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B. Huyge, Sanctorum, J., Jeurissen, B., De Beenhouwer, J., and Sijbers, J., “Fiber Orientation Estimation from X-ray Dark Field Images of Fiber Reinforced Polymers using Constrained Spherical Deconvolution”, Polymers, vol. 15, no. 13, p. 2887, 2023.PDF icon Download paper (2.95 MB)
Y. Huybrechts, De Ridder, R., Bergen, D., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Vergauwen, L., Schepers, D., Van Dijck, E., Tong, Q., Verhulst, A., De Beenhouwer, J., Sijbers, J., Hammond, C., Forlino, A., Mortier, G., Coucke, P., P Witten, E., Kwon, R. Young, Willaert, A., Hendrickx, G., and Van Hul, W., “Loss of the Ubiquitin-Associated Domain of sqstm1/p62 in Zebrafish Causes a Phenotype Resembling Paget’s Disease of Bone”, Calcified Tissue International, vol. 116, no. 1, pp. 1-15, 2025.
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., “The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?”, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
C. C. Hung, Scheunders, P., Pham, M., Su, M. C., and Coleman, T., “Using Intelligent Optimization Techniques in the K-means Algorithm for Multispectral Image Classification”, International Journal of Fuzzy Systems, vol. 6, pp. 107-117, 2004.
C. C. Hung, Coleman, T., and Scheunders, P., “Using genetic differential competitive learning for unsupervised training in multispectral image classification systems”, in Proceedings IEEE International Conference on Systems, Man, and Cybernetics , San Diego, California, October 11-14, 1998, pp. 4482-4485.
C. C. Hung, Coleman, T., and Scheunders, P., “The genetic algorithm approach and K-means clustering: their role in unsupervised training in image classification”, in Proc. IASTED International Conf. On Computer Graphics and Imaging , Halifax, Canada, june 1-3, 1998, pp. 103-106.
S. Huijs, Huysmans, T., De Jong, A., Arnout, N., Sijbers, J., and Bellemans, J., “Principal component analysis as a tool for determining optimal tibial baseplate geometry in modern TKA design”, Acta Orthop Belg, vol. 84, no. 4, pp. 452-460, 2018.
K. Hufkens, Thoonen, G., Vanden Borre, J., Scheunders, P., and Ceulemans, R., “Habitat reporting of a heathland site: Classification probabilities as additional information, a case study”, Ecological Informatics, vol. 5, pp. 248 - 255, 2010.
K. Hufkens, Scheunders, P., and Ceulemans, R., “Validation of the sigmoid wave curve fitting algorithm on a forest-tundra ecotone in the Northwest Territories, Canada”, Ecological Informatics, vol. 4, pp. 1-7, 2009.
K. Hufkens, Ceulemans, R., and Scheunders, P., “Estimating the ecotone width in patchy ecotones using a sigmoid wave approach”, Ecological Informatics, vol. 3, pp. 97-104, 2008.
K. Hufkens, Ceulemans, R., and Scheunders, P., “Ecotones in vegetation ecology: methodology and definitions revisited”, Ecological Research, vol. 24, pp. 977-986, 2009.
T. Hu, Li, W., Liu, N., Tao, R., Zhang, F., and Scheunders, P., “Hyperspectral Image Restoration Using Adaptive Anisotropy Total Variation and Nuclear Norms”, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 2, pp. 1516-1533, 2021.PDF icon tgrs_2020.pdf (5.71 MB)
T. Hu, Liu, N., Li, W., Tao, R., Zhang, F., and Scheunders, P., “Destriping Hyperspectral Imagery By Adaptive Anisotropic Total Variation And Truncated Nuclear Norm”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2021.
S. Hosseinnejad, Bosch, E. G. T., Kohr, H., Lazić, I., Zharinov, V., Franken, E., Sijbers, J., and De Beenhouwer, J., “3D atomic resolution tomography from iDPC-STEM images using multiple atom model prior”, Microscopy Conference. 2021.PDF icon Download abstract (534.35 KB)
M. Das and Liang, Z., “SPIE ProceedingsSingle-step, quantitative x-ray differential phase contrast imaging using spectral detection in a coded aperture setup”, in SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging, Orlando, Florida, United States, 2015, vol. 9412, p. 941252.
M. Das, Kandel, B., Park, C. Soo, and Liang, Z., “SPIE ProceedingsEnergy calibration of photon counting detectors using x-ray tube potential as a reference for material decomposition applications”, in SPIE Medical ImagingMedical Imaging 2015: Physics of Medical Imaging, Orlando, Florida, United States, 2015, vol. 9412, p. 941214.
R. Heylen, Parente, M., and Scheunders, P., “Estimation of the number of endmembers in a hyperspectral image via the hubness phenomenon”, IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 4, pp. 2191-2200, 2017.
R. Heylen, Burazerovic, D., and Scheunders, P., “Fully constrained least-squares spectral unmixing by simplex projection”, IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 11, pp. 4112-4122, 2011.PDF icon PDF (1.11 MB)Package icon Matlab code (1.93 KB)
R. Heylen, Scheunders, P., Zare, A., and Gader, P., “Alternating angle minimization based unmixing with endmember variability”, in IEEE IGARSS 2016, International Geoscience and Remote Sensing Symposium, pp. 6974-6977, Beijing, July 10-15 , 2016.
R. Heylen and Scheunders, P., “Multi-dimensional Pixel Purity Index”, in IEEE-WHISPERS 2013, Workshop on Hyperspectral Image and Signal Processing, Gainesville, Florida, June 25-28, 2013.
R. Heylen and Scheunders, P., “Calculation of geodesic distances in non-linear mixing models: demonstration on the generalized bilinear model”, IEEE Geoscience and Remote Sensing letters, vol. 9, no. 4, pp. 644-648, 2012.
R. Heylen, Burazerovic, D., and Scheunders, P., “A graph-based method for non-linear unmixing of hyperspectral imagery”, in IEEE IGARSS2010, IEEE International Geoscience and Remote Sensing Symposium, Honolulu, Haway, July 25-30, 2010, pp. 197-200.
R. Heylen, Thanki, A., Verhees, D., Iuso, D., De Beenhouwer, J., Sijbers, J., Witvrouw, A., Haitjema, H., and Bey-Temsamani, A., “3D total variation denoising in X-CT imaging applied to pore extraction in additively manufactured parts”, Measurement Science and Technology, vol. 33, no. 4, pp. 1-12, 2022.
R. Heylen and Scheunders, P., “Hyperspectral intrinsic dimensionality estimation with nearest-neighbor distance ratio's”, IEEE JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 570-579, 2013.
R. Heylen and Scheunders, P., “A fast geometric algorithm for solving the inversion problem in spectral unmixing”, in IEEE-WHISPERS 2012, Workshop on Hyperspectral Image and Signal Processing, Shanghai, June 4-7, 2012.

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