Publications

Export 1013 results:
Author [ Type(Asc)] Year
Journal Article
Sanctorum, J., D. Adriaens, J. J. J. Dirckx, J. Sijbers, C. Van Ginneken, P. Aerts, and S. Van Wassenbergh, "Methods for characterization and optimisation of measuring performance of stereoscopic x-ray systems with image intensifiers", Measurement Science and Technology, vol. 30, issue 10, 2019.
Van den Broek, W., A. Rosenauer, J. Sijbers, D. Van Dyck, and S. Van Aert, "A memory efficient method for fully three-dimensional object reconstruction with HAADF STEM Ultramicroscopy", Ultramicroscopy, vol. 141, pp. 22–31, 2014.
Goris, B., J. De Beenhouwer, A. De Backer, D. Zanaga, K. J. Batenburg, A. Sánchez-Iglesias, L. M. Liz-Marzán, S. Van Aert, S. Bals, J. Sijbers, et al., "Measuring Lattice Strain in Three Dimensions through Electron Microscopy", Nano Letters, vol. 15, issue 10, pp. 6996–7001, 2015.
Sijbers, J., and A J. den Dekker, "Maximum Likelihood estimation of signal amplitude and noise variance from MR data", Magnetic Resonance in Medicine, vol. 51, no. 3, pp. 586-594, 2004. PDF icon Download full paper (295.12 KB)
Sijbers, J., A J. den Dekker, P. Scheunders, and D. Van Dyck, "Maximum Likelihood estimation of Rician distribution parameters", IEEE Transactions on Medical Imaging, vol. 17, no. 3, pp. 357-361, 1998. PDF icon Download paper (106.26 KB)
Rajan, J., B. Jeurissen, M. Verhoye, J. Van Audekerke, and J. Sijbers, "Maximum likelihood estimation based denoising of magnetic resonance images using restricted local neighborhoods", Physics in Medicine and Biology, vol. 56, no. 16, pp. 5221-5234, 2011. PDF icon Download full paper (643.93 KB)
Fatermans, J., S. Van Aert, and A J. den Dekker, "The maximum a posteriori probability rule for atom column detection from HAADF STEM images", Ultramicroscopy, vol. 201, pp. 81-91, 2019.
Keustermans, W., T. Huysmans, B. Schmelzer, J. Sijbers, and J. J. J. Dirckx, "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.
Leemans, A., J. Sijbers, M. Verhoye, A. Van Der Linden, and D. Van Dyck, "Mathematical Framework for Simulating Diffusion Tensor MR Neural Fiber Bundles", Magnetic Resonance in Medicine, vol. 53, pp. 944-953, 2005. PDF icon Download full paper (1.55 MB)
Delgado Y Palacios, R., C. Adriaan, H. Kim, M. Verhoye, D. H. J. Poot, D. Jouke, J. Van Audekerke, H. Benveniste, J. Sijbers, O.. Wiborg, et al., "Magnetic resonance imaging and spectroscopy reveal differential hippocampal changes in anhedonic and resilient subtypes of the chronic mild stress rat model", Biological psychiatry, vol. 70, no. 5, pp. 449-457, 2011.
Juntu, J., J. Sijbers, S. De Backer, J. Rajan, and D. Van Dyck, "A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images", Journal of Magnetic Resonance Imaging, vol. 31, pp. 680–689, 2010. PDF icon Download paper (300.61 KB)
Scheunders, P., "Local mapping for multispectral image visualisation", Image and Vision Computing, vol. 19, no. 13, pp. 971-978, 2001.
Van Nieuwenhove, V., G. Van Eyndhoven, K. J. Batenburg, N. Buls, J. Vandemeulebroucke, J. De Beenhouwer, and J. Sijbers, "Local Attenuation Curve Optimization (LACO) framework for high quality perfusion maps in low-dose cerebral perfusion CT", Medical Physics, vol. 43, issue 12, pp. 6429-6438, 2016.
Emsell, L., A. Leemans, C. Langan, W. Van Hecke, G. J. Barker, P. McCarthy, B. Jeurissen, J. Sijbers, S. Sunaert, D. M. Cannon, et al., "Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion MRI tractography study", Biologicial Psychiatry, vol. 73, issue 2, pp. 194-201, 2013.
Sijbers, J., A J. den Dekker, and R. Bos, "A likelihood ratio test for functional MRI data analysis to account for colored noise", Lecture Notes in Computer Science, vol. 3708, pp. 538-546, September, 2005. PDF icon Download full paper (483.15 KB)
den Dekker, A J., D. H. J. Poot, R. Bos, and J. Sijbers, "Likelihood based hypothesis tests for brain activation detection from MRI data disturbed by colored noise: a simulation study", IEEE Transactions on Medical Imaging, vol. 28, no. 2, pp. 287-296, February, 2009.
Fransen, E., R. Dhooghe, G. Van Camp, M. Verhoye, J. Sijbers, E. Reyniers, P. Soriano, H. Kamiguchi, R. Willemsen, K. E. Koekoek, et al., "L1 knockout mice show dilated ventricles, vermis hypoplasia and impaired exploration patterns", Human Molecular Genetics, vol. 7, no. 6, pp. 999-1009, 1998. PDF icon Download paper (248.02 KB)
Scheunders, P., "Joint quantization and error-diffusion of color images using competitive learning", Journal of the IEE Proceedings, Vision, Image and Signal Processing, vol. 14, no. 2, pp. 137-140, 1998.
Beirinckx, Q., G. Ramos-Llordén, B. Jeurissen, D. H. J. Poot, P. M. Parizel, M. Verhoye, J. Sijbers, and A J. den Dekker, "Joint Maximum Likelihood estimation of motion and T1 parameters from magnetic resonance images in a super-resolution framework: a simulation study", Fundamenta Informaticae, vol. 172, pp. 105–128, 2020.
Collier, Q., J. Veraart, B. Jeurissen, A J. den Dekker, and J. Sijbers, "Iterative Reweighted Linear Least Squares for Accurate, Fast, and Robust Estimation of Diffusion Magnetic Resonance Parameters", Magnetic Resonance in Medicine, vol. 73, issue 6, pp. 2174–2184, 2015.
Van Eyndhoven, G., K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, "An iterative CT reconstruction algorithm for fast fluid flow imaging", IEEE Transactions on Image Processing, vol. 24, issue 11, pp. 4446-4458, 2015.
Van Gompel, G., K. Van Slambrouck, M. Defrise, K. J. Batenburg, J. De Mey, J. Sijbers, and J. Nuyts, "Iterative correction of beam hardening artifacts in CT", Medical Physics, vol. 38, no. 1, pp. 36-49, July, 2011.
Riji, R., J. Rajan, J. Sijbers, and M. S. Nair, "Iterative bilateral filter for Rician noise reduction in MR images", Signal, Image and Video Processing , 2014.
Roine, T., B. Jeurissen, D. Perrone, J. Aelterman, A. Leemans, W. Philips, and J. Sijbers, "Isotropic non-white matter partial volume effects in constrained spherical deconvolution", Information-based methods for neuroimaging: analyzing structure, function and dynamics: Frontiers Media SA, pp. 112, 2015.
Roine, T., B. Jeurissen, D. Perrone, J. Aelterman, A. Leemans, W. Philips, and J. Sijbers, "Isotropic non-white matter partial volume effects in constrained spherical deconvolution", Frontiers in Neuroinformatics, vol. 8, no. 28: Frontiers, pp. 1-9, 03/2014. PDF icon Download paper (1.79 MB)

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