Publications

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2026
M. Yosifov, Fernandes, T. Linhares, Zanini, F., Carmignato, S., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Investigating the Influence of Individual Physical Effects on Dimensional Measurement Deviations Using XCT Simulations”, Measurement, vol. 263, no. 120168, 2026.
S. Mandija, Arduino, A., Cui, C., Fuchs, P., Giannakopoulos, I. I., Ider, Y. Ziya, Jung, K. - J., Katoch, N., Katscher, U., Kim, D. - H., Lattanzi, R., Meerbothe, T., Odille, F., Shmueli, K., Soullié, P., Tha, K. Khin, Zilberti, L., and van den Berg, C. A. T., “Standardization of MR Electrical Properties Tomography: A Guideline From the ISMRM Electro-Magnetic Tissue Properties Study Group.”, J Magn Reson Imaging, 2026.
2025
Y. Huybrechts, De Ridder, R., Bergen, D., De Samber, B., Boudin, E., Tonelli, F., Knapen, D., Vergauwen, L., Schepers, D., Van Dijck, E., Tong, Q., Verhulst, A., De Beenhouwer, J., Sijbers, J., Hammond, C., Forlino, A., Mortier, G., Coucke, P., P Witten, E., Kwon, R. Young, Willaert, A., Hendrickx, G., and Van Hul, W., “Loss of the Ubiquitin-Associated Domain of sqstm1/p62 in Zebrafish Causes a Phenotype Resembling Paget’s Disease of Bone”, Calcified Tissue International, vol. 116, no. 1, pp. 1-15, 2025.
D. Ali Chaghdo, Koirala, B., Cristina, L., De Kock, T., Fontaine, L., Hayen, R., and Scheunders, P., “Moisture Content Estimation of Porous Building Stones using Hyperspectral Imaging”, Scientific Data, vol. 13, p. 102, 2025.PDF icon moisture_content_estimation_of_porous_building_sto.pdf (4.32 MB)
D. Ali Chaghdo, Koirala, B., Cristina, L., De Kock, T., Fontaine, L., Hayen, R., and Scheunders, P., “Moisture Content Estimation of Porous Building Stones using Hyperspectral Imaging”, Scientific Data, vol. 13, p. 102, 2025.PDF icon moisture_content_estimation_of_porous_building_sto.pdf (4.32 MB)
2024
D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, vol. 54, pp. 13160–13177, 2024.PDF icon Download paper (2.48 MB)
D. Iuso, Chatterjee, S., Cornelissen, S., Verhees, D., De Beenhouwer, J., and Sijbers, J., “Voxel-wise segmentation for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural models”, Applied Intelligence, vol. 54, pp. 13160–13177, 2024.PDF icon Download paper (2.48 MB)
2023
G. Zhang, Scheunders, P., and Cerra, D., “Shadow-aware nonlinear spectral unmixing with spatial regularization”, IEEE Transactions on Geoscience and Remote Sensing, vol. 61, p. 5517516, 2023.PDF icon shadow-aware_nonlinear_spectral_unmixing_with_spatial_regularization.pdf (17.62 MB)
M. Siqueira Pinto, Winzeck, S., Kornaropoulos, E. N., Richter, S., Paolella, R., Correia, M. M., Glocker, B., Williams, G., Vik, A., Posti, J., Håberg, A. Kristine, Stenberg, J., Guns, P. - J., den Dekker, A. J., Menon, D. K., Sijbers, J., Van Dyck, P., and Newcombe, V. F. J., “Use of support vector machines approach via ComBat harmonized diffusion tensor imaging for the diagnosis and prognosis of mild traumatic brain injury: a CENTER-TBI study”, Journal of Neurotrauma, vol. 40, no. 13-14, pp. 1317-1338, 2023.
2022
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.
J. Christopher, Lumbeeck, L. - P., Paramonov, P., De Beenhouwer, J., and Sijbers, J., “Discrete Terahertz tomography: a simulation study”, e-Journal of Nondestructive Testing, vol. 27, no. 3, 2022.PDF icon Download paper (345.5 KB)
G. Barisano, Sepehrband, F., Collins, H. R., Jillings, S., Jeurissen, B., Taylor, A. J., Schoenmaekers, C., De Laet, C., Rukavishnikov, I., Nosikova, I., Rumshiskaya, A., Annen, J., Sijbers, J., Laureys, S. S. L., Van Ombergen, A., Petrovichev, V., Sinitsyn, V., Pechenkova, E. V., Grishin, A., Eulenburg, Pzu, Law, M., Sunaert, S., Parizel, P. M., Tomilovskaya, E., Roberts, D., and Wuyts, F. L., “The effect of prolonged Spaceflight on Cerebrospinal Fluid and Perivascular Spaces of Astronauts and Cosmonauts”, PNAS, vol. 119, no. 17, 2022.
V. Anania, Collier, Q., Veraart, J., Buikema, A. Eline, Vanhevel, F., Billiet, T., Jeurissen, B., den Dekker, A. J., and Sijbers, J., “Improved diffusion parameter estimation by incorporating T2 relaxation properties into the DKI-FWE model”, NeuroImage, vol. 256, p. 119219, 2022.
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., “MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, no. 5522815, 2022.PDF icon misicnet_ieee_tgrs_author_version.pdf (5.57 MB)
B. Rasti, Koirala, B., Scheunders, P., and Chanussot, J., “MiSiCNet: Minimum Simplex Convolutional Network for Deep Hyperspectral Unmixing”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon misicnet_ieee_tgrs_author_version.pdf (5.52 MB)
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)
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.
2021
M. Naeyaert, Aelterman, J., Golkov, V., Cremers, D., Pizurica, A., Sijbers, J., and Verhoye, M., “Accelerating in vivo fast spin echo high angular resolution diffusion imaging with an isotropic resolution in mice through compressed sensing”, Magnetic Resonance in Medicine, vol. 85, no. 3, pp. 1397-1413, 2021.
M. Roshani, Phan, G., Roshani, G. Hossein, Hanus, R., Corniani, E., and Nazemi, E., “Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil–water three phase flows”, Measurement, vol. 168, 2021.
M. Roshani, Phan, G. T. T., Roshani, G. Hossein, Hanus, R., Duong, T., Corniani, E., Nazemi, E., and Kalmouni, E. M., “Evaluation of flow pattern recognition and void fraction measurement in two phase flow independent of oil pipeline’s scale layer thickness”, Alexandria Engineering Journal, vol. 60, 2021.
A. De Luca, Ianus, A., Leemans, A., Palombo, M., Shemesh, N., Zhang, H., Alexander, D. C., Nilsson, M., Froeling, M., Biessels, G. - J., Zucchelli, M., Frigo, M., Albay, E., Sedlar, S., Alimi, A., Deslauriers-Gauthier, S., Deriche, R., Fick, R., Afzali, M., Pieciak, T., Bogusz, F., Aja-Fernandez, S., Ozarslan, E., Jones, D. K., Chen, H., Jin, M., Zhang, Z., Wang, F., Nath, V., Parvathaneni, P., Morez, J., Sijbers, J., Jeurissen, B., Shreyas,, Fadnavis,, Endres, S., Rokem, A., Garyfallidis, E., Sanchez, I., Prchkovska, V., Rodrigues, P., Landman, B. A., and Schilling, K. G., “On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge”, NeuroImage, vol. 240, no. 118367, 2021.
E. Ribeiro Sabidussi, Klein, S., Caan, M., Bazrafkan, S., den Dekker, A. J., Sijbers, J., Niessen, W. J., and Poot, D. H. J., “Recurrent Inference Machines as inverse problem solvers for MR relaxometry”, Medical Image Analysis, vol. 74, pp. 1-11, 2021.PDF icon Download paper (2.26 MB)
2020
M. Roshani, Sattari, M. Amir, Ali, P. Jammal Muh, Roshani, G. Hossein, Corniani, E., and Nazemi, E., “Application of GMDH neural network technique to improve measuring precision of a simplified photon attenuation based two-phase flowmeter”, Flow Measurement and Instrumentation, vol. 75, 2020.
P. Bladt, den Dekker, A. J., Clement, P., Achten, E., and Sijbers, J., “The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling”, NMR in Biomedicine, vol. 33, no. 12, pp. 1-17, 2020.PDF icon Download paper (16.44 MB)
V. Varkarakis, Bazrafkan, S., and Corcoran, P., “Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets”, Science Direct Elsevier Neural Networks, vol. 121, pp. 101-121, 2020.

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