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B. Jeurissen, Leemans, A., Tournier, J. - D., and Sijbers, J., Can residual bootstrap reliably estimate uncertainty in fiber orientation obtained by spherical deconvolution from diffusion-weighted MRI?, 14th Annual Meeting of the Organization of Human Brain Mapping, vol. 41. Melbourne, Australia, 2008.
B. Jeurissen, Processing multi-shell diffusion MRI data using MRtrix3, Belgian Neuroinformatics Congress. Frontiers in Neuroinformatics, 2015.
B. Jeurissen, Naeyaert, M., Leemans, A., and Sijbers, J., Correction of DWI gradient orientations using registration techniques, 3rd meeting of the ISMRM Benelux Chapter, Hoeven, The Netherlands. 2011.
B. Jeurissen, Jillings, S., Giraldo, D. L., Van Ombergen, A., Tomilovskaya, E., Pechenkova, E., Rukavishnikov, I., Petrovichev, V., Sijbers, J., Eulenburg, Pzu, and Wuyts, F. L., Fixel-based analysis of multi-shell diffusion MRI reveals white matter changes after long-duration spaceflight, Proc. Intl. Soc. Mag. Reson. Med. p. 2057, 2024.
B. Jeurissen, Tournier, J. - D., Dhollander, T., Connelly, A., and Sijbers, J., Brain Tissue Types Resolved Using Spherical Deconvolution of Multi-Shell Diffusion MRI Data, ISMRM, 22nd Scientific Meeting and Exhibition. Milan, Italy, p. 973, 2014.
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., Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution, Human Brain Mapping, vol. 32, no. 3, pp. 461 - 479, 2011.
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., Diffusion MRI fiber tractography of the brain, NMR in Biomedicine, 2019.
B. Jeurissen, Leemans, A., Fieremans, E., and Sijbers, J., Fiber Tractography on a Crossing Fiber Phantom using Constrained Spherical Deconvolution MRI, Liège Image Days. Liège, Belgium, 2008.
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., Fiber Tracking on the 'Fiber Cup Phantom' using Constrained Spherical Deconvolution, in MICCAI workshop on Diffusion Modelling and the Fiber Cup (DMFC'09), London, United Kingdom, 2009.
H. K. Jenssen, Oberlander, B. C., De Beenhouwer, J., Sijbers, J., and Verwerft, M., Neutron radiography and tomography applied to fuel degradation during ramp tests and loss of coolant accident tests in a research reactor, Progress in Nuclear Energy, vol. 72, pp. 55-62, 2014.
I. O. Jelescu, Grussu, F., Ianus, A., Hansen, B., Barrett, R. L. C., Aggarwal, M., Michielse, S., Nasrallah, F., Syeda, W., Wang, N., Veraart, J., Roebroeck, A., Bagdasarian, A. F., Eichner, C., Sepehrband, F., Zimmermann, J., Soustelle, L., Bowman, C., Tendler, B. C., Hertanu, A., Jeurissen, B., Verhoye, M., Frydman, L., van de Looij, Y., Hike, D., Dunn, J. F., Miller, K., Landman, B. A., Shemesh, N., Anderson, A., McKinnon, E., Farquharson, S., Dell'Acqua, F., Pierpaoli, C., Drobnjak, I., Leemans, A., Harkins, K. D., Descoteaux, M., Xu, D., Huang, H., Santin, M. D., Grant, S. C., Obenaus, A., Kim, G. S., Wu, D., Le Bihan, D., Blackband, S. J., Ciobanu, L., Fieremans, E., Bai, R., Leergaard, T. B., Zhang, J., Dyrby, T. B., G. Johnson, A., Cohen‐Adad, J., Budde, M. D., and Schilling, K. G., Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging, Magnetic Resonance in Medicine, vol. 93, no. 6, pp. 2507 - 2534, 2025.
P. Jedrasik, Garcia, J., De Boeck, B., and Van Dyck, D., Optimal filtering versus regularization methods in the Fourier precompensation based proximity neurocorrection in electron beam lithography, Microelectronic Engineering, vol. 41, pp. 195-198, 1998.
E. Janssens, De Beenhouwer, J., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Neural Network Based X-Ray Tomography for Fast Inspection of Apples on a Conveyor Belt, in IEEE International Conference on Image Processing, 2015, pp. 917-921.
E. Janssens, Pelt, D., De Beenhouwer, J., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Fast Neural Network Based X-Ray Tomography of Fruit on a Conveyor Belt, Chemical Engineering Transactions, vol. 44, pp. 181-186, 2015.
E. Janssens, De Beenhouwer, J., Sanctorum, J., Senck, S., Heinzl, C., and Sijbers, J., Dual axis Dark Field Contrast Tomography for visualisation of scattering directions in a CFRP sample, 4th Conference on X-ray and Neutron Phase Imaging with Gratings. Zürich, Switzerland, pp. 79-80, 2017.PDF icon Download poster (729.94 KB)PDF icon Download abstract (116.29 KB)
E. Janssens, De Beenhouwer, J., Van Dael, M., De Schryver, T., Van Hoorebeke, L., Verboven, P., Nicolai, B., and Sijbers, J., Neural network Hilbert transform based filtered backprojection for fast inline X-ray inspection, Measurement Science and Technology, vol. 29, no. 3, 2018.PDF icon Download paper (3.4 MB)
E. Janssens, Senck, S., Heinzl, C., Kastner, J., De Beenhouwer, J., and Sijbers, J., Fast Reconstruction of CFRP X-ray Images based on a Neural Network Filtered Backprojection Approach, in 7th Conference on Industrial Computed Tomography, Leuven, Belgium, 2017.PDF icon Download paper (345.06 KB)
E. Janssens, Advances in X-ray reconstruction algorithms for limited data problems in conventional and non-conventional projection geometries, 2018.PDF icon Download thesis (17.29 MB)
E. Janssens, Alves Pereira, L. F., De Beenhouwer, J., Tsang, I. R., Van Dael, M., Verboven, P., Nicolai, B., and Sijbers, J., Fast inline inspection by neural network based filtered backprojection: Application to apple inspection, Case Studies in Nondestructive Testing and Evaluation, vol. 6, pp. 14–20, 2016.PDF icon Download paper (726.63 KB)
E. Janssens, Sijbers, J., Dierick, M., and De Beenhouwer, J., Fast detection of cracks in ultrasonically welded parts by inline X-ray inspection, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.
K. Vinay Jambhali, Koirala, B., Bnoulkacem, Z., and Scheunders, P., Soil Moisture Content Estimation from Hyperspectral Remote Sensing Data, in 2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2023, pp. 1-5.PDF icon soil_ketaki.pdf (580.15 KB)
K. Vinay Jambhali, Koirala, B., Bnoulkacem, Z., and Scheunders, P., Soil Moisture Content Estimation From Hyperspectral Remote Sensing Data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 22231-22240, 2025.PDF icon soil_moisture_content_estimation_from_hyperspectral_remote_sensing_data_1_.pdf (9.35 MB)
W. Jacquet, Nyssen, E., Sun, Y., De Munter, S., Sijbers, J., and Politis, C., Alveolar Nerve Unfolding Technique for Synoptic Analysis: Visualization and Quantification of Inferior Alveolar Nerve Tracings in Three-dimensional Cone-Beam Computed Tomography., The Journal of craniofacial surgery, vol. 24, no. 4, pp. e374-7, 2013.

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