Publications

Export 147 results:
Author [ Type(Desc)] Year
Filters: First Letter Of Last Name is N  [Clear All Filters]
Journal Article
J. Renders, Jeurissen, B., Nguyen, A. - T., De Beenhouwer, J., and Sijbers, J., “ImWIP: open-source image warping toolbox with adjoints and derivatives”, SoftwareX, vol. 24, p. 101524, 2023.PDF icon Download paper (1 MB)
U. Roine, Roine, T., Salmi, J., Nieminen-von Wendt, T., Leppämäki, S., Rintahaka, P., Tani, P., Leemans, A., and Sams, M., “Increased coherence of white matter fiber tract organization in adults with Asperger syndrome: A diffusion tensor imaging study”, Autism Research, vol. 6, no. 6, pp. 642-650, 2013.PDF icon Download paper (1.2 MB)
L. F. Alves Pereira, Janssens, E., Cavalcanti, G. D. C., Tsang, I. R., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., “Inline Discrete Tomography system: application to agricultural product inspection”, Computers and Electronics in Agriculture, vol. 138, pp. 117–126, 2017.
T. De Schryver, Dhaene, J., Dierick, M., Boone, M. N., Janssens, E., Sijbers, J., Van Dael, M., Verboven, P., Nicolai, B., and Van Hoorebeke, L., “In-line NDT with X-Ray CT combining sample rotation and translation”, NDT & E International, vol. 89, pp. 89–98, 2016.
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.
D. Giraldo, Smith, R. E., Struyfs, H., Niemantsverdriet, E., De Roeck, E., Bjerke, M., Engelborghs, S., Romero, E., Sijbers, J., and Jeurissen, B., “Investigating tissue-specific abnormalities in Alzheimer’s disease with multi-shell diffusion MRI”, Journal of Alzheimer's Disease, vol. 90, no. 4, pp. 1771-1791, 2022.
R. Riji, Rajan, J., Sijbers, J., and Nair, M. S., “Iterative bilateral filter for Rician noise reduction in MR images”, Signal, Image and Video Processing , 2014.
G. Van Gompel, Van Slambrouck, K., Defrise, M., Batenburg, K. J., De Mey, J., Sijbers, J., and Nuyts, J., “Iterative correction of beam hardening artifacts in CT”, Medical Physics, vol. 38, pp. 36-49, 2011.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., “A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system”, Nondestructive Testing and Evaluation , vol. 35, no. 3, pp. 252-265, 2020.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I. B., Manko, O., Danilichev, S., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., Eulenburg, Pzu, Sijbers, J., Wuyts, F. L., and Jeurissen, B., “Macro- and microstructural changes in cosmonauts’ brains after long-duration spaceflight”, Science Advances, vol. 6, no. 36, p. eaaz9488, 2020.PDF icon Download paper (942.53 KB)
J. Gao, Liang, Z., Soper, D. E., Lai, H. - L., Nadolsky, P. M., and Yuan, C. - P., “MEKS: A program for computation of inclusive jet cross sections at hadron colliders”, Computer Physics Communications, vol. 184, no. 6, pp. 1626 - 1642, 2013.
P. Kempeneers, Zarco-Tejada, P. J., North, P. R. J., De Backer, S., Delalieux, S., Sepulcre-Canto, G., Morales, F., van Aardt, J., Sagardoy, R., Coppin, P., and Scheunders, P., “Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery”, International Journal of Remote Sensing, vol. 29, pp. 5093-5111, 2008.
Q. Beirinckx, Jeurissen, B., Nicastro, M., Poot, D. H. J., Verhoye, M., den Dekker, A. J., and Sijbers, J., “Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping”, Computerized Medical Imaging and Graphics, vol. 100, no. 102071, pp. 1-16, 2022.PDF icon Download paper (15.42 MB)PDF icon Download supplementary material (1.35 MB)
E. Nazemi, Six, N., Iuso, D., De Samber, B., Sijbers, J., and De Beenhouwer, J., “Monte-Carlo-Based Estimation of the X-ray Energy Spectrum for CT Artifact Reduction”, Applied Sciences, vol. 11, no. 7, 2021.PDF icon Download paper (4.96 MB)
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.
S. De Backer, Cornelissen, F., Lemeire, J., Nuydens, R., Meert, T., Schelkens, P., and Scheunders, P., “Mosiacing of Fibered Fluorescence Microscopy Video”, Lecture notes in Computer Science, vol. 5259, pp. 915-923, 2008.
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. 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)
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.
S. De Backer, Naud, A., and Scheunders, P., “Non-linear Dimensionality Reduction Techniques for Unsupervised Feature Extraction”, Pattern Recognition Letters, vol. 19, pp. 711-720, 1998.
P. Scheunders, De Backer, S., and Naud, A., “Non-linear mapping for feature extraction”, Lecture Notes in Computer Science, vol. 1451, pp. 823-830, 1998.
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.
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. Kenney, McInerney, S., McPhilemy, G., Najt, P., Scanlon, C., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Donohoe, G., Hallahan, B., McDonald, C., and Cannon, D., “P. 3.033 Lateralisation of the arcuate fasciculus in psychosis & the role in verbal learning & auditory verbal hallucinations”, European Neuropsychopharmacology, vol. 26, no. 1, pp. S76–S77, 2016.

Pages