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G. Thoonen, Hufkens, K., Vanden Borre, J., and Scheunders, P., “Using patch metrics as validation for contextual classification of heathland vegetation.”, in Proceedings of GEOBIA 2010, the Geographic Object-Based Image Analysis Conference, 2010, vol. XXXVIII-4/C7.
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, 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.
G. Tisson, “Reconstructie van Transversaal Getrunceerde Cone Beam Projecties in Micro-Tomografie”, University of Antwerp, Antwerp, 2006.
G. Tisson, Scheunders, P., and Van Dyck, D., “3D region of interest X-ray CT for geometric magnification from multiresolution acquisitions”, in Proc. ISBI04, IEEE International Symposium on Biomedical Imaging, 15-18 april 2004, Arlington, VA, 2004, pp. 567-570.
G. Tisson, Scheunders, P., and Van Dyck, D., “ROI Cone-Beam CT on a Circular Orbit for Geometric Magnification Using Reprojection”, in Proc. IEEE Medical Imaging Conference, Rome, 16-22 october, 2004.
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.
L. Tits, Somers, B., Heylen, R., Scheunders, P., and Coppin, P., “Improving the efficiency of MESMA through geometric unmixing principles”, in SPIE Remote Sensing, Drseden, Germany, 23-26 September , 2013, vol. 8892.
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.
J. - D. Tournier, Jeurissen, B., and Christiaens, D., “Iterative model-based Rician bias correction and its application to denoising in diffusion MRI”, Proc Intl Soc Mag Reson Med. p. 3795, 2023.
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. R. Tsang and Tsang, I. J., “Cluster size diversity, percolation, and complex systems”, Physical Review E, vol. 60, pp. 2684-2698, 1999.
I. R. Tsang, “Pattern Recognition and Complex Systems”, University of Antwerp, Antwerp, 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.
I. J. Tsang, “Pattern Recognition, Neighborhood Codes, and Lattice Animals”, University of Antwerp, Antwerp, 2000.
I. R. Tsang, Tsang, I. J., Scheunders, P., and Van Dyck, D., “Pattern Recognition using neighborhood coding”, in Proc. CVPRIP'98, Intern. Workshop on Computer Vision, Pattern Recognition and Image Processing , North Carolina, october 23-28, 1998, pp. 250-253.
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W. Van Aarle, Cant, J., De Beenhouwer, J., and Sijbers, J., “Discrete tomographic reconstruction from deliberately motion blurred X-ray projections”, in 6th Conference on Industrial Computed Tomography, Wels, Austria, 2016, pp. 1-6.PDF icon Download paper (444.66 KB)
W. Van Aarle, “Tomographic segmentation and discrete tomography for quantitative analysis of transmission tomography data”, University of Antwerp, Antwerp, Belgium, 2012.PDF icon Download PhD thesis (39.16 MB)
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, 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, Ghysels, P., Sijbers, J., and Vanroose, W., “Memory access optimization for iterative tomography on many-core architectures”, in The 12th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2013, pp. 364-367.PDF icon fully3d_wvaarle.pdf (2.8 MB)
W. Van Aarle, van der Maar, S., Batenburg, K. J., and Sijbers, J., “Computed tomography on all scales using the ASTRA toolbox”, Liege Image Days 2008: Medical Imaging. 2008.PDF icon wvaarle_poster.pdf (610.59 KB)
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., “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, Batenburg, K. J., and Sijbers, J., “Threshold Selection for Segmentation of Dense Objects in Tomograms”, in International Symposium on Visual Computing, Berlin Heidelberg, 2008, vol. 5358, pp. 700-709.

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