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B. Koirala, Zahiri, Z., and Scheunders, P., “A Robust Supervised Method for Estimating Soil Moisture Content From Spectral Reflectance”, IEEE Transactions on Geoscience and Remote Sensing , vol. 60, pp. 1-13, 2022.PDF icon soil_moisture_content.pdf (7.95 MB)
B. Koirala, Mboga, N., Moelans, R., Knaeps, E., Sels, S., Winters, F., Samsonova, S., Vanlanduit, S., and Scheunders, P., “Study on the Potential of Oil Spill Monitoring in a Port Environment Using Optical Reflectance”, Remote Sensing, 2023.PDF icon remotesensing-15-04950_1.pdf (20.86 MB)
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. 58, no. 10, pp. 7393-7405, 2020.PDF icon final_version_leaf_parameter_estimation.pdf (2.66 MB)
B. Koirala, Rasti, B., Bnoulkacem, Z., Ribeiro, A. De Lima, Madriz, Y., Herrmann, E., Gestels, A., De Kerf, T., Lorenz, S., Fuchs, M., Janssens, K., Steenackers, G., Gloaguen, R., and Scheunders, P., “A Multisensor Hyperspectral Benchmark Dataset For Unmixing of Intimate Mixtures”, IEEE Sensors Journal, 2023.PDF icon a_multisensor_hyperspectral_benchmark_dataset_for_unmixing_of_intimate_mixtures_1_.pdf (22.13 MB)
B. Koirala, Rasti, B., and Scheunders, P., “A Supervised Approach for Estimating Fractional Abundances of Binary Intimate Mixtures”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, pp. 1-11, 2024.PDF icon Download paper (4.49 MB)
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.
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.
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.
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.
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.
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.
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.
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.
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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)
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, 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)
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 and Szczepankiewicz, F., “Multi-tissue spherical deconvolution of tensor-valued diffusion MRI.”, Neuroimage, vol. 245, p. 118717, 2021.
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.

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