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Approaching Real-Time Low-Dose STEM: Image Recovery from Subsampled Measurements via Online Bayesian Dictionary Learning

Published online by Cambridge University Press:  22 July 2022

J. Wells*
Affiliation:
Distributed Algorithms CDT, University of Liverpool, Liverpool, L69 3GH, UK
D. Nicholls
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, L69 3GH, UK
A.W. Robinson
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, L69 3GH, UK
A. Moshtaghpour
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, L69 3GH, UK Rosalind Franklin Institute, Harwell Science & Innovation Campus, Didcot, OX11 0QS, UK
Y. Zheng
Affiliation:
Department of Eye and Vision Science, University of Liverpool, Liverpool, L7 8TX, UK
J. Castagna
Affiliation:
UKRI-STFC Hartree Centre, Daresbury Laboratory, Warrington, WA4 4AD, United Kingdom
N. D. Browning
Affiliation:
Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, L69 3GH, UK Physical & Computational Science, Pacific Northwest National Lab, Richland, WA 99352, USA Sivananthan Laboratories, 590 Territorial Drive, Bolingbrook, IL 60440, USA
*
*Corresponding Author: J. Wells ([email protected])

Abstract

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Type
Microscopy Infrastructures: Architectures, Avenues and Access
Copyright
Copyright © Microscopy Society of America 2022

References

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Sertoglu, S. et al. , 23rd European Signal Processing Conf. (2015), pp. 27712775.Google Scholar
The authors acknowledge funding from ESPRC and Sivananthan Laboratories, IL USA. Dr. Mounib Bahri (University of Liverpool, Liverpool) and Daniel Nicholls2 are recognized for their work in acquiring data used in Figure 1.Google Scholar