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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., and Van Dyck, D., “Image processing using neighbourhood coding”, Pattern Recognition Letters, vol. 20, pp. 1279-1286, 1999.
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.
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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, 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., 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., “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, 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, 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)
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, 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.
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.
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.
M. Van Dael, Lebotsa, S., Herremans, E., Verboven, P., Sijbers, J., Opara, U. L., Cronje, U. L., and Nicolai, B., “A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs”, Postharvest Biology and Technology, vol. 112, pp. 205-214, 2016.
M. Van Dael, Verboven, P., Zanella, A., Sijbers, J., and Nicolai, B., “Combination of shape and X-ray inspection for apple internal quality control: in silico analysis of the methodology based on X-ray computed tomography”, Postharvest Biology and Technology, vol. 148, pp. 218-227, 2019.
M. Van Dael, Verboven, P., Dhaene, J., Van Hoorebeke, L., Sijbers, J., and Nicolai, B., “Multisensor X-ray inspection of internal defects in horticultural products”, Postharvest Biology and Technology, vol. 128, pp. 33–43, 2017.
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., “An energy-based beam hardening model in tomography”, Physics in Medicine and Biology, vol. 47, pp. 4181-4190, 2002.PDF icon Download full paper (203.21 KB)
E. Van de Casteele, Van Dyck, D., Sijbers, J., and Raman, E., “A model-based correction method for beam hardening artefacts in X-ray microtomography”, Journal of X-ray science and technology, vol. 12, pp. 53-57, 2004.PDF icon Download full paper (632.04 KB)
E. Van de Casteele, Perilli, E., Van Aarle, W., Reynolds, K., and Sijbers, J., “Discrete tomography in an in vivo small animal bone study”, Journal of Bone and Mineral Metabolism, vol. 36, no. 1, pp. 40–53, 2018.
T. Van De Looverbosch, Jiaqi, H., Tempelaere, A., Kelchtermans, K., Verboven, P., Tuytelaars, T., Sijbers, J., and Nicolai, B., “Inline nondestructive internal disorder detection in pear fruit using explainable deep anomaly detection on X-ray images”, Computers and Electronics in Agriculture, vol. 197, no. 106962, pp. 1-14, 2022.
T. Van De Looverbosch, Bhuiyan, H. Rahman, Verboven, P., Dierick, M., Van Loo, D., De Beenhouwer, J., Sijbers, J., and Nicolai, B., “Nondestructive internal quality inspection of pear fruit by X-ray CT using machine learning”, Food Control, vol. 113, no. 107170, pp. 1-13, 2020.

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