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A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter One - Introduction, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
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.
S. De Backer and Scheunders, P., Enhancement of fMRI image series with the aid of an anatomical image, in ISBI’06, IEEE International Symposium on Biomedical Imaging, Arlington, Virginia, april 6-9, 2006, pp. 1052-1055.
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.
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.
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.
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.
S. De Backer and Scheunders, P., A competitive elliptical clustering algorithm, Pattern Recognition Letters, vol. 20, pp. 1141-1147, 1999.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Five - Optimal experiment design for nanoparticle atom counting from ADF STEM images, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
S. De Backer, Kempeneers, P., Debruyn, W., and Scheunders, P., Classification of Dune Vegetation from Remotely Sensed Hyperspectral Images, in Image Analysis and Recognition Proc. of International Conference on Image Analysis and Recognition, Porto, Portugal, 2004, pp. 497-503.
S. De Backer, Unsupervised Pattern Recognition - Dimensionality Reduction and Classification, University of Antwerp, Antwerp, 2002.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Two - Statistical parameter estimation theory: principles and simulation studies, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Three - Efficient fitting algorithm, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
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.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., Chapter Four - Atom counting, in Advances in Imaging and Electron Physics,, vol. 217, Science Direct Elsevier, 2021.
J. De Beenhouwer, Sijbers, J., and Vanthienen, P. - J., Mask assembly for edge illumination phase contrast radiation imaging, U.S. Patent EP2025062978W2024.PDF icon mask_patent.pdf (6.93 MB)
J. De Beenhouwer, Palenstijn, W. J., Bleichrodt, F., Batenburg, K. J., and Sijbers, J., A framework for markerless alignment with full 3D flexibility, European Microscopy Conference. 2012.PDF icon Download abstract (117.9 KB)
J. De Beenhouwer and Sijbers, J., A PHASE‑CONTRAST X‑RAY IMAGING SYSTEM FOR OBTAINING A DARK‑FIELD IMAGE AND A METHOD THEREFOR, U.S. Patent EP 4 351 425 B12025.PDF icon Download patent (547.58 KB)
B. De Boeck, Infotree - A study of its foundations, University of Antwerp, Antwerp, 2001.
B. De Boeck, Scheunders, P., and Van Dyck, D., From inductive inference to the fundamental equations of measuerement, in Proc. First International Conference on Complex Systems, 2000, pp. 115-122.
T. De Bondt, Jacquemyn, Y., Van Hecke, W., Sijbers, J., Sunaert, S., and Parizel, P. M., Regional gray matter volume differences and sex-hormone correlations as a function of menstrual cycle phase and hormonal contraceptives use., Brain research, vol. 1530, pp. 22-31, 2013.
T. De Bondt, Van Hecke, W., Veraart, J., Leemans, A., Sijbers, J., Sunaert, S., Jacquemyn, Y., and Parizel, P. M., Does the use of hormonal contraceptives cause microstructural changes in cerebral white matter? Preliminary results of a DTI and tractography study., European radiology, vol. 23, no. 1, pp. 57-64, 2013.PDF icon Download paper (411.18 KB)
F. De Carlo, Gursoy, D., Ching, D., Batenburg, K. J., Ludwig, W., Mancini, L., Welford, F. M., Mokso, R., Pelt, D., Sijbers, J., and Rivers, M., TomoBank: A Tomographic Data Repository for Computational X-ray Science, Measurement Science and Technology, vol. 29, no. 3, pp. 1-10, 2018.PDF icon Download paper (5.71 MB)
G. De Groof, Verhoye, M., Van Meir, V., Tindemans, I., Leemans, A., and Van Der Linden, A., In Vivo Visualization of the Neuroanatomy and Brain Connectivity of Starling Brain Through Diffusion Tensor Imaging, in 6th Bi-Annual Meeting – Belgian Society for Neuroscience, Brussels, Belgium, 2005.
G. De Groof, Verhoye, M., Van Meir, V., Tindemans, I., Leemans, A., and Van Der Linden, A., In vivo diffusion tensor imaging (DTI) of brain subdivisions and vocal pathways in songbirds, NeuroImage, vol. 29, pp. 754-763, 2006.

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