Publications

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2020
M. Roshani, Sattari, M. Amir, Ali, P. Jammal Muh, Roshani, G. Hossein, Corniani, E., and Nazemi, E., “Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter”, Flow Measurement and Instrumentation, vol. 75, 2020.
P. Bladt, den Dekker, A. J., Clement, P., Achten, E., and Sijbers, J., “The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling”, NMR in Biomedicine, vol. 33, no. 12, pp. 1-17, 2020.PDF icon Download paper (16.44 MB)
V. Varkarakis, Bazrafkan, S., and Corcoran, P., “Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets”, Science Direct Elsevier Neural Networks, vol. 121, pp. 101-121, 2020.
B. De Samber, De Rycke, R., De Bruyne, M., Kienhuis, M., Sandblad, L., Bohic, S., Cloetens, P., Urban, C., Polerecky, L., and Vincze, L., “Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS)”, Analytica Chimica Acta, vol. 1106, pp. 22-32, 2020.PDF icon Download paper (4.01 MB)
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)
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)
2019
E. Pechenkova, Nosikova, I., Rumshiskaya, A., Litvinova, L., Rukavishnikov, I., Mershina, E., Sinitsyn, V., Van Ombergen, A., Jeurissen, B., Jillings, S., Laureys, S., Sijbers, J., Grishin, A., Chernikova, L., Naumov, I., Kornilova, L., Wuyts, F. L., Tomilovskaya, E., and Kozlovskaya, I., “Alterations of Functional Brain Connectivity After Long-Duration Spaceflight as Revealed by fMRI.”, Front Physiol, vol. 10, no. 761, pp. 1-23, 2019.
J. Van Houtte, Stanković, K., Booth, B. G., Danckaers, F., Bertrand, V., Verstreken, F., Sijbers, J., and Huysmans, T., “An Articulating Statistical Shape Model of the Human Hand”, in Advances in Human Factors in Simulation and Modeling (AHFE 2018), Cham, 2019, vol. 780, pp. 433–445.
F. Danckaers, Scataglini, S., Haelterman, R., Van Tiggelen, D., Huysmans, T., and Sijbers, J., “Automatic Generation of Statistical Shape Models in Motion”, in Advances in Human Factors in Simulation and Modeling (AHFE 2018), Cham, 2019, vol. 780, pp. 170–178.
H. Verhelst, Giraldo, D., Linden, C. Vander, Vingerhoets, G., Jeurissen, B., and Caeyenberghs, K., “Cognitive Training in Young Patients With Traumatic Brain Injury: A Fixel-Based Analysis.”, Neurorehabil Neural Repair, 2019.
S. Mukunthan, Vleugels, J., Huysmans, T., and De Bruyne, G., “Latent Heat Loss of a Virtual Thermal Manikin for Evaluating the Thermal Performance of Bicycle Helmets”, in Advances in Human Factors in Simulation and Modeling, Cham, 2019, pp. 66–78.
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.
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.
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)
Y. - T. Ling, Cools, S., De Beenhouwer, J., Sijbers, J., and Vandervorst, W., “A Trajectory Based Bottom-Up Volume Reconstruction Method for Atom Probe Tomography”, European Atom Probe Workshop. 2019.
2018
P. Bladt, den Dekker, A. J., Clement, P., Achten, E., and Sijbers, J., “Absolute CBF quantification in multi-time point ASL: the T1 issue”, 10th Annual Meeting of ISMRM Benelux, January 26th 2018, Antwerp, Belgium. 2018.
Q. Collier, Veraart, J., Jeurissen, B., Vanhevel, F., Pullens, P., Parizel, P. M., den Dekker, A. J., and Sijbers, J., “Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach”, Magnetic Resonance in Medicine, vol. 80, no. 2, pp. 802-813, 2018.PDF icon Download paper (1.93 MB)
J. Goyens, Vasilopoulou-Kampitsi, M., Claes, R., Sijbers, J., and Mancini, L., “Enhanced contrast in X-ray microtomographic images of the membranous labyrinth using different X-ray sources and scanning modes”, Journal of Anatomy, vol. 233, p. 770--782, 2018.PDF icon Download paper (1.44 MB)
T. B. A. de Carvalho, Sibaldo, M. A., Tsang, I. J., Cavalcanti, G. D. C., Sijbers, J., and Tsang, I. R., “IntensityPatches and RegionPatches for Image Recognition”, Applied Soft Computing, vol. 62, pp. 176-186, 2018.
T. B. A. de Carvalho, Sibaldo, M. A., Tsang, I. J., Cavalcanti, G. D. C., Sijbers, J., and Tsang, I. R., “IntensityPatches and RegionPatches for Image Recognition”, Applied Soft Computing, vol. 62, pp. 176-186, 2018.
B. Rasti, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., “Noise reduction in hyperspectral imagery: overview and application”, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
Q. Collier, “Robust estimation of diffusion tensor and diffusion kurtosis imaging parameters”, University of Antwerp, Antwerp, 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.
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.
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.

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