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2019
E. Ribeiro Sabidussi, Nicastro, M., Bazrafkan, S., Beirinckx, Q., Jeurissen, B., Sijbers, J., den Dekker, A. J., Klein, S., and Poot, D. H. J., “A deep learning approach to T1 mapping in quantitative MRI”, 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology (ESMRMB), Rotterdam, The Netherlands, vol. 32 (Suppl. 1). Magn Reson Mater Phy, 2019.
J. Rimpelainen, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., “Deep learning based missing wedge artefact removal for electron tomography”, Microscopy Conference, Berlin, Germany. pp. 660-661, 2019.
S. Scataglini, Danckaers, F., Huysmans, T., Sijbers, J., and Andreoni, G., “Design smart clothing using digital human models”, in DHM and Posturography, Academic Press, 2019, pp. 683-698.
F. Danckaers, “The Development of 3D Statistical Shape Models for Diverse Applications”, 2019.
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., “Diffusion MRI fiber tractography of the brain”, NMR in Biomedicine, 2019.
A. E. Buikema, den Dekker, A. J., and Sijbers, J., “Diffusion time dependence in the mid-time regime: a simulation study using PGSE.”, 27th Annual Meeting of the ISMRM. Montreal, Canada, 2019.
A. Presenti, Sijbers, J., and De Beenhouwer, J., “Dynamic angle selection for few-view X-ray inspection of CAD based objects”, in Proc. SPIE, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2019, vol. 11072.
A. E. Buikema, den Dekker, A. J., and Sijbers, J., “Effect of diffusion time dependence on parameter estimation in the clinical time frame: a simulation study using PGSE”, 11th Annual Meeting of the ISMRM Benelux Chapter. Leiden, the Netherlands, 2019.
E. Janssens, Sijbers, J., Dierick, M., and De Beenhouwer, J., “Fast detection of cracks in ultrasonically welded parts by inline X-ray inspection”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.
E. Janssens, Sijbers, J., Dierick, M., and De Beenhouwer, J., “Fast detection of cracks in ultrasonically welded parts by inline X-ray inspection”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.
T. Elberfeld, De Beenhouwer, J., and Sijbers, J., “Fiber assignment by continuous tracking for parametric fiber reinforced polymer reconstruction”, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2019, vol. 11072.PDF icon Download paper (5.15 MB)
J. Weissenböck, Fröhler, B., Gröller, E., Sanctorum, J., De Beenhouwer, J., Sijbers, J., Karunakaran, S. Ayalur, Hoeller, H., Kastner, J., and Heinzl, C., “An Interactive Visual Comparison Tool for 3D Volume Datasets represented by Nonlinearly Scaled 1D Line Plots through Space-filling Curves”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.22 MB)
B. Auer, Zeraatkar, N., De Beenhouwer, J., Kalluri, K., Kuo, P. H., Furenlid, L. R., and King, M. A., “Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging”, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, vol. 11072, pp. 187 – 190.
B. Auer, Kalluri, K., De Beenhouwer, J., Zeraatkar, N., Könik, A., Kuo, P. H., Furenlid, L. R., and King, M. A., “Investigation of keel versus knife edge pinhole profiles for a next-generation SPECT system dedicated to clinical brain imaging”, 2nd International Conference on Monte Carlo Techniques for Medical Applications. 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.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Aerts, P., Dirckx, J. J. J., and Sijbers, J., “A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.93 MB)
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Aerts, P., Dirckx, J. J. J., and Sijbers, J., “A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.93 MB)
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., “Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling”, Computers in Biology and Medicine, vol. 105, pp. 27-38, 2019.
J. Fatermans, Van Aert, S., and den Dekker, A. J., “The maximum a posteriori probability rule for atom column detection from HAADF STEM images”, Ultramicroscopy, vol. 201, pp. 81-91, 2019.
J. Sanctorum, Adriaens, D., Dirckx, J. J. J., Sijbers, J., Van Ginneken, C., Aerts, P., and Van Wassenbergh, S., “Methods for characterization and optimisation of measuring performance of stereoscopic x-ray systems with image intensifiers”, Measurement Science and Technology, vol. 30, no. 10, 2019.
T. Elberfeld, Bazrafkan, S., De Beenhouwer, J., and Sijbers, J., “Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images”, 4th International Conference on Tomography of Materials & Structures. 2019.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., and Sijbers, J., “Moving Statistical Body Shape Models Using Blender”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 28–38.
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.
T. Huysmans, Danckaers, F., Vleugels, J., Lacko, D., De Bruyne, G., Verwulgen, S., and Sijbers, J., “Multi-patch B-Spline Statistical Shape Models for CAD-Compatible Digital Human Modeling”, in Advances in Human Factors in Simulation and Modeling, Cham, 2019, pp. 179–189.
T. Huysmans, Danckaers, F., Vleugels, J., Lacko, D., De Bruyne, G., Verwulgen, S., and Sijbers, J., “Multi-patch B-Spline Statistical Shape Models for CAD-Compatible Digital Human Modeling”, in Advances in Human Factors in Simulation and Modeling, Cham, 2019, pp. 179–189.

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