Publications

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Journal Article
A. Dabravolski, Batenburg, K. J., and Sijbers, J., A Multiresolution Approach to Discrete Tomography Using DART, PLoS ONE, vol. 9, no. 9, 2014.PDF icon Download paper (6.13 MB)
A. Leemans, Sijbers, J., De Backer, S., Vandervliet, E., and Parizel, P. M., Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data, Magnetic Resonance in Medicine, vol. 55, pp. 1414-1423, 2006.
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.
B. Jeurissen, Tournier, J. - D., Dhollander, T., Connelly, A., and Sijbers, J., Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data, NeuroImage, vol. 103, pp. 411–426, 2014.
E. Janssens, De Beenhouwer, J., Van Dael, M., De Schryver, T., Van Hoorebeke, L., Verboven, P., Nicolai, B., and Sijbers, J., Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection, Measurement Science and Technology, vol. 29, no. 3, 2018.PDF icon Download paper (3.4 MB)
R. F. Kooy, Reyniers, E., Verhoye, M., Sijbers, J., Cras, P., Oostra, B. A., Willems, P. J., and Van Der Linden, A., Neuroanatomy of the fragile X knockout mouse brain studied using in vivo high resolution Magnetic Resonance Imaging (MRI), European Journal of Human Genetics, vol. 7, pp. 526-532, 1999.PDF icon ejhg99.pdf (261.08 KB)
H. K. Jenssen, Oberlander, B. C., De Beenhouwer, J., Sijbers, J., and Verwerft, M., Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor, Progress in Nuclear Energy, vol. 72, pp. 55-62, 2014.
J. Rajan, den Dekker, A. J., and Sijbers, J., A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test, Signal Processing, vol. 103, pp. 16-23, 2014.
J. Rajan, Poot, D. H. J., Juntu, J., and Sijbers, J., Noise measurement from magnitude MRI using local estimates of variance and skewness., Physics in medicine and biology, vol. 55, no. 16, pp. N441-9, 2010.PDF icon Download paper (219.85 KB)
T. Van De Looverbosch, Raeymaekers, E., Verboven, P., Sijbers, J., and Nicolai, B., Non-destructive internal disorder detection of Conference pears by semantic segmentation of X-ray CT scans using deep learning, Expert Systems with Applications, vol. 176, no. 114925, pp. 1-12, 2021.
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.
J. Rajan, Veraart, J., Van Audekerke, J., Verhoye, M., and Sijbers, J., Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images, Magnetic Resonance Imaging, vol. 30, no. 10, pp. 1512-1518, 2012.PDF icon Download full paper (1.11 MB)
J. Rajan, Veraart, J., Van Audekerke, J., Verhoye, M., and Sijbers, J., Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images., Magnetic resonance imaging, vol. 30, no. 10, pp. 1512-8, 2012.
P. V. Sudeep, Palanisamy, P., Kesavadas, C., Sijbers, J., den Dekker, A. J., and Rajan, J., A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps, Signal Image and Video Processing, vol. 11, no. 5, pp. 913-920, 2017.
W. Van Hecke, Leemans, A., D'Agostino, E., De Backer, S., Vandervliet, E., Parizel, P. M., and Sijbers, J., Nonrigid Coregistration of Diffusion Tensor Images Using a Viscous Fluid Model and Mutual Information, IEEE Transactions on Medical Imaging, vol. 26, pp. 1598-1612, 2007.PDF icon Download paper (1.85 MB)
M. Naeyaert, Roose, D., Mai, Z., Keliris, A. J., Sijbers, J., Van Der Linden, A., and Verhoye, M., Normalized Averaged Range (nAR), a Robust Quantification Method for MPIO-content, Journal of Magnetic Resonance, vol. 300, pp. 18-27, 2019.
G. Ramos-Llordén, Vegas-Sánchez-Ferrero, G., Björk, M., Vanhevel, F., Parizel, P. M., Estépar, R. San José, den Dekker, A. J., and Sijbers, J., NOVIFAST: A fast algorithm for accurate and precise VFA MRI T1 mapping, IEEE Transactions on Medical Imaging, vol. 37, no. 11, pp. 2414 - 2427, 2018.PDF icon Download paper (3.3 MB)
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.
J. Morez, Szczepankiewicz, F., den Dekker, A. J., Vanhevel, F., Sijbers, J., and Jeurissen, B., Optimal experimental design and estimation for q-space trajectory imaging, Human Brain Mapping, vol. 44, no. 4, pp. 1793-1809, 2023.PDF icon Download paper (5.87 MB)
D. H. J. Poot, den Dekker, A. J., Achten, E., Verhoye, M., and Sijbers, J., Optimal experimental design for Diffusion Kurtosis Imaging, IEEE Transactions on Medical Imaging, vol. 29, pp. 819-829, 2010.PDF icon Download paper (1.12 MB)
J. Gonnissen, De Backer, A., den Dekker, A. J., Martinez, G. T., Rosenauer, A., Sijbers, J., and Van Aert, S., Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images, Applied Physics Letters, vol. 105, no. 063116, 2014.
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)
K. J. Batenburg and Sijbers, J., Optimal Threshold Selection for Tomogram Segmentation by Projection Distance Minimization, IEEE Transactions on Medical Imaging, vol. 28, pp. 676-686, 2009.PDF icon Download full paper (2.51 MB)
H. E. Bortier, Bernat, A., Huysmans, T., Van Glabbeek, F., Sijbers, J., Pinho, R., Gielen, J., and Hubens, G., Osteologic exploration of the clavicle: a new approach, The FASEB Journal, vol. 23, 2009.
B. G. Booth, Keijsers, N. L. W., and Sijbers, J., Outlier detection for foot complaint diagnosis: modeling confounding factors using metric learning, IEEE Intelligent Systems, vol. 36, no. 3, pp. 41-49, 2021.

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