye, M., “Diffusion kurtosis imaging allows the early detection and longitudinal follow-up of amyloid β-induced pathology.”, Alzheimer's Research & Therapy , vol. 10, no. 1, pp. 1-16, 2018.
S. De Backer, Pizurica, A., Huysmans, B., Philips, W., and Scheunders, P., “Denoising of Multicomponent Images Using Wavelet Least-Squares Estimators”, Image and Vision Computing, vol. 26, pp. 1038-1051, 2008.
W. Van Hecke, Sijbers, J., D'Agostino, E., Maes, F., De Backer, S., Vandervliet, E., Parizel, P. M., and Leemans, A., “On the construction of an inter-subject diffusion tensor magnetic resonance atlas of the healthy human brain”, NeuroImage, vol. 43, pp. 69-80, 2008.PDF icon Download paper (3.34 MB)
W. Van Hecke, Sijbers, J., De Backer, S., Poot, D. H. J., Parizel, P. M., and Leemans, A., “On the construction of a ground truth framework for evaluating voxel-based diffusion tensor MRI analysis methods”, NeuroImage, vol. 46, pp. 692-707, 2009.PDF icon Download paper (4.14 MB)
S. De Backer and Scheunders, P., “A competitive elliptical clustering algorithm”, Pattern Recognition Letters, vol. 20, pp. 1141-1147, 1999.
W. Van Hecke, Leemans, A., De Backer, S., Jeurissen, B., Parizel, P. M., and Sijbers, J., “Comparing isotropic and anisotropic smoothing for voxel-based DTI analyses: A simulation study”, Human Brain Mapping, vol. 31, pp. 98-114, 2010.

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