Publications

Export 1332 results:
[ Author(Desc)] Type Year
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 
J
B. Jeurissen, Leemans, A., and Sijbers, J., “Automated correction of improperly rotated diffusion gradient orientations in diffusion-weighted MRI”, Medical Image Analysis, vol. 18, pp. 953-962, 2014.
B. Jeurissen, Leemans, A., Jones, D. K., Tournier, J. - D., and Sijbers, J., “Counting the number of fiber orientations in diffusion MRI voxels using constrained spherical deconvolution”, 2nd meeting of the ISMRM Benelux Chapter. Utrecht, The Netherlands, 2010.
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., “Diffusion MRI fiber tractography of the brain”, NMR in Biomedicine, 2019.
B. Jeurissen, “Improved analysis of brain connectivity using high angular resolution diffusion MRI”, University of Antwerp, 2012.PDF icon Download thesis book (35.42 MB)
B. Jeurissen, Leemans, A., Tournier, J. - D., and Sijbers, J., “Probabilistic Fiber Tracking using the Residual Bootstrap with Constrained Spherical Deconvolution MRI”, ISMRM, 17th Scientific Meeting and Exhibition. Honolulu, USA, 2009.
B. Jeurissen and Szczepankiewicz, F., “Multi-tissue spherical deconvolution of tensor-valued diffusion MRI.”, Neuroimage, vol. 245, p. 118717, 2021.
B. Jeurissen, Leemans, A., Tournier, J. - D., and Sijbers, J., “Estimation of Uncertainty in Constrained Spherical Deconvolution Fiber Orientations”, in 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France, 2008, pp. 907-910.
B. Jeurissen, “Processing multi-shell diffusion MRI data using MRtrix3”, Front. Neuroinform. Conference Abstract: Second Belgian Neuroinformatics Congress. 2015.
B. Jeurissen, Leemans, A., Jones, D. K., Tournier, J. - D., and Sijbers, J., “Estimating the number of fiber orientations in diffusion MRI voxels: a constrained spherical deconvolution study”, ISMRM, 18th Scientific Meeting and Exhibition. Stockholm, Sweden, 2010.
B. Jeurissen, Leemans, A., Tournier, J. - D., Jones, D. K., and Sijbers, J., “Investigating the prevalence of complex fiber configurations in white matter tissue with diffusion magnetic resonance imaging.”, Human Brain Mapping, vol. 34, pp. 2747-66, 2013.
B. Jeurissen, Tournier, J. - D., and Sijbers, J., “Tissue-type segmentation using non-negative matrix factorization of multi-shell diffusion-weighted MRI images”, ISMRM 23th Annual Meeting, Toronto, Ontario, Canada, vol. 23. p. 349, 2015.PDF icon Download abstract (1.11 MB)
B. Jeurissen, Leemans, A., Tournier, J. - D., and Sijbers, J., “Bootstrap methods for estimating uncertainty in Constrained Spherical Deconvolution fiber orientations”, ISMRM, 16th Scientific Meeting and Exhibition. Toronto, Canada, p. 3324, 2008.
B. Jeurissen, Leemans, A., Tournier, J. - D., Jones, D. K., and Sijbers, J., “Assessing the implications of complex fiber configurations for DTI metrics in real data sets”, ISMRM, 20th Scientific Meeting and Exhibition. Melbourne, Australia, p. 3584, 2012.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., P Eulenburg, zu, Sijbers, J., Wuyts, F. L., and Jeurissen, B., “Diffusion MRI reveals macro- and microstructural changes in cosmonauts' brains after long-duration spaceflight”, Proc Intl Soc Mag Reson Med 28. p. 4531, 2020.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I. B., Manko, O., Danilichev, S., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., Eulenburg, Pzu, Sijbers, J., Wuyts, F. L., and Jeurissen, B., “Macro- and microstructural changes in cosmonauts’ brains after long-duration spaceflight”, Science Advances, vol. 6, no. 36, p. eaaz9488, 2020.PDF icon Download paper (942.53 KB)
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Laureys, S., P Eulenburg, zu, Sunaert, S., Sijbers, J., Wuyts, F. L., and Jeurissen, B., “Diffusion-weighted imaging reveals structural brain changes in cosmonauts after long-duration spaceflight”, 36th Annual Scientific Meeting of the European Society for Magnetic Resonance in Medicine & Biology, Rotterdam, The Netherlands, vol. 32 (Suppl. 1). p. Magn Reson Mater Phy. 2019; 32(Suppl. 1):S101, 2019.
S. Jillings, Pechenkova, E. V., Tomilovskaya, E., Rukavishnikov, I., Jeurissen, B., Van Ombergen, A., Nosikova, I., Rumshiskaya, A., Litvinova, L., Annen, J., De Laet, C., Schoenmaekers, C., Sijbers, J., Petrovichev, V., Sunaert, S., Parizel, P. M., Sinitsyn, V., P Eulenburg, zu, Laureys, S. S. L., Demertzi, A., and Wuyts, F. L., “Prolonged microgravity induces reversible and persistent changes on human cerebral connectivity”, Communications Biology, vol. 6, no. 46, 2023.
S. Jillings, “The impact of long-duration spaceflight on brain structure and function”, University of Antwerp, 2021.
J. S. Jorgensen and Sijbers, J., “Just enough physics”, in Computed Tomography: Algorithms, Insight, and Just Enough Theory , vol. 4, SIAM, 2021.
J. Juntu, Schepper, A. D. M., Van Dyck, P., Van Dyck, D., Gielen, J. L., Parizel, P. M., and Sijbers, J., “Classification of Soft Tissue Tumors by Machine Learning Algorithms”, in Soft Tissue Tumors, InTech, 2011.PDF icon Book.Chapter-Copy.Sent_.to_.InTech-(21.07.2011).pdf (732.07 KB)
J. Juntu, Sijbers, J., Van Dyck, D., and Gielen, J. L., “Bias Field Correction for MRI Images”, in Proceedings of the 4th International Conference on Computer Recognition Systems (CORES05), Rydzyna Castle, Poland, 2005, pp. 543-551.
J. Juntu, Sijbers, J., De Backer, S., Rajan, J., and Van Dyck, D., “A Machine Learning Study of Several Classifiers Trained with Texture Analysis Features to Differentiate Benign from Malignant Soft Tissue Tumors in T1-MRI Images”, Journal of Magnetic Resonance Imaging, vol. 31, pp. 680–689, 2010.PDF icon Download paper (300.61 KB)
J. Juntu, Sijbers, J., and Van Dyck, D., “Classification of soft tissue tumors in MRI images using kernel PCA and regularized least square classifier”, in Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, Anaheim, CA, USA, 2007, pp. 362–367.
K
J. Kaartinen, Hätönen, J., and Roine, T., “Machine Vision of Flotation Froths with a Rapid-Prototyping Platform”, in IFAC Workshop on Automation in Mining, Mineral and Metal Industry (IFACMMM2009), 2009.
A. Karami, M.Yazdi,, and Zolghadre, A., “Noise Reduction of Hyperspectral Images Using Kernel Nonnegative Tucker Decomposition”, IEEE Journal of Selected Topics in Signal Processing, vol. 5, no. 3, 2011.

Pages