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Multi-order Scaling of High-throughput Transmission Electron Microscopy

Published online by Cambridge University Press:  05 August 2019

Christopher S. Own*
Affiliation:
Voxa, Seattle, WAUSA.
Theodore DeRego
Affiliation:
Voxa, Seattle, WAUSA.
Lawrence S. Own
Affiliation:
Voxa, Seattle, WAUSA.
Gerward Weppelman
Affiliation:
Voxa, Seattle, WAUSA.
Adrian A. Wanner
Affiliation:
Princeton Neuroscience Institute, NJ, USA.
Sebastian Ströh
Affiliation:
Princeton Neuroscience Institute, NJ, USA.
Eric Hammerschmith
Affiliation:
Princeton Neuroscience Institute, NJ, USA.
Ashwin Vishwanathan
Affiliation:
Princeton Neuroscience Institute, NJ, USA.
H. Sebastian Seung
Affiliation:
Princeton Neuroscience Institute, NJ, USA.
*
*Corresponding author: csown@voxa.co
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Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Multi-Modal, Large-Scale and 3D Correlative Microscopy
Copyright
Copyright © Microscopy Society of America 2019 

References

[1]Kubota, Y, Sohn, J, and Kawaguchi, Y., Frontiers in Neural Circuits 12 (2018), Article 98.CrossRefGoogle Scholar
[2]Micheva, KD, and Smith, SJ, Neuron 55 (2007), p. 25-36CrossRefGoogle Scholar
[3]Own, CS, et al. , Microscopy & Microanalysis 21 (2015), p. 9.CrossRefGoogle Scholar
[4]Own, CS, et al. , Microscopy & Microanalysis 23 (2017), p. 32.CrossRefGoogle Scholar
[6]This work was supported by Voxa, Simons Foundation, National Institutes of Health, and CV Starr Fellowship of the Princeton Neuroscience Institute. Voxa innovations are patented and patent pending.Google Scholar
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Multi-order Scaling of High-throughput Transmission Electron Microscopy
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