Publications

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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., “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., “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.
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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, “Pattern Recognition and Complex Systems”, University of Antwerp, Antwerp, 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. J. Tsang, “Pattern Recognition, Neighborhood Codes, and Lattice Animals”, 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.
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.
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.
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.
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, “Reconstructie van Transversaal Getrunceerde Cone Beam Projecties in Micro-Tomografie”, University of Antwerp, Antwerp, 2006.
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. 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.
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, “Contextual classification of hyperspectral remote sensing images - Application in vegetation monitoring”, University of Antwerp, Antwerp, Belgium, 2012.PDF icon Download thesis (17.15 MB)
G. Thoonen, Vanden Borre, J., De Backer, S., and Scheunders, P., “Assessing the quality of heathland vegetation by classification of hyperspectral data using spatial information”, in Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009, Cape Town, South Africa, 2009, vol. 4, p. IV-330 - IV-333.
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, 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.

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