Publications

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Conference Paper
Sijbers, J., A J. den Dekker, P. Scheunders, E. Raman, and D. Van Dyck, "Unbiased signal estimation in magnitude MR images", Proceedings of the European Society for Magnetic Resonance in Medicine and Biology, vol. 2, no. 2, Brussels, Belgium, pp. 174, September, 1997.
Journal Article
Sijbers, J., A J. den Dekker, M. Verhoye, A. Van Der Linden, and D. Van Dyck, "Adaptive anisotropic noise filtering for magnitude MR data", Magnetic Resonance Imaging, vol. 17, no. 10, pp. 1533-1539, 1999. PDF icon Download full paper (366 KB)
Van Aert, S., A. De Backer, G. T. Martinez, A J. den Dekker, D. Van Dyck, S. Bals, and G. Van Tendeloo, "Advanced electron crystallography through model-based imaging", IUCrJ, vol. 3, no. 1, Jan, 2016.
Gonnissen, J., A. De Backer, A J. den Dekker, J. Sijbers, and S. Van Aert, "Atom-counting in High Resolution Electron Microscopy: TEM or STEM - that’s the question", Ultramicroscopy, vol. 147, pp. 112–120, 2017.
Sijbers, J., D. H. J. Poot, A J. den Dekker, and W. Pintjens, "Automatic estimation of the noise variance from the histogram of a magnetic resonance image", Physics in Medicine and Biology, vol. 52, no. 5, pp. 1335-1348, February, 2007. PDF icon Download paper (297.18 KB)
Bladt, P., A J. den Dekker, P. Clement, E. Achten, and J. Sijbers, "The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling", NMR in Biomedicine, In Press.
den Dekker, A J., and J. Sijbers, "Data distributions in magnetic resonance images: a review", Physica Medica, vol. 30, issue 7, pp. 725–741, 2014. PDF icon Download paper (410.33 KB)PDF icon Download paper (protected) (505.58 KB)
Gonnissen, J., A. De Backer, A J. den Dekker, J. Sijbers, and S. Van Aert, "Detecting and locating light atoms from high-resolution STEM images: the quest for a single optimal design Ultramicroscopy", Ultramicroscopy, vol. 170, pp. 128-138, 2016.
Collier, Q., J. Veraart, B. Jeurissen, F. Vanhevel, P. Pullens, P. M. Parizel, A J. den Dekker, and J. Sijbers, "Diffusion kurtosis imaging with free water elimination: a Bayesian estimation approach", Magnetic Resonance in Medicine, vol. 80, issue 2, pp. 802-813, 2018. PDF icon Download paper (1.93 MB)
Sijbers, J., A J. den Dekker, J. Van Audekerke, M. Verhoye, and D. Van Dyck, "Estimation of the noise in magnitude MR images", Magnetic Resonance Imaging, vol. 16, no. 1, pp. 87-90, 1998. PDF icon Download paper (64.9 KB)
den Dekker, A J., J. Gonnissen, A. De Backer, J. Sijbers, and S. Van Aert, "Estimation of unknown structure parameters from high-resolution (S)TEM images: what are the limits?", Ultramicroscopy, vol. 134, pp. 34-43, 2013.
Van Dyck, D., E. Bettens, J. Sijbers, M. Op de Beeck, A J. den Dekker, and A. van den Bos, "From High Resolution Image to Atomic Structure: how fare are we?", Scanning Microscopy, Special Issue on Image Processing, vol. 11, pp. 467-478, 1997. PDF icon Download full paper (3.45 MB)
Sijbers, J., and A J. den Dekker, "Generalized likelihood Ratio tests for complex fMRI data: a simulation study", IEEE Transactions on Medical Imaging, vol. 24, no. 5, pp. 604-611, May, 2005. PDF icon Download paper (377.11 KB)
den Dekker, A J., J. Sijbers, and D. Van Dyck, "How to optimize the design of a quantitative HREM experiment so as to attain the highest precision", Journal of Microscopy, vol. 194, no. 1, pp. 95-104, 1999. PDF icon Download full paper (601.48 KB)
den Dekker, A J., and J. Sijbers, "Implications of the Rician distribution for fMRI generalized likelihood ratio tests", Magnetic Resonance Imaging, vol. 23, no. 9, pp. 953-959, 2005. PDF icon Download paper (1.36 MB)
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.
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.
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.
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)
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.
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)
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)
Bettens, E., D. Van Dyck, A J. den Dekker, J. Sijbers, and A. van den Bos, "Model-based two-object resolution from observations having counting statistics", Ultramicroscopy, vol. 77, no. 1, pp. 37-48, 1999. PDF icon Download full paper (226 KB)
Rajan, J., A J. den Dekker, and J. Sijbers, "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.
Sudeep, P. V., P. Palanisamy, C. Kesavadas, J. Sijbers, A J. den Dekker, and J. Rajan, "A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps", Signal Image and Video Processing, vol. 11, issue 5, pp. 913-920, 2017.

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