Publications

Export 107 results:
[ Author(Asc)] Type Year
Filters: First Letter Of Last Name is D  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
D
A. Duijster, Scheunders, P., and De Backer, S., Wavelet-Based EM Algorithm for Multispectral-Image Restoration, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3892-3898, 2009.
A. Duijster, De Backer, S., and Scheunders, P., Wavelet-based Multicomponent Image Restoration, in Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, United States, September 9-12, 2007, vol. 6763.
A. Duijster, De Backer, S., and Scheunders, P., Multicomponent image restoration, an experimental study, Lecture Notes in Computer Science, vol. 4633, pp. 58-68, 2007.
A. Duijster, De Backer, S., and Scheunders, P., Wavelet-based Multispectral Image Restoration, in IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008, vol. 3, pp. 79-82.
J. Driesen and Scheunders, P., Wavelet based Filter Array Demosaicking, in Proc. ICIP2004, IEEE International Conference on Image Processing, 24-27 october, Singapore, 2004, pp. 3311-3314.
J. Driesen, Thoonen, G., and Scheunders, P., Spatial hyperspectral image classification by prior segmentation, in Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009, Cape Town, South Africa, 2009, vol. 3, p. III-709 - III-712.
J. Driesen and Scheunders, P., Wavelet based segmentation of multi-component images, in IEEE BENELUX/DSP Valley Signal Processing Symposium (SPS-DARTS) March 28-29, Antwerp, Belgium, 2006, pp. 151-154.
J. Driesen and Scheunders, P., Wavelet based segmentation of multivalued images, in SPIE Optics East, 23-26 October, Boston, Massachusetts USA, 2005, vol. 6001, pp. 13-22.
J. Driesen and Scheunders, P., A Multicomponent Image Segmentation Framework, Lecture Notes in Computer Science, vol. 5259, pp. 589-600, 2008.
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.
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.
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.
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.
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.
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 van den Bos, A., Resolution: a survey, J. Opt. Soc. Am. A, vol. 14, pp. 547–557, 1997.
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, 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 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., 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., 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 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., 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., 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.

Pages