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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.
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., 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, 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)
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.
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.
B. Jeurissen, Descoteaux, M., Mori, S., and Leemans, A., Diffusion MRI fiber tractography of the brain, NMR in Biomedicine, 2019.
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, Tournier, J. - D., Dhollander, T., Connelly, A., and Sijbers, J., Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data, NeuroImage, vol. 103, pp. 411–426, 2014.
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.
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)
K
A. Karami, Heylen, R., and Scheunders, P., Band-specific Shearlet-based Hyperspectral Image Noise Reduction, IEEE Transaction Geosciences and Remote Sensing , vol. 53, no. 9, 2015.
A. Karami, Heylen, R., and Scheunders, P., Hyperspectral Image Compression Optimized for Spectral Unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol. pp, no. 99, 2016.
D. Kazantsev, Van Eyndhoven, G., Lionheart, W. R. B., Withers, P. J., Dobson, K. J., McDonald, S. A., Atwood, R., and Lee, P. D., Employing temporal self-similarity across the entire time domain in computed tomography reconstruction, Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, vol. 373, 2015.
D. Kazantsev, Thompson, W. M., Lionheart, W. R. B., Van Eyndhoven, G., Kaestner, A. P., Dobson, K. J., Withers, P. J., and Lee, P. D., 4D-CT reconstruction with unified spatial-temporal patch-based regularization, Inverse Problems and Imaging, vol. 9, no. 2, pp. 447-467, 2015.
P. Kempeneers, De Backer, S., Debruyn, W., and Scheunders, P., Generic Wavelet-Based Hyperspectral Classification Applied to Vegetation Stress Detection, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, pp. 610-614, 2005.
P. Kempeneers, Zarco-Tejada, P. J., North, P. R. J., De Backer, S., Delalieux, S., Sepulcre-Canto, G., Morales, F., van Aardt, J., Sagardoy, R., Coppin, P., and Scheunders, P., Model inversion for chlorophyll estimation in open canopies from hyperspectral imagery, International Journal of Remote Sensing, vol. 29, pp. 5093-5111, 2008.
J. P. M. Kenney, McPhilemy, G., Scanlon, C., Najt, P., McInerney, S., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Hallahan, B., McDonald, C., and Cannon, D. M., The arcuate fasciculus network and verbal deficits in psychosis, Translational Neuroscience, vol. 8, no. 1, pp. 117-126, 2017.
J. Kenney, McInerney, S., McPhilemy, G., Najt, P., Scanlon, C., Arndt, S., Scherz, E., Byrne, F., Leemans, A., Jeurissen, B., Donohoe, G., Hallahan, B., McDonald, C., and Cannon, D., P. 3.033 Lateralisation of the arcuate fasciculus in psychosis & the role in verbal learning & auditory verbal hallucinations, European Neuropsychopharmacology, vol. 26, no. 1, pp. S76–S77, 2016.
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model, Computers in Biology and Medicine, vol. 117, no. 103600, pp. 1-13, 2020.
W. Keustermans, Huysmans, T., Danckaers, F., Zarowski, A., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., High quality statistical shape modelling of the human nasal cavity and applications, Royal Society Open Science, vol. 5, no. 12, 2018.PDF icon Download paper (1.85 MB)
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., Matlab® toolbox for semi-automatic segmentation of the human nasal cavity based on active shape modeling, Computers in Biology and Medicine, vol. 105, pp. 27-38, 2019.
B. Koirala, Zahiri, Z., and Scheunders, P., A Machine Learning Framework for Estimating Leaf Biochemical Parameters From Its Spectral Reflectance and Transmission Measurements, IEEE Transactions on Geoscience and Remote Sensing, vol. 99, pp. 1-13, 2020.
B. Koirala, Khodadadzadeh, M., Contreras, C., Zahiri, Z., Gloaguen, R., and Scheunders, P., A supervised method for nonlinear hyperspectral unmixing, Remote Sensing, vol. 11, no. 20 , 2019.

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