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J. Renders, Sijbers, J., and De Beenhouwer, J., “Adjoint image warping using multivariate splines with application to 4D-CT”, Medical Physics, vol. 48, no. 10, pp. 6362-6374, 2021.PDF icon Download paper (6.28 MB)
J. Renders, Mancini, L., De Beenhouwer, J., and Sijbers, J., “Direct reconstruction of wet foam from sparse-view, dynamic X-ray CT scans”, Advanced Engineering Materials, vol. 2400957, pp. 1-10, 2024.PDF icon Download paper (2.77 MB)
J. Renders, Nguyen, A. - T., De Beenhouwer, J., and Sijbers, J., “Motion compensating X-ray micro-CT of diamonds in a processing stage”, 31st International Conference on Diamond and Carbon Materials. 2021.PDF icon Download poster (1.04 MB)
J. Renders, De Beenhouwer, J., and Sijbers, J., “Mesh-based reconstruction of dynamic foam images using X-ray CT”, in International Conference on 3D Vision (3DV2021), 2021, pp. 1312-1320.
J. Renders, “Improved 4DCT reconstruction algorithms for the imaging of foam microstructure formation”, 2024.
J. Renders, Jeurissen, B., Nguyen, A. - T., De Beenhouwer, J., and Sijbers, J., “ImWIP: open-source image warping toolbox with adjoints and derivatives”, SoftwareX, vol. 24, p. 101524, 2023.PDF icon Download paper (1 MB)
J. Renders, Shafieizargar, B., Verhoye, M., De Beenhouwer, J., den Dekker, A. J., and Sijbers, J., “DELTA-MRI: Direct deformation Estimation from LongiTudinally Acquired k-space data”, in IEEE International Symposium on Biomedical Imaging, 2023, pp. 1-4.
J. Renders, Sijbers, J., and De Beenhouwer, J., “Adjoint pairs of image warping operators for motion modeling in 4D-CT”, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020.PDF icon Download paper (617.11 KB)
P. Reischig, King, A., Nervo, L., Viganó, N., Guilhem, Y., Palenstijn, W. J., Batenburg, K. J., Preuss, M., and Ludwig, W., “Advances in X-ray diffraction contrast tomography: flexibility in the setup geometry and application to multiphase materials”, Journal of Applied Crystallography, vol. 46, no. 2, pp. 297 - 311, 2013.
Y. D. Reijmer, Leemans, A., Heringa, S. M., Wielaard, I., Jeurissen, B., Koek, H. L., and Biessels, G. J., “Constrained spherical deconvolution based tractography and cognition in Alzheimer’s disease”, International Conference on Alzheimer’s Disease. Paris, France, 2011.
Y. D. Reijmer, Leemans, A., Heringa, S. M., Wielaard, I., Jeurissen, B., Koek, H. L., and Biessels, G. J., “Constrained spherical deconvolution based tractography and cognition in Alzheimer’s disease”, Human Brain Mapping. Québec, Canada, 2011.
Y. D. Reijmer, Leemans, A., Heringa, S. M., Wielaard, I., Jeurissen, B., Koek, H. L., and Biessels, G. J., “Improved sensitivity to cerebral white matter abnormalities in Alzheimer's disease with spherical deconvolution based tractography.”, PloS one, vol. 7, no. 8, p. e44074, 2012.
Y. D. Reijmer, Leemans, A., Heringa, S. M., Wielaard, I., Jeurissen, B., Koek, H. L., and Biessels, G. J., “Constrained spherical deconvolution based tractography and cognition in Alzheimer’s disease”, Congress of the International Society for Vascular, Cognitive and Behavioural Disorders, vol. 5. Lille, France, 2011.
A. J. Rebelo, Scheunders, P., Esler, K. J., and Meire, P., “Evaluating palmiet wetland decline: a comparison of three methods”, Remote Sensing Applications: Society and Environment, vol. 8, pp. 212-223, 2017.
B. Rasti, Koirala, B., and Scheunders, P., “HapkeCNN: Blind nonlinear unmixing for intimate mixtures using Hapke model and convolutional neural network”, IEEE Transactions on Geoscience and Remote Sensing, 2022.PDF icon hapke_cnn.pdf (8.14 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, no. 5522815, 2022.PDF icon misicnet_ieee_tgrs_author_version.pdf (5.57 MB)
B. Rasti and Koirala, B., “Blind Nonlinear Unmixing For Intimate Mixtures Using Hapke Model And CNN”, in Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022, pp. 1-5.PDF icon whispers_2022_hapkecnn.pdf (1.93 MB)
B. Rasti, Koirala, B., and Scheunders, P., “Sparse Unmixing using Deep Convolutional Networks”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 24-27.PDF icon suncnn_igarss2022.pdf (1.03 MB)
B. Rasti, Koirala, B., and Scheunders, P., “Sparse unmixing using deep convolutional networks”, in IGARSS 2022, International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022.
B. Rasti, Koirala, B., and Scheunders, P., “HapkeCNN: Blind Nonlinear Unmixing for Intimate Mixtures Using Hapke Model and Convolutional Neural Network”, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2022.PDF icon nonlinear_unmixing.pdf (8.14 MB)
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., “Spectral Unmixing Using Deep Convolutional Encoder-Decoder”, in 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 3829-3832.PDF icon igarss2021.pdf (659.27 KB)
B. Rasti and Koirala, B., “SUnCNN: Sparse Unmixing Using Unsupervised Convolutional Neural Network”, IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2021.PDF icon ieee_grsl_sundip.pdf (2.34 MB)
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., “How Hyperspectral Image Unmixing and Denoising Can Boost Each Other”, Remote Sensing, vol. 12, no. 1728, 2020.PDF icon remotesensing-12-01728.pdf (2.27 MB)
B. Rasti, Koirala, B., Scheunders, P., Ghamisi, P., and Gloaguen, R., “Boosting Hyperspectral Image Unmixing using Denoising: Four Scenarios”, in IGARSS 2021, International Geoscience and Remote Sensing Symposium, Brussels, Belgium, 2021.
B. Rasti, Koirala, B., Scheunders, P., Ghamisi, P., and Gloaguen, R., “BOOSTING HYPERSPECTRAL IMAGE UNMIXING USING DENOISING: FOUR SCENARIOS”, in IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021.

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