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Journal Article
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)
F. Calamante, Jeurissen, B., Smith, R. E., Tournier, J. - D., and Connelly, A., The role of whole-brain diffusion MRI as a tool for studying human in vivo cortical segregation based on a measure of neurite density, Magnetic Resonance in Medicine, vol. 79, no. 5, pp. 2738–2744, 2018.
P. Pullens, Bladt, P., Sijbers, J., Maas, A. I. R., and Parizel, P. M., A safe, cheap and easy-to-use isotropic diffusion phantom for clinical and multicenter studies, Medical Physics, vol. 44, no. 3, pp. 1063–1070, 2017.
I. J. Tsang, Tsang, I. R., De Boeck, B., and Van Dyck, D., Scaling and critical probability for cluster size and lattice animals diversity on randomly occupied square lattices, Journal of Physics A: Mathematical and General, vol. 33, pp. 2739-2754, 2000.
M. Van Dael, Lebotsa, S., Herremans, E., Verboven, P., Sijbers, J., Opara, U. L., Cronje, U. L., and Nicolai, B., A segmentation and classification algorithm for online detection of internal disorders in citrus using X-ray radiographs, Postharvest Biology and Technology, vol. 112, pp. 205-214, 2016.
K. J. Batenburg, Van Aarle, W., and Sijbers, J., A Semi-Automatic Algorithm for Grey Level Estimation in Tomography, Pattern Recognition Letters, vol. 32, pp. 1395-1405, 2011.
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.
G. Zhang, Scheunders, P., Cerra, D., and Muller, R., Shadow-aware nonlinear spectral unmixing for hyperspectral imagery, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 5514-5533, 2022.PDF icon shadow-aware_nonlinear_spectral_unmixing_for_hyperspectral_imagery.pdf (9.51 MB)
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.
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.
J. Fatermans, den Dekker, A. J., Müller-Caspary, K., Lobato, I., O'Leary, C. M., Nellist, P. D., and Van Aert, S., Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images, Phys. Rev. Lett., vol. 121, p. 056101, 2018.
J. Grammens, Van Haver, A., Danckaers, F., Booth, B. G., Sijbers, J., and Verdonk, P., Small medial femoral condyle morphotype is associated with medial compartment degeneration and distinct morphological characteristics: a comparative pilot study, Knee Surgery, Sports Traumatology, Arthroscopy, no. 686 , 2020.
E. K. Ghasrodashti, Karami, A., Heylen, R., and Scheunders, P., Spatial Resolution Enhancement of Hyperspectral Images Using Spectral Unmixing and Bayesian Sparse Representation, Remote Sensing, vol. 9, no. 6, 2017.
V. Van Meir, Boumans, T., De Groof, G., Van Audekerke, J., Smolders, A., Scheunders, P., Sijbers, J., Verhoye, M., Balthazart, J., and Van Der Linden, A., Spatiotemporal properties of the BOLD response in the songbirds auditory circuit during a variety of listening tasks, NeuroImage, vol. 25, pp. 1242-1255, 2005.
J. Van Audekerke, Verhoye, M., Peeters, R. R., Sijbers, J., and Van Der Linden, A., Special designed RF-antenna with integrated non-invasive carbon electrodes for simultaneous MRI and EEG acquisition at 7T, Magnetic Resonance Imaging, vol. 18, pp. 887-891, 2000.PDF icon Download full paper (179 KB)
D. Burazerovic, Heylen, R., Raymaekers, D., Knaeps, E., and Scheunders, P., A spectral-unmixing approach to estimate water-mass concentrations in case-II waters, IEEE-JSTARS, Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, 2014.
Y. Huybrechts, De Ridder, R., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Schepers, D., De Beenhouwer, J., Sijbers, J., Forlino, A., Coucke, P., P. Witten, E., Kwon, R., Willaert, A., Hendrickx, G., and Van Hul, W., The sqstm1tmΔUBA zebrafish model, a proof-of-concept in vivo model for Paget’s disease of bone?, Bone Reports, vol. 16, no. 101483, pp. 75-76, 2022.
B. G. Booth, Keijsers, N. L. W., Sijbers, J., and Huysmans, T., STAPP: SpatioTemporal Analysis of Plantar Pressure Measurements using Statistical Parametric Mapping, Gait and Posture, vol. 3, no. 63, pp. 268-275, 2018.
B. Bosmans, Huysmans, T., Wirix-Speetjens, R., Verschueren, P., Sijbers, J., Bosmans, J., and Vander Sloten, J., Statistical shape modeling and population analysis of the aortic root of TAVI patients, Journal of Medical Devices, vol. 7, no. 4, 2013.
G. Van de Wouwer, Scheunders, P., and Van Dyck, D., Statistical texture characterization from discrete wavelet representations, IEEE Transactions on Image Processing, vol. 8, pp. 592-598, 1999.
A. De Backer, van den Bos, K. H. W., Van den Broek, W., Sijbers, J., and Van Aert, S., StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images, Ultramicroscopy, vol. 171, pp. 104–116, 2016.
N. J. Forde, O'Donoghue, S., Scanlon, C., Emsell, L., Chaddock, C., Leemans, A., Jeurissen, B., Barker, G. J., Cannon, D. M., Murray, R. M., and others, Structural brain network analysis in families multiply affected with bipolar I disorder, Psychiatry Research: Neuroimaging, vol. 234, pp. 44–51, 2015.
N. J. Forde, Ronan, L., Suckling, J., Scanlon, C., Neary, S., Holleran, L., Leemans, A., Tait, R., Rua, C., Fletcher, P. C., Jeurissen, B., Dodds, C. M., Miller, S. R., Bullmore, E. T., McDonald, C., Nathan, P. J., and Cannon, D. M., Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism., NeuroImage, vol. 90, pp. 280-9, 2014.
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)
S. Sekar, Jonckers, E., Verhoye, M., Willems, R., Veraart, J., Van Audekerke, J., Couto, J., Giugliano, M., Wuyts, K., Dedeurwaerdere, S., Sijbers, J., Mackie, C., Ver Donck, L., Steckler, T., and Van Der Linden, A., Subchronic memantine induced concurrent functional disconnectivity and altered ultra-structural tissue integrity in the rodent brain: revealed by multimodal MRI., Psychopharmacology, vol. 227, no. 3, pp. 479-91, 2013.

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