Export 1146 results:
Author Type [ Year(Asc)]
B. Fröhler, Elberfeld, T., Möller, T., Hege, H. - C., De Beenhouwer, J., Sijbers, J., Kastner, J., and Heinzl, C., Analysis and Comparison of Algorithms for the Tomographic Reconstruction of Curved Fibers, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.PDF icon Download paper (703.79 KB)
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.
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.
J. Fatermans, den Dekker, A. J., Müller-Caspary, K., Gauquelin, N., Verbeeck, J., and Van Aert, S., Atom column detection from simultaneously acquired ABF and ADF STEM images, Ultramicroscopy, vol. 219, p. 113046, 2020.
J. Fatermans, den Dekker, A. J., Gauquelin, N., Verbeeck, J., and Van Aert, S., Bayesian model selection for atom column detection from ABF-ADF STEM images, Virtual Early Career EMC 2020 (online), Copenhagen, Denmark. 2020.
V. Nguyen, De Beenhouwer, J., Bazrafkan, S., Hoang, A. - T., Van Wassenbergh, S., and Sijbers, J., BeadNet: a network for automated spherical marker detection in radiographs for geometry calibration, in 6th International Conference on Image Formation in X-Ray Computed Tomography, 2020, pp. 518-521.PDF icon Download paper (2.16 MB)
M. Ljubenović, Bazrafkan, S., De Beenhouwer, J., and Sijbers, J., CNN-based Deblurring of Terahertz Images, in Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), 2020, vol. 4, pp. 323-330.PDF icon Download paper (16.31 MB)
G. Araizi-Kanoutas, Geessinck, J., Gauquelin, N., Smit, S., Verbeeck, X. H., Mishra, S. K., Bencok, P., Schlueter, C., Lee, T. - L., Krishnan, D., Fatermans, J., Verbeeck, J., Rijnders, G., Koster, G., and Golden, M. S., Co valence transformation in isopolar LaCoO3/LaTiO3 perovskite heterostructures via interfacial engineering, Phys. Rev. Materials, vol. 4, 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.
J. Morez, Sijbers, J., Vanhevel, F., and Jeurissen, B., Constrained spherical deconvolution of non-spherically sampled diffusion MRI data, Human Brain Mapping, vol. 42, pp. 521–538, 2020.PDF icon Download paper (5.87 MB)
P. Bladt, den Dekker, A. J., Clement, P., Achten, E., and Sijbers, J., The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling, NMR in Biomedicine, vol. 33, no. 12, pp. 1-17, 2020.PDF icon Download paper (16.44 MB)
K. Rafiezadeh Sahi, Ghamisi, P., Rasti, B., Jackisch, R., Scheunders, P., and Gloaguen, R., Data Fusion Using a Multi-Sensor Sparse-Based Clustering Algorithm, Remote Sensing, vol. 12 (23), no. 4007, 2020.
A. Presenti, Bazrafkan, S., Sijbers, J., and De Beenhouwer, J., Deep learning-based 2D-3D sample pose estimation for X-ray 3DCT, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020.
V. Varkarakis, Bazrafkan, S., and Corcoran, P., Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets, Science Direct Elsevier Neural Networks, vol. 121, pp. 101-121, 2020.
S. Jillings, Van Ombergen, A., Tomilovskaya, E., Rumshiskaya, A., Litvinova, L., Nosikova, I., Pechenkova, E., Rukavishnikov, I., Kozlovskaya, I., Sunaert, S., Parizel, P. M., Sinitsyn, V., Petrovichev, V., Laureys, S., P Eulenburg, zu, Sijbers, J., Wuyts, F., and Jeurissen, B., Diffusion MRI reveals macro- and microstructural changes in cosmonauts' brains after long-duration spaceflight, Proc Intl Soc Mag Reson Med 28. p. 4531, 2020.
P. Van Dyck, Billiet, T., Desbuquoit, D., Verdonk, P., Heusdens, C. H., Roelant, E., Sijbers, J., and Froeling, M., Diffusion tensor imaging of the anterior cruciate ligament graft following reconstruction: a longitudinal study, European Radiology, vol. 34, pp. 6673–6684, 2020.
W. Keustermans, Huysmans, T., Schmelzer, B., Sijbers, J., and Dirckx, J. J. J., The effect of nasal shape on the thermal conditioning of inhaled air: Using clinical tomographic data to build a large-scale statistical shape model, Computers in Biology and Medicine, vol. 117, no. 103600, pp. 1-13, 2020.
B. De Samber, De Rycke, R., De Bruyne, M., Kienhuis, M., Sandblad, L., Bohic, S., Cloetens, P., Urban, C., Polerecky, L., and Vincze, L., Effect of sample preparation techniques upon single cell chemical imaging: A practical comparison between synchrotron radiation based X-ray fluorescence (SR-XRF) and Nanoscopic Secondary Ion Mass Spectrometry (nano-SIMS), Analytica Chimica Acta, vol. 1106, pp. 22-32, 2020.PDF icon Download paper (4.01 MB)
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)
M. Siqueira Pinto, Paolella, R., Billiet, T., Van Dyck, P., Guns, P. - J., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., Harmonisation of Brain Diffusion MRI: Concepts and Methods, Frontiers in Neuroscience , vol. 14, pp. 1-17, 2020.PDF icon Download paper (2.61 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.
V. Anania, Billiet, T., Jeurissen, B., Ribbens, A., den Dekker, A. J., and Sijbers, J., Improved voxel-wise quantification of diffusion and kurtosis metrics in the presence of noise and intensity outliers, 12th Annual Meeting ISMRM Benelux Chapter, Arnhem, The Netherlands. 2020.
B. Shafieizargar, Jeurissen, B., den Dekker, A. J., and Sijbers, J., Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept, International Society for Magnetic Resonance in Medicine (ISMRM), vol. 28. 2020.
B. Shafieizargar, Jeurissen, B., den Dekker, A. J., and Sijbers, J., Joint estimation of phase and diffusion tensor parameters from multi-shot k-q-space data: a proof of concept, ISMRM-Benelux, vol. 12. 2020.
Q. Beirinckx, Ramos-Llordén, G., Jeurissen, B., Poot, D. H. J., Parizel, P. M., Verhoye, M., Sijbers, J., and den Dekker, A. J., Joint Maximum Likelihood estimation of motion and T1 parameters from magnetic resonance images in a super-resolution framework: a simulation study, Fundamenta Informaticae, vol. 172, pp. 105–128, 2020.