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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, 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.
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.
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.
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, 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.
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., and Van Dyck, D., “Image processing using neighbourhood coding”, Pattern Recognition Letters, vol. 20, pp. 1279-1286, 1999.
I. R. Tsang, “Pattern Recognition and Complex Systems”, University of Antwerp, Antwerp, 2000.
I. J. Tsang, “Pattern Recognition, Neighborhood Codes, and Lattice Animals”, University of Antwerp, Antwerp, 2000.
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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, Crombecq, K., Couckuyt, I., Batenburg, K. J., and Sijbers, J., “Efficient parameter estimation for discrete tomography using adaptive modeling”, in 11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2011.PDF icon Download full paper (853.19 KB)
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)
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, 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, 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, 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.
W. Van Aarle, Van Gompel, G., Batenburg, K. J., Van de Casteele, E., and Sijbers, J., “A 3-dimensional discrete tomography approach for superresolution micro-CT images: application to foams”, in The first international conference on image formation in X-ray computed tomography, 2010, pp. 45-48.PDF icon Download full paper (816.87 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., 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)

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