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Refining scan positions in Ptychography through error minimisation and potential application of Machine Learning

Guzzi, F.
•
Kourousias, G.
•
Billè, F.
altro
Carrato, S.
2018
  • journal article

Periodico
JOURNAL OF INSTRUMENTATION
Abstract
Ptychography is an advanced technique whose latest developments have allowed for exceptionally high resolution in X-ray microscopy, as well as new setups that can even be lensless; the spatial resolution has already reached < 5 nm in synchrotron beamlines. Still there are certain demanding requirements such as beam coherence and strong involvement of computational methods that make it a rather difficult technique to implement. In this paper we introduce a computational work-flow aiming at refining the individual probe positions of a ptychography scan. Indeed, the precision of those positions is of high importance as it impacts the reconstruction. Special setups using precise sample stages with nanopositioning and advanced interferometers are important; however, positioning errors still remain a problem for many operating laboratories. This paper examines the Structural Similarity Index as a suitable metric for evaluating the registration in alignment of individually reconstructed probes. Eventually it suggests the use of Machine Learning techniques as future direction in probe alignment. It also presents a new software tool for precise manual alignment and visualization. All the software developed during this research project is provided to the scientific community as open source.
DOI
10.1088/1748-0221/13/06/C06002
WOS
WOS:000434106400002
Archivio
http://hdl.handle.net/11368/2927612
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85049688197
http://iopscience.iop.org/article/10.1088/1748-0221/13/06/C06002/pdf
Diritti
closed access
license:copyright editore
FVG url
https://arts.units.it/request-item?handle=11368/2927612
Soggetti
  • Data processing metho...

  • Analysis and statisti...

Scopus© citazioni
2
Data di acquisizione
Jun 14, 2022
Vedi dettagli
Web of Science© citazioni
4
Data di acquisizione
Mar 23, 2024
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