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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, 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.
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.
U. Roine, Salmi, J., Roine, T., Nieminen-von Wendt, T., Leppämäki, S., Rintahaka, P., Tani, P., Leemans, A., and Sams, M., Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome, Molecular Autism, vol. 6, p. 4, 2015.PDF icon Download paper (1.75 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Leemans, A., and Sijbers, J., Informed constrained spherical deconvolution (iCSD), Medical Image Analysis, vol. 24, no. 1, pp. 269–281, 2015.PDF icon Download accepted manuscript (987.95 KB)
U. Roine, Roine, T., Salmi, J., Nieminen-von Wendt, T., Tani, P., Leppämäki, S., Rintahaka, P., Caeyenberghs, K., Leemans, A., and Sams, M., Abnormal wiring of the connectome in adults with high-functioning autism spectrum disorder, Molecular Autism, vol. 6, p. 65, 2015.PDF icon Download paper (1.64 MB)
U. Roine, Roine, T., Salmi, J., Nieminen-von Wendt, T., Leppämäki, S., Rintahaka, P., Tani, P., Leemans, A., and Sams, M., Increased coherence of white matter fiber tract organization in adults with Asperger syndrome: A diffusion tensor imaging study, Autism Research, vol. 6, no. 6, pp. 642-650, 2013.PDF icon Download paper (1.2 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., Isotropic non-white matter partial volume effects in constrained spherical deconvolution, Information-based methods for neuroimaging: analyzing structure, function and dynamics, p. 112, 2015.
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Leemans, A., Philips, W., and Sijbers, J., Isotropic non-white matter partial volume effects in constrained spherical deconvolution, Frontiers in Neuroinformatics, vol. 8, pp. 1-9, 2014.PDF icon Download paper (1.79 MB)
T. Roine, Jeurissen, B., Perrone, D., Aelterman, J., Philips, W., Sijbers, J., and Leemans, A., Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks, Medical Image Analysis, vol. 52, pp. 56-67, 2019.PDF icon Download paper (4.03 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, 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)
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, 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)
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.
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, vol. 60, pp. 1-15, 2022.PDF icon nonlinear_unmixing.pdf (8.14 MB)
B. Rasti, Koirala, B., Scheunders, P., and Ghamisi, P., UnDIP: hyperspectral unmixing using deep image prior, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-15, 2021.PDF icon manuscript.pdf (13 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, 2022.PDF icon hapke_cnn.pdf (8.14 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, Scheunders, P., Ghesami, P., Licciardi, G., and Chanussot, J., Noise reduction in hyperspectral imagery: overview and application, Remote Sensing , vol. 10, no. 3, p. 482, 2018.
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., 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. Rast, 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 ieee_journal_misicnet.pdf (11.02 MB)

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