Publications

Export 184 results:
Author [ Type(Desc)] Year
Filters: First Letter Of Last Name is C  [Clear All Filters]
Journal Article
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.
G. Van Eyndhoven, Kurttepeli, M., Van Oers, C. J., Cool, P., Bals, S., Batenburg, K. J., and Sijbers, J., “Pore REconstruction and Segmentation (PORES) method for improved porosity quantification of nanoporous materials”, Ultramicroscopy, vol. 148, pp. 10-19, 2015.
M. Roshani, Phan, G., Faraj, R. Hassan, Phan, N. - H., Roshani, G. Hossein, Corniani, E., and Nazemi, E., “Proposing a gamma radiation based intelligent system for simultaneous analyzing and detecting type and amount of petroleum by-products”, Nuclear Engineering and Technology, 2020.PDF icon 1-s2.0-s1738573320308779-main.pdf (1.38 MB)
E. Ribeiro Sabidussi, Klein, S., Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., “Recurrent Inference Machines as inverse problem solvers for MR relaxometry”, Medical Image Analysis, vol. 74, pp. 1-11, 2021.PDF icon Download paper (2.26 MB)
A. Cuyt, Sijbers, J., Verdonk, B., and Van Dyck, D., “Region and Contour Identification of Physical Objects”, Applied Numerical Analysis Computational Mathematics, vol. 1, pp. 343-352, 2004.
F. Calamante, Jeurissen, B., Smith, R. E., Tournier, J. - D., and Connelly, A., “The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density”, Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2738–2744, 2018.
F. Calamante, Jeurissen, B., Smith, R. E., Tournier, J. - D., and Connelly, A., “The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density”, Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2738–2744, 2018.
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.
N. Chabi, Iuso, D., Beuing, O., Preim, B., and Saalfeld, S., “Self-calibration of C-arm imaging system using interventional instruments during an intracranial biplane angiography.”, Int J Comput Assist Radiol Surg, 2022.
G. Zhang, Scheunders, P., Cerra, D., and Muller, R., “Shadow-aware nonlinear spectral unmixing for hyperspectral imagery”, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 5514-5533, 2022.PDF icon shadow-aware_nonlinear_spectral_unmixing_for_hyperspectral_imagery.pdf (9.51 MB)
G. Zhang, Scheunders, P., and Cerra, D., “Shadow-aware nonlinear spectral unmixing with spatial regularization”, IEEE Transactions on Geoscience and Remote Sensing, vol. 61, p. 5517516, 2023.PDF icon shadow-aware_nonlinear_spectral_unmixing_with_spatial_regularization.pdf (17.62 MB)
G. Liu, Nath, T., Guo, Z., Linneweber, G., Claeys, A., Li, J., Bengochea, M., De Backer, S., Weyn, B., Sneyders, M., Nicasy, H., Yu, P., Scheunders, P., and Hassan, B., “A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila”, Plos Computational Biology, vol. 14, no. 8, p. e1006410, 2018.
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., “The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?”, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
N. J. Forde, O'Donoghue, S., Scanlon, C., Emsell, L., Chaddock, C., Leemans, A., Jeurissen, B., Barker, G. J., Cannon, D. M., Murray, R. M., and others, “Structural brain network analysis in families multiply affected with bipolar I disorder”, Psychiatry Research: Neuroimaging, vol. 234, pp. 44–51, 2015.
N. J. Forde, O'Donoghue, S., Scanlon, C., Emsell, L., Chaddock, C., Leemans, A., Jeurissen, B., Barker, G. J., Cannon, D. M., Murray, R. M., and others, “Structural brain network analysis in families multiply affected with bipolar I disorder”, Psychiatry Research: Neuroimaging, vol. 234, pp. 44–51, 2015.
N. J. Forde, Ronan, L., Suckling, J., Scanlon, C., Neary, S., Holleran, L., Leemans, A., Tait, R., Rua, C., Fletcher, P. C., Jeurissen, B., Dodds, C. M., Miller, S. R., Bullmore, E. T., McDonald, C., Nathan, P. J., and Cannon, D. M., “Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism.”, NeuroImage, vol. 90, pp. 280-9, 2014.
S. Sekar, Jonckers, E., Verhoye, M., Willems, R., Veraart, J., Van Audekerke, J., Couto, J., Giugliano, M., Wuyts, K., Dedeurwaerdere, S., Sijbers, J., Mackie, C., Ver Donck, L., Steckler, T., and Van Der Linden, A., “Subchronic memantine induced concurrent functional disconnectivity and altered ultra-structural tissue integrity in the rodent brain: revealed by multimodal MRI.”, Psychopharmacology, vol. 227, no. 3, pp. 479-91, 2013.
L. Serbruyns, Leunissen, I., Huysmans, T., Cuypers, K., Meesen, R. L., van Ruitenbeek, P., Sijbers, J., and Swinnen, S. P., “Subcortical volumetric changes across the adult lifespan: subregional thalamic atrophy accounts for age-related sensorimotor performance declines”, Cortex, vol. 65, pp. 128-138, 2015.PDF icon paper (1.35 MB)
B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., “A supervised method for nonlinear hyperspectral unmixing”, Remote Sensing, vol. 11, no. 20 , 2019.PDF icon remotesensing-11-02458-v3.pdf (3.23 MB)
P. Bladt, van Osch, M. J. P., Clement, P., Achten, E., Sijbers, J., and den Dekker, A. J., “Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling”, Magnetic Resonance in Medicine, vol. 84, no. 5, pp. 2523-2536, 2020.PDF icon Download paper (1.3 MB)
F. De Carlo, Gursoy, D., Ching, D., Batenburg, K. J., Ludwig, W., Mancini, L., Welford, F. M., Mokso, R., Pelt, D., Sijbers, J., and Rivers, M., “TomoBank: A Tomographic Data Repository for Computational X-ray Science”, Measurement Science and Technology, vol. 29, no. 3, pp. 1-10, 2018.PDF icon Download paper (5.71 MB)
W. S. Oliveira, Teixeira, J. V., Tsang, I. R., Cavalcanti, G. D. C., and Sijbers, J., “Unsupervised Retinal Vessel Segmentation Using Combined Filters”, Plos One, vol. 11, pp. 1-21, 2016.
M. Siqueira Pinto, Winzeck, S., Kornaropoulos, E. N., Richter, S., Paolella, R., Correia, M. M., Glocker, B., Williams, G., Vik, A., Posti, J., Håberg, A. Kristine, Stenberg, J., Guns, P. - J., den Dekker, A. J., Menon, D. K., Sijbers, J., Van Dyck, P., and Newcombe, V. F. J., “Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study”, Journal of Neurotrauma, vol. 40, no. 13-14, pp. 1317-1338, 2023.
C. C. Hung, Scheunders, P., Pham, M., Su, M. C., and Coleman, T., “Using Intelligent Optimization Techniques in the K-means Algorithm for Multispectral Image Classification”, International Journal of Fuzzy Systems, vol. 6, pp. 107-117, 2004.
K. Hufkens, Scheunders, P., and Ceulemans, R., “Validation of the sigmoid wave curve fitting algorithm on a forest-tundra ecotone in the Northwest Territories, Canada”, Ecological Informatics, vol. 4, pp. 1-7, 2009.

Pages