Publications

Export 1316 results:
[ Author(Asc)] Type Year
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F
N. J. Forde, Ellison-Wright, I., Nathan, P. J., Zaman, R., Dudas, R., Agius, M., Fernandez-Egea, E., Leemans, A., Jeurissen, B., Scanlon, C., McDonald, C., and Cannon, D. M., “White Matter Tract Deficits in Schizophrenia”, Neuroscience Ireland Conference, vol. 7. Dublin, Ireland, 2011.
P. Fillard, Descoteaux, M., Goh, A., Gouttard, S., Jeurissen, B., Malcolm, J., Ramirez-Manzanares, A., Reisert, M., Sakaie, K., Tensaouti, F., Yo, T. - S., Mangin, J. - F., and Poupon, C., “Quantitative Evaluation of 10 Tractography Algorithms on a Realistic Diffusion MR Phantom”, NeuroImage, vol. 56, pp. 220-234, 2011.
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.
J. Fatermans, den Dekker, A. J., Müller-Caspary, K., Lobato, I., O'Leary, C. M., Nellist, P. D., and Van Aert, S., “Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images”, Phys. Rev. Lett., vol. 121, p. 056101, 2018.
J. Fatermans, “Quantitative atom detection from atomic-resolution transmission electron microscopy images”, 2019.PDF icon Download thesis (29.73 MB)
J. Fatermans, den Dekker, A. J., Müller-Caspary, K., Lobato, I., and Van Aert, S., “Bayesian analysis of noisy scanning transmission electron microscopy images for single atom detection”, SCANDEM 2018, Technical University of Denmark, Kgs. Lyngby, Denmark. p. 95, 2018.
J. Fatermans, De Backer, A., den Dekker, A. J., and Van Aert, S., “Chapter Seven - Image-quality evaluation and model selection with maximum a posteriori probability”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
J. Fatermans, den Dekker, A. J., and Van Aert, S., “Atom detection from electron microscopy images”, RBSM 2019, Louvain-la-Neuve, Belgium. p. 15, 2019.
J. Fatermans, Müller-Caspary, K., den Dekker, A. J., and Van Aert, S., “Detection of atomic columns from noisy STEM images”, Microscopy Conference 2017 (MC 2017), Lausanne, Switzerland. pp. 445-446, 2017.
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., O'Leary, C. M., Nellist, P. D., and Van Aert, S., “Atom column detection from STEM images using the maximum a posteriori probability rule”, MC 2019, Berlin, Germany. 2019.
J. Fatermans, Van Aert, S., and den Dekker, A. J., “The maximum a posteriori probability rule for atom column detection from HAADF STEM images”, Ultramicroscopy, vol. 201, pp. 81-91, 2019.
J. Fatermans, Van Aert, S., and den Dekker, A. J., “Bayesian model-order selection in electron microscopy to detect atomic columns in noisy images”, RBSM 2016, Brussels, Belgium. p. 53, 2016.
J. Fatermans, De Backer, A., den Dekker, A. J., and Van Aert, S., “Chapter Six - Atom column detection”, in Advances in Imaging and Electron Physics, vol. 217, Science Direct Elsevier, 2021.
J. Fatermans, den Dekker, A. J., Müller-Caspary, K., Lobato, I., and Van Aert, S., “The maximum a posteriori probability rule to detect single atoms from low signal-to-noise ratio scanning transmission electron microscopy images”, IMC19, Sydney, Australia. 2018.
E
L. Emsell, Leemans, A., Langan, C., Van Hecke, W., Barker, G. J., McCarthy, P., Jeurissen, B., Sijbers, J., Sunaert, S., Cannon, D. M., and McDonald, C., “Limbic and callosal white matter changes in euthymic bipolar I disorder: an advanced diffusion MRI tractography study”, Biologicial Psychiatry, vol. 73, no. 2, pp. 194-201, 2013.
T. Elberfeld, Fröhler, B., Heinzl, C., Sijbers, J., and De Beenhouwer, J., “cuPARE: Parametric Reconstruction of Curved Fibres from Glass fibre-reinforced Composites”, Nondestructive Testing and Evaluation, 2022.PDF icon Download paper (9.66 MB)
T. Elberfeld, “Parametric Fiber Analysis for Glass Fiber-reinforced Composite Tomographic Images”, 2023.PDF icon Download PhD thesis (35.09 MB)
T. Elberfeld, De Beenhouwer, J., and Sijbers, J., “Fiber assignment by continuous tracking for parametric fiber reinforced polymer reconstruction”, in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D), 2019, vol. 11072.PDF icon Download paper (5.15 MB)
T. Elberfeld, De Beenhouwer, J., den Dekker, A. J., Heinzl, C., and Sijbers, J., “Parametric Reconstruction of Advanced Glass Fiber-reinforced Polymer Composites from X-ray Images”, 8th Conference on Industrial Computed Tomography. Wels, Austria, 2018.PDF icon Download paper (636.09 KB)
T. Elberfeld, De Beenhouwer, J., den Dekker, A. J., Heinzl, C., and Sijbers, J., “Parametric Reconstruction of Glass Fiber-reinforced Polymer Composites from X-ray Projection Data - A Simulation Study”, Journal of Nondestructive Evaluation, vol. 37, no. 62, pp. 1573-4862, 2018.
T. Elberfeld, Bazrafkan, S., De Beenhouwer, J., and Sijbers, J., “Mixed-Scale Dense Convolutional Neural Network based Improvement of Glass Fiber-reinforced Composite CT Images”, 4th International Conference on Tomography of Materials & Structures. 2019.
D
A. Duijster, De Backer, S., and Scheunders, P., “Wavelet-based Multispectral Image Restoration”, in IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008, vol. 3, pp. 79-82.
A. Duijster, De Backer, S., and Scheunders, P., “Wavelet-based Multicomponent Image Restoration”, in Wavelet Applications in Industrial Processing V, part of SPIE Optics East, Boston, MA, United States, September 9-12, 2007, vol. 6763.
A. Duijster, Scheunders, P., and De Backer, S., “Wavelet-Based EM Algorithm for Multispectral-Image Restoration”, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3892-3898, 2009.

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