Publications

Export 165 results:
Author [ Type(Desc)] Year
Filters: Author is Arnold Jan den Dekker  [Clear All Filters]
Journal Article
J. Sijbers and den Dekker, A. J., “Generalized likelihood Ratio tests for complex fMRI data: a simulation study”, IEEE Transactions on Medical Imaging, vol. 24, pp. 604-611, 2005.PDF icon Download paper (377.11 KB)
M. Siqueira Pinto, Paolella, R., Billiet, T., Van Dyck, P., Guns, P. - J., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., “Harmonisation of Brain Diffusion MRI: Concepts and Methods”, Frontiers in Neuroscience , vol. 14, pp. 1-17, 2020.PDF icon Download paper (2.61 MB)
A. J. den Dekker, Sijbers, J., and Van Dyck, D., “How to optimize the design of a quantitative HREM experiment so as to attain the highest precision”, Journal of Microscopy, vol. 194, pp. 95-104, 1999.PDF icon Download full paper (601.48 KB)
A. J. den Dekker and Sijbers, J., “Implications of the Rician distribution for fMRI generalized likelihood ratio tests”, Magnetic Resonance Imaging, vol. 23, pp. 953-959, 2005.PDF icon Download paper (1.36 MB)
V. Anania, Collier, Q., Veraart, J., Buikema, A. Eline, Vanhevel, F., Billiet, T., Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model”, NeuroImage, vol. 256, p. 119219, 2022.
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.PDF icon Download paper (final author version) (2.15 MB)
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)
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. 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)
Q. Beirinckx, Bladt, P., van der Plas, M. C. E., van Osch, M. J. P., Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Model-based super-resolution reconstruction for pseudo-continuous Arterial Spin Labeling”, NeuroImage, vol. 286, p. 120506, 2024.PDF icon Download paper (7.23 MB)PDF icon Download supplementary material (20.75 MB)
Q. Beirinckx, Jeurissen, B., Nicastro, M., Poot, D. H. J., Verhoye, M., den Dekker, A. J., and Sijbers, J., “Model-based super-resolution reconstruction with joint motion estimation for improved quantitative MRI parameter mapping”, Computerized Medical Imaging and Graphics, vol. 100, no. 102071, pp. 1-16, 2022.PDF icon Download paper (15.42 MB)PDF icon Download supplementary material (1.35 MB)
E. Bettens, Van Dyck, D., den Dekker, A. J., Sijbers, J., and van den Bos, A., “Model-based two-object resolution from observations having counting statistics”, Ultramicroscopy, vol. 77, pp. 37-48, 1999.PDF icon Download full paper (226 KB)
J. Rajan, den Dekker, A. J., and Sijbers, J., “A new non local maximum likelihood estimation method for Rician noise reduction in Magnetic Resonance images using the Kolmogorov-Smirnov test”, Signal Processing, vol. 103, pp. 16-23, 2014.
P. V. Sudeep, Palanisamy, P., Kesavadas, C., Sijbers, J., den Dekker, A. J., and Rajan, J., “A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps”, Signal Image and Video Processing, vol. 11, no. 5, pp. 913-920, 2017.
G. Ramos-Llordén, Vegas-Sánchez-Ferrero, G., Björk, M., Vanhevel, F., Parizel, P. M., Estépar, R. San José, den Dekker, A. J., and Sijbers, J., “NOVIFAST: A fast algorithm for accurate and precise VFA MRI T1 mapping”, IEEE Transactions on Medical Imaging, vol. 37, no. 11, pp. 2414 - 2427, 2018.PDF icon Download paper (3.3 MB)
J. Morez, Szczepankiewicz, F., den Dekker, A. J., Vanhevel, F., Sijbers, J., and Jeurissen, B., “Optimal experimental design and estimation for q-space trajectory imaging”, Human Brain Mapping, vol. 44, no. 4, pp. 1793-1809, 2023.PDF icon Download paper (5.87 MB)
D. H. J. Poot, den Dekker, A. J., Achten, E., Verhoye, M., and Sijbers, J., “Optimal experimental design for Diffusion Kurtosis Imaging”, IEEE Transactions on Medical Imaging, vol. 29, pp. 819-829, 2010.PDF icon Download paper (1.12 MB)
J. Gonnissen, De Backer, A., den Dekker, A. J., Martinez, G. T., Rosenauer, A., Sijbers, J., and Van Aert, S., “Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images”, Applied Physics Letters, vol. 105, no. 063116, 2014.
J. Sijbers, den Dekker, A. J., Raman, E., and Van Dyck, D., “Parameter estimation from magnitude MR images”, International Journal of Imaging Systems and Technology, vol. 10, pp. 109-114, 1999.PDF icon Download paper (350.44 KB)
T. Elberfeld, De Beenhouwer, J., den Dekker, A. J., Heinzl, C., and Sijbers, J., “Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data - A Simulation Study”, Journal of Nondestructive Evaluation, vol. 37, no. 62, pp. 1573-4862, 2018.
G. Ramos-Llordén, den Dekker, A. J., and Sijbers, J., “Partial Discreteness: a Novel Prior for Magnetic Resonance Image Reconstruction”, IEEE Transactions on Medical Imaging, vol. 36, no. 5, pp. 1041 - 1053, 2017.PDF icon Download paper (3.72 MB)
T. Roelandts, Batenburg, K. J., den Dekker, A. J., and Sijbers, J., “The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography”, Computer Vision and Image Understanding, vol. 126, pp. 28-37, 2014.PDF icon Download paper (4.58 MB)

Pages