Publications

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2023
L. F. Alves Pereira, De Beenhouwer, J., and Sijbers, J., “The Deep Steerable Convolutional Framelet Network for Suppressing Directional Artifacts in X-ray Tomosynthesis”, in 31st European Signal Processing Conference, EUSIPCO, 2023.
L. F. Alves Pereira, De Beenhouwer, J., and Sijbers, J., “Sparse-view Medical Tomosynthesis via Mixed Scale Dense Convolutional Framelet Networks”, in IEEE International Symposium on Biomedical Imaging (ISBI), 2023, pp. 880-884.
2022
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Inze, D., and Scheunders, P., “Analysis of Plant Stress Response Using Hyperspectral Imaging and Kernel Ridge Regression”, in 11th International Conference on Robotics, Vision, Signal Processing and Power Applications, Singapore, 2022, vol. 829.
A. Presenti, Liang, Z., Alves Pereira, L. F., Sijbers, J., and De Beenhouwer, J., “CNN-based pose estimation from a single X-ray projection for 3D inspection of manufactured objects”, in 11th Conference on Industrial Computed Tomography, 2022.
2021
A. Presenti, Liang, Z., Alves Pereira, L. F., Sijbers, J., and De Beenhouwer, J., “CNN-based Pose Estimation of Manufactured Objects During Inline X-ray Inspection”, in 2021 IEEE 6th International Forum on Research and Technology for Society and Industry (RTSI), 2021.
L. F. Alves Pereira, Van Nieuwenhove, V., De Beenhouwer, J., and Sijbers, J., “A Deep Convolutional Framelet Network based on Tight Steerable Wavelet: application to sparse-view medical tomosynthesis”, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
2020
B. Auer, Kalluri, K., Abayazeed, A. H., De Beenhouwer, J., Zeraatkar, N., Lindsay, C., Momsen, N., R. Richards, G., May, M., Kupinski, M. A., Kuo, P. H., Furenlid, L. R., and King, M. A., “Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020), 2020.
B. Auer, Kalluri, K., Abayazeed, A. H., De Beenhouwer, J., Zeraatkar, N., Lindsay, C., Momsen, N., R. Richards, G., May, M., Kupinski, M. A., Kuo, P. H., Furenlid, L. R., and King, M. A., “Aperture size selection for improved brain tumor detection and quantification in multi-pinhole 123I-CLINDE SPECT imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Boston, USA (2020), 2020.
T. Peeters, Vleugels, J., Verwulgen, S., Danckaers, F., Huysmans, T., Sijbers, J., and De Bruyne, G., “A Comparative Study Between Three Measurement Methods to Predict 3D Body Dimensions Using Shape Modelling”, in Advances in Additive Manufacturing, Modeling Systems and 3D Prototyping, Cham, 2020, vol. 975, pp. 464–470.
L. F. Alves Pereira, De Beenhouwer, J., Kastner, J., and Sijbers, J., “Extreme Sparse X-ray Computed Laminography Via Convolutional Neural Networks”, in ICTAI 2020, 2020.PDF icon Download paper (2.5 MB)
2019
S. Verwulgen, Lacko, D., Justine, H., Kustermans, S., Moons, S., Thys, F., Zelck, S., Vaes, K., Huysmans, T., Vleugels, J., and Truijen, S., “Determining Comfortable Pressure Ranges for Wearable EEG Headsets”, in Advances in Human Factors in Wearable Technologies and Game Design, Cham, 2019, pp. 11–19.
B. Auer, Zeraatkar, N., De Beenhouwer, J., Kalluri, K., Kuo, P. H., Furenlid, L. R., and King, M. A., “Investigation of a Monte Carlo simulation and an analytic-based approach for modeling the system response for clinical I-123 brain SPECT imaging”, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, vol. 11072, pp. 187 – 190.
V. Nguyen, De Beenhouwer, J., Sanctorum, J., Van Wassenbergh, S., Aerts, P., Dirckx, J. J. J., and Sijbers, J., “A low-cost and easy-to-use phantom for cone-beam geometry calibration of a tomographic X-ray system”, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.93 MB)
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., and Sijbers, J., “Moving Statistical Body Shape Models Using Blender”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 28–38.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., and Sijbers, J., “Moving Statistical Body Shape Models Using Blender”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 28–38.
B. Auer, De Beenhouwer, J., Zeraatkar, N., Kuo, P. H., Furenlid, L. R., and King, M. A., “Preliminary investigation of attenuation and scatter correction strategies for a next-generation SPECT system dedicated to quantitative clinical brain imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Manchester, UK, 2019.
V. Andrejchenko, Zahiri, Z., Heylen, R., and Scheunders, P., “A spectral mixing model accounting for multiple reflections and shadow”, in IGARSS 2019, International Geoscience and Remote Sensing Symposium, Yokohama, Japan, 2019, pp. 286-289.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., Sijbers, J., and Andreoni, G., “Using 3D Statistical Shape Models for Designing Smart Clothing”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 18–27.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., Sijbers, J., and Andreoni, G., “Using 3D Statistical Shape Models for Designing Smart Clothing”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 18–27.
S. Scataglini, Danckaers, F., Haelterman, R., Huysmans, T., Sijbers, J., and Andreoni, G., “Using 3D Statistical Shape Models for Designing Smart Clothing”, in Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), Cham, 2019, pp. 18–27.
2018
J. Weissenböck, Arikan, M., Salaberger, D., Kastner, J., De Beenhouwer, J., Sijbers, J., Rauchenzauner, S., Raab-Wernig, T., Gröller, E., and Heinzl, C., “Comparative Visualization of Orientation Tensors in Fiber-Reinforced Polymers”, in 8th Conference on Industrial Computed Tomography, Wels, Austria , 2018.PDF icon Download paper (1.03 MB)
M. Shahrimie Asaari, Mertens, S., Dhondt, S., Wuyts, N., and Scheunders, P., “Detection of plant responses to drought using close-range hyperspectral imaging in a high-throughput phenotyping platform”, in IEEE Whispers 2018, Workshop on Hyperspectral Image and Signal Processing, Amsterdam, 23-26 September , 2018.
V. Andrejchenko, Heylen, R., Liao, W., Philips, W., and Scheunders, P., “MRF-based decision fusion for hyperspectral image classification”, in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 2018.
B. Auer, Könik, A., Fromme, T. J., Kalluri, K., De Beenhouwer, J., Zubal, G. I., Furenlid, L. R., and King, M. A., “Preliminary evaluation of surface mesh modeling of system geometry, anatomy phantom, and source activity for GATE simulations”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.
B. Auer, De Beenhouwer, J., Fromme, T. J., Kalluri, K., Goding, J. C., Zubal, G. I., Furenlid, L. R., and King, M. A., “Preliminary investigation of design parameters of an innovative multi- pinhole system dedicated to brain SPECT imaging”, in IEEE Nuclear Science Symposium and Medical Imaging Conference, Sydney, Australia, 2018.

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