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G. Liu, Nath, T., Guo, Z., Linneweber, G., Claeys, A., Li, J., Bengochea, M., De Backer, S., Weyn, B., Sneyders, M., Nicasy, H., Yu, P., Scheunders, P., and Hassan, B., “A simple computer vision pipeline reveals the effects of isolation on social interaction dynamics in Drosophila”, Plos Computational Biology, vol. 14, no. 8, p. e1006410, 2018.
Y. - T. Ling, Cools, S., Bogdanowicz, J., Fleischmann, C., De Beenhouwer, J., Sijbers, J., and Vandervorst, W., “A Bottom-Up Volume Reconstruction Method for Atom Probe Tomography”, Microscopy and Microanalysis, vol. 28, no. 4, pp. 1-14, 2022.
W. Liao, Pizurica, A., Scheunders, P., Philips, W., and Pi, Y., “Semi-supervised local discriminant analysis for feature extraction in hyperspectral images”, IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 1, pp. 184-198, 2013.
A. Leemans, Sijbers, J., De Backer, S., Vandervliet, E., and Parizel, P. M., “Multiscale white matter fiber tract coregistration: a new feature-based approach to align diffusion tensor data”, Magnetic Resonance in Medicine, vol. 55, pp. 1414-1423, 2006.
A. Leemans, Sijbers, J., De Backer, S., Vandervliet, E., and Parizel, P. M., “Affine Coregistration of Diffusion Tensor Magnetic Resonance Images Using Mutual Information”, Lecture Notes in Computer Science, vol. 3708, pp. 523-530, 2005.PDF icon Download full paper (1.26 MB)
A. Leemans, Sijbers, J., Verhoye, M., Van Der Linden, A., and Van Dyck, D., “Mathematical Framework for Simulating Diffusion Tensor MR Neural Fiber Bundles”, Magnetic Resonance in Medicine, vol. 53, pp. 944-953, 2005.PDF icon Download full paper (1.55 MB)
D. Lacko, Huysmans, T., Vleugels, J., De Bruyne, G., Van Hulle, M. M., Sijbers, J., and Verwulgen, S., “Product sizing with 3D anthropometry and k-medoids clustering”, Computer-Aided Design, vol. 91, pp. 60-74, 2017.
D. Lacko, Vleugels, J., Fransen, E., Huysmans, T., De Bruyne, G., Van Hulle, M. M., Sijbers, J., and Verwulgen, S., “Ergonomic design of an EEG headset using 3D anthropometry”, Applied Ergonomics, vol. 58, pp. 128–136, 2017.
D. Lacko, Huysmans, T., Parizel, P. M., De Bruyne, G., Verwulgen, S., Van Hulle, M. M., and Sijbers, J., “Evaluation of an anthropometric shape model of the human scalp”, Applied Ergonomics, vol. 48, pp. 70-85, 2015.PDF icon Paper (3.63 MB)File Shape matrix (cfr section 2.1.1) (36.93 MB)File Measurement matrix (cfr section 2.2.1) (20.05 KB)File Labeled measurements (cfr section 2.2.1) (47.63 KB)
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R. F. Kooy, Reyniers, E., Verhoye, M., Sijbers, J., Cras, P., Oostra, B. A., Willems, P. J., and Van Der Linden, A., “Neuroanatomy of the fragile X knockout mouse brain studied using in vivo high resolution Magnetic Resonance Imaging (MRI)”, European Journal of Human Genetics, vol. 7, pp. 526-532, 1999.PDF icon ejhg99.pdf (261.08 KB)
A. Könik, Auer, B., De Beenhouwer, J., Kalluri, K., Zeraatkar, N., Furenlid, L. R., and King, M. A., “Primary, scatter, and penetration characterizations of parallel-hole and pinhole collimators for I-123 SPECT”, Physics in Medicine & Biology, vol. 64, no. 24, p. 245001, 2019.PDF icon i123_spectra_final_revision_11_7_19.pdf (7.63 MB)
A. Könik, De Beenhouwer, J., Mukherjee, J. M., Kalluri, K., Banerjee, S., Zeraatkar, N., Fromme, T. J., and King, M. A., “Simulations of a Multipinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging”, IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 2, pp. 444-451, 2018.
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.PDF icon remotesensing-11-02458-v3.pdf (3.23 MB)
B. Koirala, Zahiri, Z., Lamberti, A., and Scheunders, P., “Robust supervised method for nonlinear spectral unmixing accounting for endmember variability”, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 9, pp. 7434-7448, 2021.PDF icon ieee_version.pdf (3.76 MB)
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, 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, 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., 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)
B. Koirala, Rasti, B., Bnoulkacem, Z., and Scheunders, P., “Nonlinear Spectral Unmixing Using Bézier Surfaces”, IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-16, 2024.PDF icon Download paper (9.66 MB)
B. Koirala and Scheunders, P., “An efficient method for water content estimation of building materials from spectral reflectance”, NDT & E International, vol. 147, p. 103214, 2024.PDF icon Download paper (7.21 MB)
H. Khan, Giraldo, D., Woodruff, H. C., Werthen-Brabants, L., Mali, S. Atul, Amirrajab, S., De Brouwer, E., Popescu, V., Van Wijmeersch, B., Gerlach, O., Sijbers, J., Peeters, L. M., and Lambin, P., “Leveraging Hand-Crafted Radiomics on Multicenter FLAIR MRI for Predicting Disability Worsening in People with Multiple Sclerosis”, Front. Neurosci., vol. 19, 2025.
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.

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