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K. Zarei Zefreh, Welford, F. M., and Sijbers, J., Investigation on the effect of exposure time on scintillator afterglow for ultra-fast tomography acquisition, in 18th International Workshop on Radiation Imaging Detectors, Barcelona, Spain, 2016, vol. 11, p. C12014.PDF icon Download paper (482.36 KB)
V. Van Nieuwenhove, Van Eyndhoven, G., Batenburg, K. J., Buls, N., Vandemeulebroucke, J., De Beenhouwer, J., and Sijbers, J., Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT, Medical Physics, vol. 43, no. 12, pp. 6429-6438, 2016.
J. Cant and Sijbers, J., Method and system for correcting geometric misalignment during image reconstruction in chest tomosynthesis, U.S. Patent EP16173767.12016.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Sijbers, J., and Leemans, A., Methodological Considerations on Graph Theoretical Analysis of Structural Brain Networks, Proc. Intl. Soc. Mag. Reson. Med. 24. p. 3437, 2016.
P. Bladt, Van Steenkiste, G., Ramos-Llordén, G., den Dekker, A. J., and Sijbers, J., Multi-voxel algorithm for quantitative bi-exponential MRI T1 estimation, in SPIE Medical Imaging, San Diego, California, United States of America, 2016, vol. 9784, p. 978402.PDF icon Download paper (624.23 KB)
G. Ramos-Llordén, den Dekker, A. J., Björk, M., Verhoye, M., and Sijbers, J., NOVIFAST: A fast non-linear least squares method for accurate and precise estimation of T1 from SPGR signals, 24th Annual Meeting of the ISMRM, Singapore. 2016.
T. Huysmans, Sijbers, J., and Verstreken, F., Orthosis, U.S. Patent WO/2016/1812822016.
T. B. A. de Carvalho, Sibaldo, M. A. A., Tsang, I. R., Cavalcanti, G. D. C., Tsang, I. J., and Sijbers, J., Pixel clustering for face recognition, in 5th Brazilian Conference on Intelligent Systems, Brazil, 2016, pp. 121-126.
A. Dabravolski, De Beenhouwer, J., and Sijbers, J., Projection-based polygon estimation in X-ray computed tomography, in 6th International Conference on Optical Measurement Techniques for Structures and Systems (OPTIMESS), 2016, pp. 41-50.PDF icon Download paper (615.72 KB)
D. Zanaga, Bleichrodt, F., Altantzis, T., Winckelmans, N., Palenstijn, W. J., Sijbers, J., de Nijs, B., van Huis, M. A., Sánchez-Iglesias, A., Liz-Marzán, L. M., van Blaaderen, A., Batenburg, K. J., Bals, S., and Van Tendeloo, G., Quantitative 3D analysis of huge nanoparticle assemblies., Nanoscale, vol. 8, no. 1, pp. 292-9, 2016.
Q. Collier, den Dekker, A. J., Jeurissen, B., and Sijbers, J., Robust DKI parameter estimation in case of CSF partial volume effects, ISMRM 24th annual meeting, Singapore. 2016.
Q. Collier, den Dekker, A. J., Jeurissen, B., and Sijbers, J., Robust DKI Parameter Estimation in Case of CSF Partial Volume Effects, Proc. Intl. Soc. Mag. Reson. Med. 24. p. 1044, 2016.
Q. Collier, den Dekker, A. J., Jeurissen, B., and Sijbers, J., A robust framework for combined estimation of DKI and CSF partial volume fraction parameters, 8th annual meeting of the ISMRM Benelux chapter, Eindhoven, Netherlands. 2016.
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.
A. De Backer, van den Bos, K. H. W., Van den Broek, W., Sijbers, J., and Van Aert, S., StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images, Ultramicroscopy, vol. 171, pp. 104–116, 2016.
G. Van Steenkiste, Super-resolution estimation of quantitative MRI parameters, University of Antwerp, 2016.PDF icon Download PhD thesis (7.56 MB)
G. Van Steenkiste, Jeurissen, B., Veraart, J., den Dekker, A. J., Parizel, P. M., Poot, D. H. J., and Sijbers, J., Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations, Magnetic Resonance in Medicine, vol. 75, no. 1, pp. 181-195, 2016.
Z. Wang, Rogge, S., Van Dael, M., Van Nieuwenhove, V., Verboven, P., Sijbers, J., and Nicolai, B., Understanding microstructural deformation of apple tissue from 4D micro-CT imaging, ISHS Symposium 2016: Sensing Plant Water Status - Methods and Applications in Horticultural Science. Potsdam, Germany, 5-7 October. 2016.
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.
G. Van Eyndhoven, Batenburg, K. J., Kazantsev, D., Van Nieuwenhove, V., Lee, P. D., Dobson, K. J., and Sijbers, J., A 4D CT reconstruction algorithm for fast liquid flow imaging, Applied Inverse Problems Conference, Helsinki. 2015.
V. Van Nieuwenhove, De Beenhouwer, J., De Schryver, T., Van Hoorebeke, L., and Sijbers, J., Affine deformation correction in cone beam Computed Tomography, in Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Newport, Rhode Island, USA, 2015, pp. 182-185.PDF icon Download paper (2.91 MB)
B. Jeurissen, Sijbers, J., and Tournier, J. - D., Assessing inter-subject variability of white matter response functions used for constrained spherical deconvolution, ISMRM 23th Annual Meeting, Toronto, Ontario, Canada, vol. 23. p. 2834, 2015.PDF icon Download abstract (780.16 KB)
W. Van Aarle, Palenstijn, W. J., De Beenhouwer, J., Altantzis, T., Bals, S., Batenburg, K. J., and Sijbers, J., The ASTRA Toolbox: a platform for advanced algorithm development in electron tomography, Ultramicroscopy, vol. 157, pp. 35–47, 2015.PDF icon Download paper (3.47 MB)
F. Danckaers, Huysmans, T., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Building a Statistical Shape Model of the Apple from Corresponded Surfaces, Chemical Engineering Transactions, vol. 44, pp. 49-54, 2015.PDF icon Download paper (696.94 KB)
G. Van Steenkiste, Hamaide, J., Jeurissen, B., Poot, D. H. J., Van Audekerke, J., Sijbers, J., and Verhoye, M., Combination of super-resolution reconstruction diffusion tensor imaging and track density imaging reveals song control system connectivity in zebra finches, Proc. Intl. Soc. Mag. Reson. Med. 23. p. 2861, 2015.