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D
den Dekker, A J., and J. Sijbers, "Detection of brain activation from magnitude fMRI data using a generalized likelihood ratio test", Proceedings of the 12th European Signal Processing Conference, Vienna, Austria, ISBN 3-200-00165-8, pp. 233-236, September, 2004.
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., 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.
den Dekker, A J., and J. Sijbers, "Brain activation detection from magnitude fMRI data using a generalized likelihood ratio test", Abstracts of the 23rd Benelux Meeting on Systems and Control, Helvoirt, The Netherlands, March, 2004.
den Dekker, A J., J. Sijbers, M. Verhoye, and D. Van Dyck, "Maximum Likelihood estimation of the signal component magnitude in phase contrast MR images", Proceedings of SPIE Medical Imaging, vol. 3338, San Diego, California, USA, pp. 408-415, February, 1998.
Dhollander, T., R E. Smith, J-D. Tournier, B. Jeurissen, and A. Connelly, "Time to Move On: An FOD-Based DEC Map to Replace DTI's Trademark DEC FA", ISMRM 23th Annual Meeting, pp. 1027, 2015.
Dhollander, T., J. Veraart, W. Van Hecke, F. Maes, S. Sunaert, J. Sijbers, and P. Suetens, "Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space", MICCAI 2011: Medical Image Computing and Computer-Assisted Intervention, pp. 166-173, 2011.
Distante, C., J. Blanc-Talon, W. Philips, D. Popescu, and P. Scheunders, "ACIVS 2016, Advanced Concepts for Intelligent Vision Systems", Lecture Notes in Computer Science, vol. 10016, 2016.
Dox, T., R. Heylen, and P. Scheunders, "Spectral variability in a multilinear mixing model", IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.
Driesen, J., and P. Scheunders, "A Multicomponent Image Segmentation Framework", Lecture Notes in Computer Science, vol. 5259, pp. 589-600, 2008.
Driesen, J., and P. Scheunders, "Wavelet based segmentation of multivalued images", SPIE Optics East, 23-26 October, Boston, Massachusetts USA, vol. 6001, no. 2, pp. 13-22, 2005.
Driesen, J., and P. Scheunders, "Wavelet based Filter Array Demosaicking", Proc. ICIP2004, IEEE International Conference on Image Processing, 24-27 october, Singapore, pp. 3311-3314, 2004.
Driesen, J., and P. Scheunders, "Wavelet based segmentation of multi-component images", IEEE BENELUX/DSP Valley Signal Processing Symposium (SPS-DARTS) March 28-29, Antwerp, Belgium, pp. 151-154, 2006.
Driesen, J., G. Thoonen, and P. Scheunders, "Spatial hyperspectral image classification by prior segmentation", Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009, vol. 3, Cape Town, South Africa, pp. III-709 - III-712, July, 2009.
Duijster, A., P. Scheunders, and S. De Backer, "Wavelet-Based EM Algorithm for Multispectral-Image Restoration", IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 11, pp. 3892-3898, November, 2009.
Duijster, A., S. De Backer, and P. Scheunders, "Wavelet-based Multispectral Image Restoration", IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, vol. 3: IEEE International, pp. 79-82, 2008.
Duijster, A., S. De Backer, and P. Scheunders, "Wavelet-based Multicomponent Image Restoration", Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, United States, September 9-12, vol. 6763, October, 2007.
Duijster, A., S. De Backer, and P. Scheunders, "Multicomponent image restoration, an experimental study", Lecture Notes in Computer Science, vol. 4633, pp. 58-68, 2007.
E
Elberfeld, T., J. De Beenhouwer, A J. den Dekker, C. Heinzl, and J. Sijbers, "Parametric Reconstruction of Advanced Glass Fiber-reinforced Polymer Composites from X-ray Images", 8th Conference on Industrial Computed Tomography, Wels, Austria, 2018. PDF icon Download paper (636.09 KB)
Elberfeld, T., J. De Beenhouwer, A J. den Dekker, C. Heinzl, and J. Sijbers, "Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data - A Simulation Study", Journal of Nondestructive Evaluation, vol. 37, issue 62, pp. 1573-4862, Jul, 2018.
Elberfeld, T., S. Bazrafkan, J. De Beenhouwer, and J. Sijbers, "Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images", 4th International Conference on Tomography of Materials & Structures, 07/2019.
Elberfeld, T., J. De Beenhouwer, and J. Sijbers, "Fiber assignment by continuous tracking for parametric fiber reinforced polymer reconstruction", 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), vol. 11072, 2019. PDF icon Download paper (5.15 MB)
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.

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