Publications

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I. Blockx, De Groof, G., Verhoye, M., Van Audekerke, J., Raber, K., Poot, D. H. J., Sijbers, J., Osmand, A. P., Von Hörsten, S., and Van Der Linden, A., Microstructural changes observed with DKI in a transgenic Huntington rat model: Evidence for abnormal neurodevelopment., NeuroImage, vol. 59, pp. 957-67, 2012.
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.
W. Van den Broek, Rosenauer, A., Sijbers, J., Van Dyck, D., and Van Aert, S., A memory efficient method for fully three-dimensional object reconstruction with HAADF STEM Ultramicroscopy, Ultramicroscopy, vol. 141, pp. 22–31, 2014.
B. Goris, De Beenhouwer, J., De Backer, A., Zanaga, D., Batenburg, K. J., Sánchez-Iglesias, A., Liz-Marzán, L. M., Van Aert, S., Bals, S., Sijbers, J., and Van Tendeloo, G., Measuring Lattice Strain in Three Dimensions through Electron Microscopy, Nano Letters, vol. 15, no. 10, pp. 6996–7001, 2015.
J. Sijbers and den Dekker, A. J., Maximum Likelihood estimation of signal amplitude and noise variance from MR data, Magnetic Resonance in Medicine, vol. 51, pp. 586-594, 2004.PDF icon Download full paper (295.12 KB)
J. Sijbers, den Dekker, A. J., Scheunders, P., and Van Dyck, D., Maximum Likelihood estimation of Rician distribution parameters, IEEE Transactions on Medical Imaging, vol. 17, pp. 357-361, 1998.PDF icon Download paper (106.26 KB)
J. Rajan, Jeurissen, B., Verhoye, M., Van Audekerke, J., and Sijbers, J., Maximum likelihood estimation based denoising of magnetic resonance images using restricted local neighborhoods, Physics in Medicine and Biology, vol. 56, pp. 5221-5234, 2011.PDF icon Download full paper (643.93 KB)
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.
A. Leemans, Sijbers, J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., 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)
R. Delgado Y Palacios, Adriaan, C., Kim, H., Verhoye, M., Poot, D. H. J., Jouke, D., Van Audekerke, J., Benveniste, H., Sijbers, J., Wiborg, O., and Van Der Linden, A., 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, pp. 449-457, 2011.
J. Juntu, Sijbers, J., De Backer, S., Rajan, J., and Van Dyck, D., 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)
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Bazrafkan, S., Dirckx, J. J. J., and Sijbers, J., A low-cost geometry calibration procedure for a modular cone-beam X-ray CT system, Nondestructive Testing and Evaluation , In Press.
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.
L. Emsell, Leemans, A., Langan, C., Van Hecke, W., Barker, G. J., McCarthy, P., Jeurissen, B., Sijbers, J., Sunaert, S., Cannon, D. M., and McDonald, C., Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion MRI tractography study, Biologicial Psychiatry, vol. 73, no. 2, pp. 194-201, 2013.
J. Sijbers, den Dekker, A. J., and Bos, R., A likelihood ratio test for functional MRI data analysis to account for colored noise, Lecture Notes in Computer Science, vol. 3708, pp. 538-546, 2005.PDF icon Download full paper (483.15 KB)
A. J. den Dekker, Poot, D. H. J., Bos, R., and Sijbers, J., 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, pp. 287-296, 2009.
E. Fransen, Dhooghe, R., Van Camp, G., Verhoye, M., Sijbers, J., Reyniers, E., Soriano, P., Kamiguchi, H., Willemsen, R., Koekoek, K. E., Zeeuw, D. C. I., De Deyn, P. P., Van Der Linden, A., Lemmon, V., Kooy, R. F., and Willems, P. J., L1 knockout mice show dilated ventricles, vermis hypoplasia and impaired exploration patterns, Human Molecular Genetics, vol. 7, pp. 999-1009, 1998.PDF icon Download paper (248.02 KB)
Q. Beirinckx, Ramos-Llordén, G., Jeurissen, B., Poot, D. H. J., Parizel, P. M., Verhoye, M., Sijbers, J., and den Dekker, A. J., 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.
Q. Collier, Veraart, J., Jeurissen, B., den Dekker, A. J., and Sijbers, J., Iterative Reweighted Linear Least Squares for Accurate, Fast, and Robust Estimation of Diffusion Magnetic Resonance Parameters, Magnetic Resonance in Medicine, vol. 73, no. 6, pp. 2174–2184, 2015.
G. Van Eyndhoven, Batenburg, K. J., Kazantsev, D., Van Nieuwenhove, V., Lee, P. D., Dobson, K. J., and Sijbers, J., An iterative CT reconstruction algorithm for fast fluid flow imaging, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4446-4458, 2015.
G. Van Gompel, Van Slambrouck, K., Defrise, M., Batenburg, K. J., De Mey, J., Sijbers, J., and Nuyts, J., Iterative correction of beam hardening artifacts in CT, Medical Physics, vol. 38, pp. 36-49, 2011.
R. Riji, Rajan, J., Sijbers, J., and Nair, M. S., Iterative bilateral filter for Rician noise reduction in MR images, Signal, Image and Video Processing , 2014.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., Isotropic non-white matter partial volume effects in constrained spherical deconvolution, Frontiers in Neuroinformatics, vol. 8, pp. 1-9, 2014.PDF icon Download paper (1.79 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., Isotropic non-white matter partial volume effects in constrained spherical deconvolution, Information-based methods for neuroimaging: analyzing structure, function and dynamics, p. 112, 2015.
K. Zarei Zefreh, Investigation on the effect of exposure time on scintillator afterglow for ultra-fast tomography acquisition, Journal of Instrumentation, vol. 11, 2016.

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