Deep learning at the edge enables real-time streaming ptychographic imaging.
Nat Commun
; 14(1): 7059, 2023 Nov 03.
Article
em En
| MEDLINE
| ID: mdl-37923741
ABSTRACT
Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Nat Commun
Ano de publicação:
2023
Tipo de documento:
Article