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T. Roelandts, Batenburg, K. J., and Sijbers, J., “Localizing DART using the Reconstructed Residual Error”, in 1st International Conference on Tomography of Materials and Structures (ICTMS), Ghent, Belgium, 2013, vol. Book of Abstracts: Talks, pp. 113-116.PDF icon Download full paper (491.53 KB)
T. Roelandts, Batenburg, K. J., den Dekker, A. J., and Sijbers, J., “The reconstructed residual error: A novel segmentation evaluation measure for reconstructed images in tomography”, Computer Vision and Image Understanding, vol. 126, pp. 28-37, 2014.PDF icon Download paper (4.58 MB)
T. Roelandts, Batenburg, K. J., Biermans, E., Kubel, C., Bals, S., and Sijbers, J., “Accurate segmentation of dense nanoparticles by partially discrete electron tomography”, Ultramicroscopy, vol. 114, pp. 96-105, 2012.PDF icon Download paper (1.71 MB)
T. Roelandts, “Local Prior Knowledge in Tomography”, 2013.PDF icon Download PhD thesis (15.6 MB)
T. Roelandts, Batenburg, K. J., Biermans, E., Bals, S., and Sijbers, J., “Partially Discrete Tomography for the Reconstruction of Dense Particles”, 17th International Microscopy Congress (IMC17). Rio de Janeiro, Brazil, p. I7.19, 2010.
E. M. R. Robert, Schmitz, N., Boeren, I., Driessens, T., Herremans, K., De Mey, J., Van de Casteele, E., Beeckman, H., and Koedam, N., “Successive Cambia: A Developmental Oddity or an Adaptive Structure?”, PLoS ONE, vol. 6, no. 1, p. e16558, 2011.
J. Rimpelainen, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., “Deep learning based missing wedge artefact removal for electron tomography”, Microscopy Conference, Berlin, Germany. pp. 660-661, 2019.
R. Riji, Rajan, J., Sijbers, J., and Nair, M. S., “Iterative bilateral filter for Rician noise reduction in MR images”, Signal, Image and Video Processing , 2014.
H. Rezaei, Karami, A., and Scheunders, P., “Hyperspectral and multispectral image fusion based on spectral matching in the shearlet domain”, in IEEE IGARSS 2018, International Geoscience and Remote Sensing Symposium, Valencia, Spain, July 23-27, 2018.
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, 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)
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, “Improved 4DCT reconstruction algorithms for the imaging of foam microstructure formation”, 2024.PDF icon Download thesis (41.42 MB)
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, 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.
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., “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.
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.
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., Scheunders, P., and Chanussot, J., “Deep Blind Unmixing using Minimum Simplex Convolutional Network”, in IEEE International Geoscience and Remote Sensing Symposium, 2022, pp. 28-31.PDF icon misicnet_igarss2022.pdf (1.29 MB)
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 hapkecnnrg.pdf (8.23 MB)

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