Publications

Export 1055 results:
Author [ Type(Desc)] Year
Journal Article
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.
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.
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.
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.
P. Scheunders, Joint quantization and error-diffusion of color images using competitive learning, Journal of the IEE Proceedings, Vision, Image and Signal Processing, vol. 14, pp. 137-140, 1998.
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)
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.
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)
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.
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.
P. Scheunders, Local mapping for multispectral image visualisation, Image and Vision Computing, vol. 19, pp. 971-978, 2001.
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.
B. Koirala, Zahiri, Z., and Scheunders, P., A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements, IEEE Transactions on Geoscience and Remote Sensing, vol. 99, pp. 1-13, 2020.
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)
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.
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)
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.
J. Fatermans, Van Aert, S., and den Dekker, A. J., The maximum a posteriori probability rule for atom column detection from HAADF STEM images, Ultramicroscopy, vol. 201, pp. 81-91, 2019.
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)
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. 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)
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. Gao, Liang, Z., Soper, D. E., Lai, H. - L., Nadolsky, P. M., and Yuan, C. - P., MEKS: A program for computation of inclusive jet cross sections at hadron colliders, Computer Physics Communications, vol. 184, no. 6, pp. 1626 - 1642, 2013.
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.
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.

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