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Conference Paper
E. Janssens, De Beenhouwer, J., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Neural Network Based X-Ray Tomography for Fast Inspection of Apples on a Conveyor Belt, in IEEE International Conference on Image Processing, 2015, pp. 917-921.
R. F. Kooy, Reyniers, E., Verhoye, M., Sijbers, J., Oostra, B. A., Willems, P. J., and Van Der Linden, A., Neuroanatomy of the fragile X knockout mouse brain studied using high-resolution MRI, in 48th Annual Meeting of the American Society of Human Genetics, Denver, CO (USA), 1998, p. 1918.
G. Van Gompel, Van Dyck, D., Tisson, G., and Sijbers, J., A new algorithm for Region Of Interest Tomography, in 19th Annual Symposium of the Belgian Hospital Physicists Association, 2004.
G. Van Gompel, Tisson, G., Van Dyck, D., and Sijbers, J., A new algorithm for Region Of Interest Tomography, in SPIE Medical Imaging: Image Processing, San Diego, California, USA, 2004, vol. 127, pp. 2105-2113.PDF icon Download paper (624.91 KB)
J. Rajan, den Dekker, A. J., Juntu, J., and Sijbers, J., A New Nonlocal Maximum Likelihood Estimation Method for Denoising Magnetic Resonance Images, in 5th International Conference, PReMI 2013, Kolkata, India, December 10-14, 2013. Proceedings, 2013, Lecture Notes in Computer Science., vol. 8251.
J. Sijbers, Scheunders, P., Van Dyck, D., and Raman, E., Noise quantification prior to image restoration, in Meeting of the Dutch Society for Pattern Recognition and Image Processing, Best, The Netherlands, 1997.
J. Veraart, Van Hecke, W., Blockx, I., Van Der Linden, A., Verhoye, M., and Sijbers, J., Non-Rigid coregistration of diffusion kurtosis data, in Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on, Rotterdam, the Netherlands, 2010, pp. 392-395.PDF icon Download paper (278.35 KB)
W. Van Hecke, Leemans, A., De Backer, S., Vandervliet, E., Parizel, P. M., Sijbers, J., and D'Agostino, E., Non-rigid coregistration of diffusion tensor images using a viscous fluid model., in 23rd Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine and Biology, Warsaw, Poland, 2006, pp. 191-192.
K. Zarei Zefreh, Welford, F. M., and Sijbers, J., A Novel adaptive PCA Based Denoising Technique for Ultra-High-Rate Computed Tomography, in 7th Conference on Industrial Computed Tomography (iCT 2017), Leuven (Belgium), 2017.
J. Van Audekerke, Sijbers, J., Michiels, I., Verhoye, M., Peeters, R. R., and Van Der Linden, A., Novel design of an RF-antenna with integrated EEG electrodes for combined EEG and fMRI in animals, in 16th annual meeting: Magnetic Resonance Materials in Physics, Biology, and Medicine, Sevilla, Spain, 1999.
M. Verhoye, Van Camp, N., Peeters, R. R., Sijbers, J., Van Audekerke, J., and Van Der Linden, A., On-line simultaneous BOLD/EEG measurements of functional activity during pentylenetetrazol induced epilepsy in the rat, in 16th annual meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB00), Paris, France, 2000.
J. Sijbers, den Dekker, A. J., Verhoye, M., and Van Dyck, D., Optimal estimation of T2 maps from magnitude MR data, in Proceedings of SPIE Medical Imaging, San Diego, CA, USA, 1998, vol. 3338, pp. 384-390.PDF icon Download paper (1.04 MB)
A. Leemans, Sijbers, J., Verhoye, M., and Van Der Linden, A., Optimized Fiber Tractography based on Diffusion Tensor Magnetic Resonance Simulations, in 20th Annual Symposium - Belgian Hospital Physicists Association, Namur, Belgium, 2005.
W. Van Hecke, Leemans, A., Vandervliet, E., Parizel, P. M., and Sijbers, J., An optimized tensor orientation strategy for non-rigid alignment of DT-MRI data, in Joint Annual Meeting ISMRM-ESMRMB, Berlin, 2007.
M. Kudzinava, Poot, D. H. J., Plaisier, A., and Sijbers, J., Optimized Workflow for Diffusion Kurtosis Imaging of Newborns, in ISBI, 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Chicago, USA, 2011, pp. 922-926.PDF icon Paper (286.57 KB)PDF icon Presentation (1.25 MB)
A. J. den Dekker, Sijbers, J., and Van Dyck, D., Optimizing the design of an HREM experiment so as to attain the highest resolution, in Proceedings of FEMMS98: Frontiers of Electron Microscopy in Material Science, Kloster Irsee, Germany, 1998.
D. H. J. Poot, Sijbers, J., and den Dekker, A. J., Optimizing the Diffusion Kurtosis imaging acquisition, in European Society for Magnetic Resonance in Medicine and Biology, Valencia, Spain, 2008.
A. J. den Dekker, Sijbers, J., and Van Dyck, D., Optimizing the setting of an electron microscope for highest resolution using statistical parameter estimation theory, in Workshop: Towards Atomic Resolution Analysis 98, Port Ludlow, WA, U.S.A, 1998.
G. De Groof, Verhoye, M., Leemans, A., Sijbers, J., and Van Der Linden, A., Paired voxel-wise statistical mapping of in vivo Diffusion Tensor Imaging (DTI) data to assess the seasonal neuronal plasticity in the brain of a songbird, in 1st Annual Meeting - European Society of Molecular Imaging, Paris, France, 2006.
G. Ramos-Llordén, Segers, H., Palenstijn, W. J., den Dekker, A. J., and Sijbers, J., Partially discrete magnetic resonance tomography, in 2015 IEEE International Conference on Image Processing (ICIP), 2015, pp. 1653-1657.
T. Roelandts, Batenburg, K. J., and Sijbers, J., PDART: A Partially Discrete Algorithm for the Reconstruction of Dense Particles, in 11th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully 3D), Potsdam, Germany, 2011, pp. 448-451.PDF icon Download full paper (1.74 MB)
N. Six, De Beenhouwer, J., and Sijbers, J., pDART: Discrete algebraic reconstruction using a polychromatic forward model, in The Fifth International Conference on Image Formation in X-Ray Computed Tomography, Salt Lake City, Utah, USA, 2018.PDF icon Download paper (1.61 MB)
S. Manhaeve, Van Nieuwenhove, V., and Sijbers, J., Performance and memory use trade-off in CPU and GPU implementations of a deformation operator for 4D-CT, in 8th Conference on Industrial Computed Tomography, Wels, Austria, 2018.
J. Sijbers and den Dekker, A. J., The performance of generalized likelihood ratio tests for complex functional MRI data in the presence of phase model misspecification, in European Society of Magnetic Resonance in Medicine (ESMRMB), Copenhagen, Denmark, 2004, p. 96.
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.

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