Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-05-21T19:28:22.168Z Has data issue: false hasContentIssue false
  • English
  • Français

Automatic 3D Reconstruction by Deep Learning Neural Networks Using Images Acquired via 4D-STEM Stereo Imaging

Published online by Cambridge University Press:  22 July 2022

Gulnaz Ganeeva ,
Okan Altingövde ,
Quy Ong Khac ,
Francesco Stellacci ,
Pascal Fua ,
Emad Oveisi  and
Cécile Hébert
Gulnaz Ganeeva*
Affiliation:
Electron Spectrometry and Microscopy Laboratory (LSME), EPFL, Lausanne, Switzerland
Okan Altingövde
Affiliation:
Computer Vision Laboratory (CVLab), EPFL, Lausanne, Switzerland
Quy Ong Khac
Affiliation:
Supramolecular Nanomaterials and Interfaces Laboratory (SuNMIL), EPFL, Lausanne, Switzerland
Francesco Stellacci
Affiliation:
Supramolecular Nanomaterials and Interfaces Laboratory (SuNMIL), EPFL, Lausanne, Switzerland
Pascal Fua
Affiliation:
Computer Vision Laboratory (CVLab), EPFL, Lausanne, Switzerland
Emad Oveisi*
Affiliation:
Interdisciplinary Centre for Electron Microscopy (CIME), EPFL, Lausanne, Switzerland
Cécile Hébert*
Affiliation:
Electron Spectrometry and Microscopy Laboratory (LSME), EPFL, Lausanne, Switzerland
*
*Corresponding authors: gulnaz.ganeeva@epfl.ch, emad.oveisi@epfl.ch, cecile.hebert@epfl.ch
*Corresponding authors: gulnaz.ganeeva@epfl.ch, emad.oveisi@epfl.ch, cecile.hebert@epfl.ch
*Corresponding authors: gulnaz.ganeeva@epfl.ch, emad.oveisi@epfl.ch, cecile.hebert@epfl.ch

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
Advanced 3D Imaging and Analysis Methods for New Opportunities in Material Science
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 218 - 220
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

Jácome, A et al. , ‘Three-Dimensional Reconstruction and Quantification of Dislocation Substructures from Transmission Electron Microscopy Stereo Pairs’, Ultramicroscopy, 195 (2018), 157-170, doi: 10.1016/j.ultramic.2018.08.015.CrossRefGoogle Scholar
Oveisi, E, Letouzey, A, De Zanet, S et al. , ‘Stereo-Vision Three-Dimensional Reconstruction of Curvilinear Structures Imaged with a TEM’, Ultramicroscopy, 184 (2018), 116–24, doi: 10.1016/j.ultramic.2017.08.010.CrossRefGoogle Scholar
Oveisi, E, Letouzey, A, Alexander, D T L, et al. , ‘Tilt-Less 3-D Electron Imaging and Reconstruction of Complex Curvilinear Structures’, Scientific Reports, 7.1 (2017), doi: 10.1038/s41598-017-07537-6.CrossRefGoogle ScholarPubMed
Zhu, Y et al. , ‘Towards Bend-Contour-Free Dislocation Imaging via Diffraction Contrast STEM’, Ultramicroscopy, 193. December 2017 (2018), 12–23, doi: 10.1016/j.ultramic.2018.06.001.CrossRefGoogle Scholar
Altingövde, O et al. , ‘3D reconstruction of curvilinear structures with stereo matching deep convolutional neural networks’, Ultramicroscopy, 234 (2022), doi: 10.1016/j.ultramic.2021.113460.CrossRefGoogle ScholarPubMed
Ophus, C, ‘Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM): From Scanning Nanodiffraction to Ptychography and Beyond’, Microsc Microanal. (2019), 563-582. doi: 10.1017/S1431927619000497.CrossRefGoogle ScholarPubMed