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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, 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, 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., 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.
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.
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.
N. J. Forde, O'Donoghue, S., Scanlon, C., Emsell, L., Chaddock, C., Leemans, A., Jeurissen, B., Barker, G. J., Cannon, D. M., Murray, R. M., and others, Structural brain network analysis in families multiply affected with bipolar I disorder, Psychiatry Research: Neuroimaging, vol. 234, pp. 44–51, 2015.
N. J. Forde, Ronan, L., Suckling, J., Scanlon, C., Neary, S., Holleran, L., Leemans, A., Tait, R., Rua, C., Fletcher, P. C., Jeurissen, B., Dodds, C. M., Miller, S. R., Bullmore, E. T., McDonald, C., Nathan, P. J., and Cannon, D. M., Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism., NeuroImage, vol. 90, pp. 280-9, 2014.
N. J. Forde, Scanlon, C., Emsell, L., O'Donoghue, S., Chaddock, C., Leemans, A., Jeurissen, B., Cannon, D. M., Murray, R. M., and McDonald, C., Structural brain network analysis in families multiply affected with bipolar 1 disorder, International Review of Psychosis & Bipolarity. Athens, Greece, 2014.
W. Fortes, Sijbers, J., and Batenburg, K. J., Practical Error Bounds for Binary Tomography, in 1st International Conference on Tomography of Materials and Structures, 2013, pp. 97-100.PDF icon Download paper (165.74 KB)
N. Francken, Paramonov, P., Sijbers, J., and De Beenhouwer, J., Edge Illumination Phase Contrast Simulations Using the OptiX GPU Ray Tracing Engine, 5th International Conference on Tomography of Materials & Structures (ICTMS). 2022.
N. Francken, Sanctorum, J., Renders, J., Paramonov, P., Sijbers, J., and De Beenhouwer, J., A condensed history approach to x-ray dark field effects in edge illumination phase contrast simulations, in 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023.PDF icon Download paper (4.14 MB)
N. Francken, Paramonov, P., Sijbers, J., and De Beenhouwer, J., Enhancing industrial inspection with efficient edge illumination x-ray phase contrast simulations, in IEEE EUROCON 2023 -20th International Conference on Smart Technologies, Torino, Italy, 2023.PDF icon eurocon_2023.pdf (8.52 MB)
N. Francken, Sanctorum, J., Paramonov, P., Sijbers, J., and De Beenhouwer, J., Edge illumination x-ray phase contrast simulations using the CAD-ASTRA toolbox, Optics Express, vol. 32, no. 6, pp. 10005-10021, 2024.
E. Fransen, Dhooghe, R., Van Camp, G., Verhoye, M., Sijbers, J., Reyniers, E., Soriano, P., Kamiguchi, H., Willemsen, R., Koekoek, K. E., Zeeuw, D. C. I., De Deyn, P. P., Van Der Linden, A., Lemmon, V., Kooy, R. F., and Willems, P. J., L1 knockout mice show dilated ventricles, vermis hypoplasia and impaired exploration patterns, Human Molecular Genetics, vol. 7, pp. 999-1009, 1998.PDF icon Download paper (248.02 KB)
D. Frenkel, De Beenhouwer, J., and Sijbers, J., An adaptive probability map for the Discrete Algebraic Reconstruction Technique, in 10th Conference on Industrial Computed Tomography (ICT 2020), 2020, pp. 1-6.
D. Frenkel, De Beenhouwer, J., and Sijbers, J., Tabu-DART: an dynamic update strategy for the Discrete Algebraic Reconstruction Technique based on Tabu-search, in International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2021.
D. Frenkel, Six, N., De Beenhouwer, J., and Sijbers, J., Tabu-DART: A dynamic update strategy for efficient discrete algebraic reconstruction, The Visual Computer, vol. 39, pp. 4671–4683, 2023.PDF icon Download paper (2.31 MB)
M. Froeling, Strijkers, G. J., Jeurissen, B., van der Paardt, M., Stoker, J., Nicolay, K., Nederveen, A. J., and Leemans, A., Fiber architecture of the female pelvic floor: An exploratory investigation using different diffusion MRI tractography algorithms, ISMRM, 19th Scientific Meeting and Exhibition. Montreal, Canada, 2011.
B. Fröhler, Melo, Lda Cunha, Weissenböck, J., Kastner, J., Möller, T., Hege, H. - C., Gröller, E., Sanctorum, J., De Beenhouwer, J., Sijbers, J., and Heinzl, C., Tools for the Analysis of Datasets from X-Ray Computed Tomography based on Talbot-Lau Grating Interferometry, in 9th Conference on Industrial Computed Tomography, Padova, Italy, 2019.PDF icon Download paper (1.07 MB)
B. Fröhler, Elberfeld, T., Möller, T., Weissenböck, J., De Beenhouwer, J., Sijbers, J., Hege, H. - C., Kastner, J., and Heinzl, C., A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science, Computer Graphics Forum, vol. 38, no. 3, pp. 273-283, 2019.

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