Automatic 3D Reconstruction by Deep Learning Neural Networks Using Images Acquired via 4D-STEM Stereo Imaging-Reference-Cited by-同舟云学术

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

Published:2022-08-01 Issue:S1 Volume:28 Page:218-220
ISSN:1435-8115
Container-title:Microscopy and Microanalysis
language:en
Short-container-title:

Author:

Ganeeva Gulnaz¹,Altingövde Okan²,Khac Quy Ong³,Stellacci Francesco³,Fua Pascal²,Oveisi Emad⁴,Hébert Cécile¹

Affiliation:

1. EPFL Electron Spectrometry and Microscopy Laboratory (LSME), , Lausanne, Switzerland

2. EPFL Computer Vision Laboratory (CVLab), , Lausanne, Switzerland

3. EPFL Supramolecular Nanomaterials and Interfaces Laboratory (SuNMIL), , Lausanne, Switzerland

4. EPFL Interdisciplinary Centre for Electron Microscopy (CIME), , Lausanne, Switzerland

Publisher

Oxford University Press (OUP)

Subject

Instrumentation

Link

https://academic.oup.com/mam/article-pdf/28/S1/218/48822726/mam0218.pdf

Reference6 articles.

1. Three-Dimensional Reconstruction and Quantification of Dislocation Substructures from Transmission Electron Microscopy Stereo Pairs;Jácome;Ultramicroscopy,2018

2. Stereo-Vision Three-Dimensional Reconstruction of Curvilinear Structures Imaged with a TEM;Oveisi;Ultramicroscopy,2018

3. Tilt-Less 3-D Electron Imaging and Reconstruction of Complex Curvilinear Structures;Oveisi;Scientific Reports,2017

4. Towards Bend-Contour-Free Dislocation Imaging via Diffraction Contrast STEM;Zhu,2018

5. 3D reconstruction of curvilinear structures with stereo matching deep convolutional neural networks;Altingövde;Ultramicroscopy,2022

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1. Quantitative Scanning Transmission Electron Microscopy for Materials Science: Imaging, Diffraction, Spectroscopy, and Tomography;Annual Review of Materials Research;2023-07-03

2. The Use of Fuzzy Information and Linguistic Model in the Virtual Reconstruction of Defensive Borders in the 17th and 18th Centuries;Advances in Intelligent Systems and Computing;2023

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