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F. Tajdari, Huysmans, T., Yang, Y., and Song, Y., “Feature preserving non-rigid iterative weighted closest point and semi-curvature registration”, IEEE Transactions on Image Processing, 2022.
X. Tao, Koirala, B., Plaza, A., and Scheunders, P., “A New Dual-Feature Fusion Network for Enhanced Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, pp. 1-1, 2024.PDF icon Download paper (2.13 MB)
C. M. W. Tax, Jeurissen, B., Vos, S. B., Viergever, M. A., and Leemans, A., “Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data.”, NeuroImage, vol. 86, pp. 67-80, 2014.
G. Thoonen, Hufkens, K., Vanden Borre, J., Spanhove, T., and Scheunders, P., “Accuracy assessment of contextual classification results for vegetation mapping”, International Journal of Applied Earth Observation and Geoinformation, vol. 15, pp. 7 - 15, 2012.
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.
G. Thoonen, Spanhove, T., Vanden Borre, J., and Scheunders, P., “Classification of heathland vegetation in a hierarchical contextual framework”, International Journal of Remote Sensing, vol. 34, no. 1, pp. 96 - 111, 2013.
G. Thoonen, Nys, B., Haegen, V. Y., Roy, D. G., and Scheunders, P., “Automatic forensic analysis of automotive paints using optical microscopy”, Forensic Science International, vol. 259, pp. 210-220, 2016.
L. Tits, Heylen, R., Somers, B., Scheunders, P., and Coppin, P., “A geometric unmixing concept for the selection of optimal binary endmember combinations”, IEEE Geoscience and Remote Sensing letters, vol. 12, pp. 82-86, 2015.
J. - D. Tournier, Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C. - H., and Connelly, A., “MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation.”, Neuroimage, p. 116137, 2019.
I. R. Tsang and Tsang, I. J., “Cluster size diversity, percolation, and complex systems”, Physical Review E, vol. 60, pp. 2684-2698, 1999.
I. J. Tsang, Tsang, I. R., De Boeck, B., and Van Dyck, D., “Scaling and critical probability for cluster size and lattice animals diversity on randomly occupied square lattices”, Journal of Physics A: Mathematical and General, vol. 33, pp. 2739-2754, 2000.
I. J. Tsang, Tsang, I. R., and Van Dyck, D., “Image processing using neighbourhood coding”, Pattern Recognition Letters, vol. 20, pp. 1279-1286, 1999.
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W. Van Aarle, Batenburg, K. J., Van Gompel, G., Van de Casteele, E., and Sijbers, J., “Super-resolution for computed tomography based on discrete tomography”, IEEE Transactions on Image Processing, vol. 23, no. 3, pp. 1181 - 1193, 2014.PDF icon Download paper (2.24 MB)
W. Van Aarle, Batenburg, K. J., and Sijbers, J., “Optimal threshold selection for segmentation of dense homogeneous objects in tomographic reconstructions”, IEEE Transactions on Medical Imaging, vol. 30, pp. 980-989, 2011.PDF icon Download paper (1.59 MB)
W. Van Aarle, Ludwig, W., King, A., and Penumadu, D., “An accurate projection model for diffraction image formation and inversion using a polychromatic cone beam”, Journal of Applied Crystallography, vol. 48, pp. 334-343, 2015.
W. Van Aarle, Palenstijn, W. J., De Beenhouwer, J., Altantzis, T., Bals, S., Batenburg, K. J., and Sijbers, J., “The ASTRA Toolbox: a platform for advanced algorithm development in electron tomography”, Ultramicroscopy, vol. 157, pp. 35–47, 2015.PDF icon Download paper (3.47 MB)
W. Van Aarle, Palenstijn, W. J., Cant, J., Janssens, E., Bleichrodt, F., Dabravolski, A., De Beenhouwer, J., Batenburg, K. J., and Sijbers, J., “Fast and Flexible X-ray Tomography Using the ASTRA Toolbox”, Optics Express, vol. 24, pp. 25129-25147, 2016.PDF icon Download paper (8.34 MB)
W. Van Aarle, Batenburg, K. J., and Sijbers, J., “Automatic parameter estimation for the Discrete Algebraic Reconstruction Technique (DART)”, IEEE Transactions on Image Processing, vol. 21, no. 11, pp. 4608-4621, 2012.PDF icon Download paper (3.91 MB)
S. Van Aert, De Backer, A., Martinez, G. T., den Dekker, A. J., Van Dyck, D., Bals, S., and Van Tendeloo, G., “Advanced electron crystallography through model-based imaging”, IUCrJ, vol. 3, 2016.
J. Van Audekerke, Verhoye, M., Peeters, R. R., Sijbers, J., and Van Der Linden, A., “Special designed RF-antenna with integrated non-invasive carbon electrodes for simultaneous MRI and EEG acquisition at 7T”, Magnetic Resonance Imaging, vol. 18, pp. 887-891, 2000.PDF icon Download full paper (179 KB)
N. Van Camp, Blockx, I., Verhoye, M., Casteels, C., Coun, F., Leemans, A., Sijbers, J., Baekelandt, V., Van Laere, K., and Van Der Linden, A., “Diffusion tensor imaging in a rat model of Parkinson's disease after lesioning of the nigrostriatal tract.”, NMR in biomedicine, vol. 22, no. 7, pp. 697-706, 2009.
N. Van Camp, Blockx, I., Camon, L., de Vera, N., Verhoye, M., Veraart, J., Van Hecke, W., Martinez, E., Guadelupe, S., Sijbers, J., Planas, A., and Van Der Linden, A., “A complementary DTI-histological study in a model of Huntingtons disease”, Neurobiology of Aging, vol. 33, pp. 945-959, 2012.
N. Van Camp, Vreys, R., Van Laere, K., Lauwers, E., Beque, D., Verhoye, M., Casteels, C., Verbruggen, A., Debyser, Z., Mortelmans, L., Sijbers, J., Nuyts, J., Baekelandt, V., and Van Der Linden, A., “Morphologic and functional changes in the unilateral 6-hydroxydopamine lesion rat model for Parkinson's disease discerned with microSPECT and quantitative MRI.”, Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 23, no. 2, pp. 65-75, 2010.
S. Van Cauter, Veraart, J., Sijbers, J., Peeters, R. R., Himmelreich, U., Gool, V. S., Van Calenbergh, F., De Vleeschouwer, S., Van Hecke, W., and Sunaert, S., “Diffusion kurtosis imaging in the grading of gliomas”, Radiology, vol. 2, pp. 492-501, 2012.
M. Van Dael, Rogge, S., Verboven, P., Saeys, W., Sijbers, J., and Nicolai, B., “Online Tomato Inspection Using X-Ray Radiographies and 3- Dimensional Shape Models”, Chemical Engineering Transactions, vol. 44, pp. 37-42, 2015.

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