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CEM500K – A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning.

Published online by Cambridge University Press:  30 July 2021

Ryan Conrad  and
Kedar Narayan
Ryan Conrad
Affiliation:
Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States
Kedar Narayan
Affiliation:
Frederick National Laboratory for Cancer Research, Frederick, Maryland, United States

Abstract

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Type
From Images to Insights: Working with Large Multi-modal Data in Cell Biological Imaging
Information
Microscopy and Microanalysis , Volume 27 , Supplement S1 , August 2021 , pp. 3036 - 3037
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Buhmann, J. et al. , “Automatic Detection of Synaptic Partners in a Whole-Brain Drosophila EM Dataset,” bioRxiv, p. 2019.12.12.874172, Mar. 2019.Google Scholar
Lichtman, J. W., Pfister, H., and Shavit, N., “The big data challenges of connectomics,” Nat. Neurosci., vol. 17, no. 11, pp. 1448–1454, Oct. 2014.CrossRefGoogle ScholarPubMed
Conrad, R. and Narayan, K., “CEM500K – A large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning,” bioRxiv. bioRxiv, p. 2020.12.11.421792, 11-Dec-2020.Google Scholar