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Electron Microscopy

Deep learning based missing wedge artefact removal for electron tomography

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.

Quantifying 3D atomic structures of nanomaterials and their dynamics using model-based scanning transmission electron microscopy

S. Van Aert, De wael, A., Fatermans, J., Lobato, I., De Backer, A., Jones, L., den Dekker, A. J., and Nellist, P. D., “Quantifying 3D atomic structures of nanomaterials and their dynamics using model-based scanning transmission electron microscopy”, Spring Meeting of the EMRS, Nice, France. 2019.

Strategies for quantifying 3D atomic structures of nanomaterials and their dynamics using dose-efficient ADF STEM

S. Van Aert, De wael, A., Fatermans, J., Lobato, I., De Backer, A., Jones, L., den Dekker, A. J., and Nellist, P. D., “Strategies for quantifying 3D atomic structures of nanomaterials and their dynamics using dose-efficient ADF STEM”, PICO2019, Vaalsbroek, The Netherlands. 2019.

Maximising dose efficiency in quantitative STEM to reveal the 3D atomic structure of nanomaterials

S. Van Aert, Fatermans, J., De Backer, A., van den Bos, K. H. W., O'Leary, C. M., Müller-Caspary, K., Jones, L., Lobato, I., Béché, A., den Dekker, A. J., Bals, S., and Nellist, P. D., “Maximising dose efficiency in quantitative STEM to reveal the 3D atomic structure of nanomaterials”, IMC19, Sydney, Australia. 2018.

Optimal statistical experiment design for detecting and locating light atoms using quantitative high resolution (scanning) transmission electron microscopy

J. Gonnissen, “Optimal statistical experiment design for detecting and locating light atoms using quantitative high resolution (scanning) transmission electron microscopy”, 2017.

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The maximum a posteriori probability rule for atom column detection from HAADF STEM images

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.

The maximum a posteriori probability rule to detect single atoms from low signal-to-noise ratio scanning transmission electron microscopy images

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.

Bayesian analysis of noisy scanning transmission electron microscopy images for single atom detection

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.

Detection of atomic columns from noisy STEM images

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.

Bayesian model-order selection in electron microscopy to detect atomic columns in noisy images

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.

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