Hostname: page-component-745bb68f8f-l4dxg Total loading time: 0 Render date: 2025-01-07T18:41:27.135Z Has data issue: false hasContentIssue false
  • English
  • Français

Object Segmentation on Cryo-electron Tomography Data

Published online by Cambridge University Press:  22 July 2022

Lan Dang  and
Steven J. Ludtke
Lan Dang*
Affiliation:
Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, US Verna Marrs and McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, US
Steven J. Ludtke
Affiliation:
Verna Marrs and McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, US
*
*Corresponding author: [email protected]

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
From Images to Insights: Working With Large Multi-modal Data in Cell Biological Imaging
Information
Microscopy and Microanalysis , Volume 28 , Supplement S1 , August 2022 , pp. 1514 - 1516
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

Lučić, V., Rigort, A., and Baumeister, W., The Journal of Cell Biology 202 (2013), p. 407-419. doi: 10.1083/jcb.201304193CrossRefGoogle Scholar
Chen, M., et al. , Nature Methods 14, (2017), p. 83-985. doi: 10.1038/nmeth.4405CrossRefGoogle Scholar
Zeng, X. and Xu, M. arXiv.org (2020), arXiv:1911.03044 (accessed Feb 14, 2021).Google Scholar
Moebel, E., Martinez-Sanchez, A., Lamm, L., Nature Methods 18 (2021), p. 1386-1394. doi: 10.1038/s41592-021-01275-4CrossRefGoogle Scholar