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Conference Paper
J. Sijbers, den Dekker, A. J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Adaptive anisotropic noise filtering for magnitude MR data”, in Proceedings of SPIE Medical Imaging, San Diego, USA, 1999, vol. 3661, pp. 1418-1425.
D. H. J. Poot, Sijbers, J., den Dekker, A. J., and Pintjens, W., “Automatic estimation of the noise variance from the histogram of a magnetic resonance image”, in IEEE/EBMS Benelux Symposium proceedings, 2006, pp. 135-138.
A. J. den Dekker, Sijbers, J., Bos, R., and Smolders, A., “Brain activation detection from functional magnetic resonance imaging data using likelihood based hypothesis tests”, in Abstracts of the 24th Benelux Meeting on Systems and Control, Houffalize, Belgium, 2005.
A. J. den Dekker and Sijbers, J., “Brain activation detection from magnitude fMRI data using a generalized likelihood ratio test”, in Abstracts of the 23rd Benelux Meeting on Systems and Control, Helvoirt, The Netherlands, 2004.
A. Presenti, Sijbers, J., den Dekker, A. J., and De Beenhouwer, J., “CAD-based defect inspection with optimal view angle selection based on polychromatic X-ray projection images”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019, pp. 1-5.PDF icon ict2019_full_paper_55.pdf (216.2 KB)
M. Nicastro, Jeurissen, B., Beirinckx, Q., Smekens, C., Poot, D. H. J., Sijbers, J., and den Dekker, A. J., “Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
J. Sijbers and den Dekker, A. J., “Construction of a likelihood ratio test for magnitude fMRI data”, in 19th Annual Symposium of the Belgian Hospital Physicists Association, 2004.
J. Sijbers, Van Camp, N., Leemans, A., den Dekker, A. J., Verhoye, M., and Van Der Linden, A., “Coregistration of Micro-MRI, microCT and microPET”, in Workshop on non Invasive 3D Microscopy, University of Antwerp, Belgium, 2004, p. 16.
J. Renders, Shafieizargar, B., Verhoye, M., De Beenhouwer, J., den Dekker, A. J., and Sijbers, J., “DELTA-MRI: Direct deformation Estimation from LongiTudinally Acquired k-space data”, in IEEE International Symposium on Biomedical Imaging, 2023, pp. 1-4.
A. J. den Dekker and Sijbers, J., “Detection of brain activation from magnitude fMRI data using a generalized likelihood ratio test”, in Proceedings of the 12th European Signal Processing Conference, Vienna, Austria, 2004, pp. 233-236.
D. Van Dyck, den Dekker, A. J., Sijbers, J., and Bettens, E., “Dose Limited Resolution”, in Proceedings Microscopy and Microanalysis, Atlanta, Georgia, U.S.A, 1998, vol. 2, pp. 802-803.
J. Sijbers, den Dekker, A. J., Van Dyck, D., and Raman, E., “Estimation of signal and noise from Rician distributed data”, in Proceedings of the IASTED International Conference on Signal Processing and Communications, Canary Islands, Spain, 1998, pp. 140-143.
D. H. J. Poot, Sijbers, J., den Dekker, A. J., and Bos, R., “Estimation of the noise variance from the background histogram mode of an MR image”, in Proceedings of the 25th Benelux Meeting on Systems and Control, Heeze, The Netherlands, 2006.
D. H. J. Poot, Sijbers, J., den Dekker, A. J., and Bos, R., “Estimation of the noise variance from the background histogram mode of an MR image”, in Proceedings of SPS-DARTS 2006 (The second annual IEEE BENELUX/DSP Valley Signal Processing Symposium), Antwerp, Belgium, 2006, pp. 159-162.
D. H. J. Poot, Sijbers, J., and den Dekker, A. J., “An exploration of spatial similarities in temporal noise spectra in fMRI measurements”, in Proceedings of SPIE Medical Imaging 2008, San Diego, CA, USA, 2008, vol. 6914, p. 69142.
J. Sijbers and den Dekker, A. J., “Generalized likelihood ratio test for complex fMRI data”, in SPIE Medical Imaging: Physiology, Function, and Structure from Medical Images, San Diego, California, USA, 2004, vol. 5369, pp. 652-663.PDF icon Download full paper (251.15 KB)
G. Van Steenkiste, Poot, D. H. J., Jeurissen, B., den Dekker, A. J., and Sijbers, J., “High resolution T1 estimation from multiple low resolution magnetic resonance images”, in IEEE International Symposium on Biomedical Imaging (ISBI): From nano to macro, 2015, vol. 12, pp. 1036-1039.
A. J. den Dekker, Sijbers, J., and Van Dyck, D., “How to design an HREM experiment so as to attain the highest precision?”, in ICEM14: 14th International Congress on Electron Microscopy, Cancun, Mexico, 1998, vol. 1, pp. 621-622.
J. Sijbers and den Dekker, A. J., “Mapping a polyhedron onto a sphere: application to Fourier descriptors”, in 22nd Benelux Meeting on Systems and Control, Lommel, Belgium, 2003.
A. J. den Dekker and Sijbers, J., “Maximum Likelihood estimation of signal amplitude and noise variance”, in 13th IFAC Symposium on System Identification (SYSID-2003), Rotterdam, The Netherlands, 2003, pp. 126-131.
A. J. den Dekker, Sijbers, J., Verhoye, M., and Van Dyck, D., “Maximum Likelihood estimation of the signal component magnitude in phase contrast MR images”, in Proceedings of SPIE Medical Imaging, San Diego, California, USA, 1998, vol. 3338, pp. 408-415.
B. Shafieizargar, Jeurissen, B., Poot, D. H. J., den Dekker, A. J., and Sijbers, J., “Multi-contrast multi-shot EPI for accelerated diffusion MRI”, in 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2021, pp. 3869-3872.
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)
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, 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)

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