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Conference Paper

P. Kempeneers, Sterckx, S., Debruyn, W., Park, Y., Ruddick, K., De Backer, S., and Scheunders, P., “Retrieval of oceanic constituents from ocean color using simulated annealing”, in IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, 25-29 July, 2005, vol. 8, pp. 5651-5654.

G. Thoonen, De Backer, S., Provoost, S., Kempeneers, P., and Scheunders, P., “Spatial Classification of Hyperspectral Data of Dune Vegetation along the Belgian Coast”, in Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International, Boston, MA, USA, 2008, vol. 3, p. III-483 - III-486.

P. Kempeneers, De Backer, S., Tejada, Z. P. J., Delalieux, S., Canto, S. G., Iribas, M. F., van Aardt, J., Coppin, P., and Scheunders, P., “Stress detection in orchards with hyperspectral remote sensing data”, in SPIE Remote Sensing, Stockholm, Sweden, september 11-14, 2006, vol. 6359.

S. De Backer and Scheunders, P., “Texture segmentation by frequency-sensitive elliptical competitive learning”, in Proc. ICIAP99, International Conference on Image Analysis and Processing , Venice, Italy, september 27-29, 1999, pp. 64-69.

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.

A. Leemans, De Backer, S., Sijbers, J., Vandervliet, E., and Parizel, P. M., “TRACT: Tissue Relative Anisotropy based Curvature Thresholding for deterministic MR diffusion tensor tractography”, in 22th Annual Scientific Meeting - European Society for Magnetic Resonance in Medicine and Biology, Basle, Switzerland, 2005, p. 289.

P. Kempeneers, De Backer, S., Delalieux, S., Sterckx, S., Debruyn, W., Coppin, P., and Scheunders, P., “Upscaling of spectroradiometer data for stress detection in orchards with remote sensing”, in SPIE Remote Sensing, Gran Canaria, 13-16 september, Maspalomas, Spain, 2004, vol. 127, pp. 37-45.

P. Kempeneers, De Backer, S., Debruyn, W., and Scheunders, P., “Wavelet Based Feature Extraction for Hyperspectral Vegetation Monitoring”, in SPIE International Symposium on Remote Sensing, Image and Signal Processing for Remote Sensing IX, Barcelona, Spain, 2003, pp. 297-305.

S. De Backer, Kempeneers, P., Debruyn, W., and Scheunders, P., “Wavelet Based Hyperspectral Data Analysis for Vegetation Stress Classification”, in Proc. of Advanced Concepts for Intelligent Vision Systems, Brussels, Belgium, 2004, pp. 387-391.

P. Scheunders and De Backer, S., “Wavelet Denoising of multicomponent images using a Gaussian Scale Mixture model”, in ICPR’06, International Conference on Pattern Recognition, Hong Kong, august 20-24, 2006, vol. 3, pp. 754-757.

P. Scheunders and De Backer, S., “Wavelet Denoising of multicomponent images using a noise-free image”, in ICIP’06, IEEE International Conference on Image Processing, Atlanta, Georgia, October 8-11, 2006, pp. 2619-2622.

P. Scheunders and De Backer, S., “Wavelet-based enhancement of remote sensing and biomedical image series using an auxiliary image”, in SPIE Optics East, 23-26 October, Boston, Massachusetts USA, 2005, vol. 6001, pp. 41-52.

A. Duijster, De Backer, S., and Scheunders, P., “Wavelet-based Multicomponent Image Restoration”, in Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, United States, September 9-12, 2007, vol. 6763.

A. Duijster, De Backer, S., and Scheunders, P., “Wavelet-based Multispectral Image Restoration”, in IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008, vol. 3, pp. 79-82.

Journal Article

W. Van den Broek, Verbeeck, J., De Backer, S., Scheunders, P., and Schryvers, D., “Acquisition of the EELS data cube by tomographic reconstruction”, Ultramicroscopy, vol. 106, pp. 269-276, 2006.

A. Leemans, Sijbers, J., De Backer, S., Vandervliet, E., and Parizel, P. M., “Affine Coregistration of Diffusion Tensor Magnetic Resonance Images Using Mutual Information”, Lecture Notes in Computer Science, vol. 3708, pp. 523-530, 2005.

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S. De Backer, Kempeneers, P., Debruyn, W., and Scheunders, P., “A Band Selection Technique for Spectral Classification”, IEEE Geoscience and Remote Sensing Letters, vol. 2, pp. 319-323, 2005.

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.

S. De Backer and Scheunders, P., “A competitive elliptical clustering algorithm”, Pattern Recognition Letters, vol. 20, pp. 1141-1147, 1999.

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.

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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.

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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.

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.

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.

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.

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