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2021
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., “Chapter Four - Atom counting”, in Advances in Imaging and Electron Physics,, vol. 217, Science Direct Elsevier, 2021.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., “Chapter One - Introduction”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
J. Fatermans, De Backer, A., den Dekker, A. J., and Van Aert, S., “Chapter Seven - Image-quality evaluation and model selection with maximum a posteriori probability”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
J. Fatermans, De Backer, A., den Dekker, A. J., and Van Aert, S., “Chapter Six - Atom column detection”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., “Chapter Three - Efficient fitting algorithm”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
A. De Backer, Fatermans, J., den Dekker, A. J., and Van Aert, S., “Chapter Two - Statistical parameter estimation theory: principles and simulation studies”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
P. Van Dyck, Froeling, M., Heusdens, C. H. W., Sijbers, J., Ribbens, A., and Billiet, T., “Diffusion Tensor Imaging of the Anterior Cruciate Ligament Following Primary Repair with Internal Bracing: a Longitudinal Study”, Journal of Orthopaedic Research , vol. 39, pp. 1318–1330, 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.
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.
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.
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.
D. Frenkel, De Beenhouwer, J., and Sijbers, J., “Tabu-DART: a dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
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.
T. Elberfeld, Fröhler, B., Heinzl, C., Sijbers, J., and De Beenhouwer, J., “cuPARE: Parametric Reconstruction of Curved Fibres from Glass fibre-reinforced Composites”, Nondestructive Testing and Evaluation, 2022.PDF icon Download paper (9.66 MB)
N. Francken, Paramonov, P., Sijbers, J., and De Beenhouwer, J., “Edge Illumination Phase Contrast Simulations Using the OptiX GPU Ray Tracing Engine”, 5th International Conference on Tomography of Materials & Structures (ICTMS). 2022.
M. Yosifov, Reiter, M., Heupl, S., Gusenbauer, C., Fröhler, B., R. Gutierrez, F. -, De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Probability of Detection applied to X-ray inspection using numerical simulations”, Nondestructive Testing and Evaluation, vol. 37, no. 5, pp. 536-551, 2022.
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.
2023
N. Francken, Sanctorum, J., Renders, J., Paramonov, P., Sijbers, J., and De Beenhouwer, J., “A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations”, in 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023.PDF icon Download paper (4.14 MB)
M. Yosifov, Weinberger, P., Reiter, M., Fröhler, B., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., “Defect detectability analysis via Probability of defect detection between traditional and deep learning methods in numerical simulations”, in e-Journal of Nondestructive Testing, 2023, vol. 28, no. 3.PDF icon Download paper (2.37 MB)
N. Francken, Paramonov, P., Sijbers, J., and De Beenhouwer, J., “Enhancing industrial inspection with efficient edge illumination x-ray phase contrast simulations”, in IEEE EUROCON 2023 -20th International Conference on Smart Technologies, Torino, Italy, 2023.PDF icon eurocon_2023.pdf (8.52 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)
D. Frenkel, Six, N., De Beenhouwer, J., and Sijbers, J., “Tabu-DART: A dynamic update strategy for efficient discrete algebraic reconstruction”, The Visual Computer, vol. 39, pp. 4671–4683, 2023.PDF icon Download paper (2.31 MB)
2024
J. Lüken, Fleischmann, C., Sijbers, J., and De Beenhouwer, J., “AdAPTS: An Adaptive Atom Probe Tomography Simulation Library”, Microscopy and Microanalysis, vol. 30, no. 1. 2024.
P. Paramonov, Francken, N., Renders, J., Iuso, D., Elberfeld, T., De Beenhouwer, J., and Sijbers, J., “CAD-ASTRA: A versatile and efficient mesh projector for X-ray tomography with the ASTRA-toolbox”, Optics Express, vol. 32, no. 3, pp. 3425-3439, 2024.PDF icon Download paper (11.29 MB)
D. Gökbel Keklikoğlu, Francken, N., Huyge, B., Merdan, Z., De Beenhouwer, J., and Sijbers, J., “Dynamic flat field correction in edge illumination imaging”, in SPIE Developments in X-Ray Tomography XV, 2024, vol. 13152.

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