Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T18:36:20.675Z Has data issue: false hasContentIssue false
  • English
  • Français

A Framework to Segment Cellular Ultrastructure from 3D Electron Microscopy Images of Human Biopsies

Published online by Cambridge University Press:  22 July 2022

Archana Machireddy ,
Guillaume Thibault ,
Cecilia E. Bueno ,
Hannah R. Smith ,
Jessica L. Riesterer ,
Joe W. Gray  and
Xubo Song
Archana Machireddy*
Affiliation:
Computer Science and Electrical Engineering, Oregon Health and Science University, Portland, OR, USA
Guillaume Thibault
Affiliation:
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
Cecilia E. Bueno
Affiliation:
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
Hannah R. Smith
Affiliation:
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA
Jessica L. Riesterer
Affiliation:
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA Multiscale Microscopy Core, Oregon Health & Science University, Portland, OR, USA Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
Joe W. Gray
Affiliation:
Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
Xubo Song
Affiliation:
Computer Science and Electrical Engineering, Oregon Health and Science University, Portland, OR, USA Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA Department of Medical Informatics and Clinical Epidemiology at Oregon Health and Science University, Portland, OR, USA
*
*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. 1522 - 1525
Check for updates
Copyright
Copyright © Microscopy Society of America 2022

References

Vergara, HM et al. , Cell 184(18) (2021), p. 4819. doi: 10.1016/j.cell.2021.07.017CrossRefGoogle ScholarPubMed
Müller, A A et al. , Journal of Cell Biology 220(2) (2021). doi: 10.1083/jcb.202010039Google Scholar
Heinrich, L et al. , Nature 599(7889) (2021), p. 1.10.1038/s41586-021-03977-3CrossRefGoogle Scholar
de Senneville, BD et al. , Communications biology 4(1) (2021), p. 1. doi: 10.1101/2021.06.15.446847CrossRefGoogle Scholar
Shen, W et al. , Proceedings of the IEEE International Conference on Computer Vision (2017), p. 2391-2400.Google Scholar
Farnebäck, G in “Scandinavian conference on Image analysis”, (Springer, Berlin, Heidelberg), p. 363-370.Google Scholar
This project was carried out with major support from the OHSU SMMART Program, National Institutes of Health (NIH), National Cancer Institute (NCI) Human Tumor Atlas Network (HTAN) Research Center (U2CCA233280), the Prospect Creek Foundation, OHSU Brenden-Colson Center for Pancreatic Care, a NIH/NCI Cancer Systems Biology Consortium Center (U54CA209988), and the Knight Cancer Institute Cancer Center Support Grant (5P30CA69533). Electron microscopy was performed at the OHSU Multiscale Microscopy Core, an OHSU University Shared Resource.Google Scholar