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High-Throughput Large Volume SEM Workflow using Sparse Scanning and In-painting Algorithms Inspired by Compressive Sensing

Published online by Cambridge University Press:  04 August 2017

Faysal Boughorbel ,
Pavel Potocek ,
Milos Hovorka ,
Libor Strakos ,
John Mitchels ,
Tomas Vystavel ,
Patrick Trampert ,
Ben Lich  and
Tim Dahmen
Faysal Boughorbel
Affiliation:
Thermo Fisher Scientific, Eindhoven, the Netherlands
Pavel Potocek
Affiliation:
Thermo Fisher Scientific, Eindhoven, the Netherlands
Milos Hovorka
Affiliation:
Thermo Fisher Scientific, Brno, Czech Republic
Libor Strakos
Affiliation:
Thermo Fisher Scientific, Brno, Czech Republic
John Mitchels
Affiliation:
Thermo Fisher Scientific, Brno, Czech Republic
Tomas Vystavel
Affiliation:
Thermo Fisher Scientific, Brno, Czech Republic
Patrick Trampert
Affiliation:
DFKI Gmbh, Saarbriicken, Germany
Ben Lich
Affiliation:
Thermo Fisher Scientific, Eindhoven, the Netherlands
Tim Dahmen
Affiliation:
DFKI Gmbh, Saarbriicken, Germany

Abstract

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Abstract
Information
Microscopy and Microanalysis , Volume 23 , Supplement S1: Proceedings of Microscopy & Microanalysis 2017 , July 2017 , pp. 150 - 151
Copyright
© Microscopy Society of America 2017 

References

[1] Candes, E. J. International Congress of Mathematicians 3 2006). p. 1433.Google Scholar
[2] Anderson, H. A., et al, IS&T/SPIE Electronic Imaging 2013). p. 86570C.Google Scholar
[3] Stevens, A., et al, Microscopy 63–1 2014). p. 41.CrossRefGoogle Scholar
[4] Boughorbel, F., et al, Microsc. Microanal. 19(S2 2013). p. 380.CrossRefGoogle Scholar