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S. Delputte, Leemans, A., Fieremans, E., De Deene, Y., D'Asseler, Y., Lemahieu, I., Achten, E., Sijbers, J., and Van de Walle, R., Density Regularized Fiber Tractography of the Brain White Matter using Diffusion Tensor MRI, in 13th Scientific Meeting - International Society for Magnetic Resonance in Medicine, Miami, USA, 2005, p. 1309.
A. Demertzi, Van Ombergen, A., Tomilovskaya, E., Jeurissen, B., Pechenkova, E. V., Di Perri, C., Litvinova, L., Amico, E., Rumshiskaya, A., Rukavishnikov, I., Sijbers, J., Sinitsyn, V., Kozlovskaya, I. B., Sunaert, S., Parizel, P. M., Van de Heyning, P. H., Laureys, S. S. L., and Wuyts, F. L., Cortical reorganization in an astronaut’s brain after long-duration spaceflight, Brain Structure and Function, vol. 221, no. 5, pp. 2873–2876, 2016.PDF icon Download paper (820.49 KB)
A. J. den Dekker and Sijbers, J., Data distributions in magnetic resonance images: a review, Physica Medica, vol. 30, no. 7, pp. 725–741, 2014.PDF icon Download paper (410.33 KB)PDF icon Download paper (protected) (505.58 KB)
A. J. den Dekker, Sijbers, J., and Van Dyck, D., How to design an HREM experiment so as to attain the highest precision?, in ICEM14: 14th International Congress on Electron Microscopy, Cancun, Mexico, 1998, vol. 1, pp. 621-622.
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)
A. J. den Dekker and van den Bos, A., Resolution: a survey, J. Opt. Soc. Am. A, vol. 14, pp. 547–557, 1997.
A. J. den Dekker, Sijbers, J., Bos, R., and Smolders, A., Brain activation detection from functional magnetic resonance imaging data using likelihood based hypothesis tests, in Abstracts of the 24th Benelux Meeting on Systems and Control, Houffalize, Belgium, 2005.
A. J. den Dekker and Sijbers, J., Detection of brain activation from magnitude fMRI data using a generalized likelihood ratio test, in Proceedings of the 12th European Signal Processing Conference, Vienna, Austria, 2004, pp. 233-236.
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, Gonnissen, J., De Backer, A., Sijbers, J., and Van Aert, S., Estimation of unknown structure parameters from high-resolution (S)TEM images: what are the limits?, Ultramicroscopy, vol. 134, pp. 34-43, 2013.
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.
A. J. den Dekker and Sijbers, J., Brain activation detection from magnitude fMRI data using a generalized likelihood ratio test, in Abstracts of the 23rd Benelux Meeting on Systems and Control, Helvoirt, The Netherlands, 2004.
A. J. den Dekker, Sijbers, J., Verhoye, M., and Van Dyck, D., Maximum Likelihood estimation of the signal component magnitude in phase contrast MR images, in Proceedings of SPIE Medical Imaging, San Diego, California, USA, 1998, vol. 3338, pp. 408-415.
A. J. den Dekker and Sijbers, J., Advanced Image Processing in Magnetic Resonance Imaging, in Series: Signal Processing and Communications, vol. 27, L. Landini, Ed. Marcel Dekker, 2005, pp. 85-143.
A. J. den Dekker, Sijbers, J., and Van Dyck, D., Quantitative HREM: viewpoints on resolution, precision, and experimental design, in Acta Cryst. A55 Supplement, Abstract M11.OE.OO5, IUCR Glasgow, Scotland, 1999.
A. J. den Dekker and Sijbers, J., Maximum Likelihood estimation of signal amplitude and noise variance, in 13th IFAC Symposium on System Identification (SYSID-2003), Rotterdam, The Netherlands, 2003, pp. 126-131.
A. J. den Dekker, Sijbers, J., and Van Dyck, D., Optimizing the setting of an electron microscope for highest resolution using statistical parameter estimation theory, in Workshop: Towards Atomic Resolution Analysis 98, Port Ludlow, WA, U.S.A, 1998.
A. J. den Dekker, Sijbers, J., and Van Dyck, D., Optimizing the design of an HREM experiment so as to attain the highest resolution, in Proceedings of FEMMS98: Frontiers of Electron Microscopy in Material Science, Kloster Irsee, Germany, 1998.
T. Dhollander, Veraart, J., Van Hecke, W., Maes, F., Sunaert, S., Sijbers, J., and Suetens, P., Feasibility and advantages of diffusion weighted imaging atlas construction in Q-space, in MICCAI 2011: Medical Image Computing and Computer-Assisted Intervention, 2011, pp. 166-173.
T. Dhollander, Smith, R. E., Tournier, J. - D., Jeurissen, B., and Connelly, A., Time to Move On: An FOD-Based DEC Map to Replace DTI's Trademark DEC FA, ISMRM 23th Annual Meeting. p. 1027, 2015.
E. Dhondt, Jeurissen, B., Danneels, L., and Van Oosterwijck, J., Structural alterations of cognitive emotional brain regions are linked to the presence of spinal sensitization in low back pain, 9th Biennial Congress of the Belgian Back Society, entitled ``The Challenge of activating Patients with Low Back Pain``. 2018.
E. Dhondt, Jeurissen, B., Danneels, L., and Van Oosterwijck, J., Structural adaptations of cognitive emotional brain regions are linked to endogenous pain modulation: a psychophysical and brain imaging study in healthy people and in low back pain, 10th Interdisciplinary World Congress on Low Back and Pelvic Girdle Pain. p. 399, 2019.
C. Distante, Blanc-Talon, J., Philips, W., Popescu, D., and Scheunders, P., ACIVS 2016, Advanced Concepts for Intelligent Vision Systems, Lecture Notes in Computer Science, vol. 10016. 2016.
A. Doroshin, Jillings, S., Jeurissen, B., Tomilovskaya, E., Pechenkova, E. V., Nosikova, I., Rumshiskaya, A., Litvinova, L., Rukavishnikov, I., De Laet, C., Schoenmaekers, C., Sijbers, J., Laureys, S. S. L., Petrovichev, V., Van Ombergen, A., Annen, J., Sunaert, S., Parizel, P. M., Sinitsyn, V., Eulenburg, Pzu, Osipowicz, K., and Wuyts, F. L., Brain Connectometry Changes in Space Travelers After Long-Duration Spaceflight, Front. Neural Circuits, vol. 16, 2022.
T. Dox, Heylen, R., and Scheunders, P., Spectral variability in a multilinear mixing model, in IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.

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