Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-23T11:06:31.874Z Has data issue: false hasContentIssue false
  • English
  • Français

Reconstructing the exit wave in high-resolution transmission electron microscopy using machine learning

Published online by Cambridge University Press:  30 July 2021

Jakob Schiøtz ,
Frederik Dahl ,
Matthew Helmi Leth Larsen ,
Christian Kisielowski ,
Stig Helveg ,
Ole Winther  and
Thomas Hansen
Jakob Schiøtz
Affiliation:
Department of Physics, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark
Frederik Dahl
Affiliation:
Department of Physics, Technical University of Denmark, Hovedstaden, Denmark
Matthew Helmi Leth Larsen
Affiliation:
Department of Physics, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark
Christian Kisielowski
Affiliation:
Lawrene Berkeley National Laboratory, The Molecular Foundry and Joint center for Artifical Photosynthesis, University of California, Berkeley, United States
Stig Helveg
Affiliation:
Center for Visualizing Catalytic Processes (VISION), Department of Physics, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark., Kongens Lyngby, Hovedstaden, Denmark
Ole Winther
Affiliation:
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Hovedstaden, Denmark
Thomas Hansen
Affiliation:
TU Nanolab, Technical University of Denmark, Kgs. Lyngby, Hovedstaden, Denmark

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Full System and Workflow Automation for Enabling Big Data and Machine Learning in Electron Microscopy
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 254 - 256
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Kisielowski, C., Frei, H., Specht, P., Sharp, I. D., Haber, J. A., Helveg, S., Adv. Struct. Chem. Imag. 2, 13 (2016). doi:10.1186/s40679-016-0027-9CrossRefGoogle Scholar
de Beeck, M.O., Van Dyck, D., Coene, W., Ultramicroscopy 64, 167–183 (1996). doi:10.1016/0304-3991(96)00058-7Google Scholar
Tiemeijer, P.C., Bischoff, M., Freitag, B., Kisielowski, C., Ultramicroscopy 118, 35–43 (2012). doi:10.1016/j.ultramic.2012.03.019CrossRefGoogle Scholar
4. Ronneberger, O., Fischer, P., Brox, T., in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015, pp. 234–241. Springer, Cham (2015). doi:10.1007/978-3-319-24574-4_28CrossRefGoogle Scholar
Madsen, J., Liu, P., Kling, J., Wagner, J.B., Hansen, T.W., Winther, O., Schiøtz, J., Adv. Theory Simul. 1, 1800037 (2018). doi:10.1002/adts.201800037Google Scholar
Madsen, J., Liu, P., Wagner, J. B., Hansen, T. W., Schiøtz, J., Adv. Struct. Chem. Imag. 3, 14 (2017). doi:10.1186/s40679-017-0047-0CrossRefGoogle Scholar
Madsen, J. and Susi, T., Microsc. Microanal. 26 (Suppl. 2), 448–450 (2020). doi:10.1017/S1431927620014701Google Scholar
Haastrup, S. et al. , 2D Materials 5, 042002 (2018). doi:10.1088/2053-1583/aacfc1 See also https://cmr.fysik.dtu.dk/c2db/c2db.htmlCrossRefGoogle Scholar