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Automated Segmentation of HeLa Nuclear Envelope from Electron Microscopy Images

  • Cefa KarabağEmail author
  • Martin L. Jones
  • Christopher J. Peddie
  • Anne E. Weston
  • Lucy M. Collinson
  • Constantino Carlos Reyes-AldasoroEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 894)

Abstract

This paper describes an image-processing pipeline for the automatic segmentation of the nuclear envelope of HeLa cells observed through Electron Microscopy. The pipeline was applied to a 3D stack of 300 images. The intermediate results of neighbouring slices are further combined to improve the final results. Comparison with a hand-segmented ground truth reported Jaccard similarity values between 94–98% on the central slices with a decrease towards the edges of the cell where the structure was considerably more complex. The processing is unsupervised and each 2D slice is processed in about 5–10 s running on a MacBook Pro. No systematic attempt to make the code faster was made. These encouraging results could be further used to provide data for more complex segmentation techniques like Deep Learning, which require a considerable amount of data to train architectures like Convolutional Neural Networks. The code is freely available from https://github.com/reyesaldasoro/HeLa-Cell-Segmentation.

Keywords

Automatic nuclear segmentation HeLa cells Electron microscopy Cell and nuclear shape 

Notes

Acknowledgements

This work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (FC001999), the UK Medical Research Council (FC001999), and the Wellcome Trust (FC001999).

The authors acknowledge the support of the Alan Turing Institute through the Data Study Groups organised by Dr Sebastian Vollmer where initial study of this data was made.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Cefa Karabağ
    • 1
    Email author
  • Martin L. Jones
    • 2
  • Christopher J. Peddie
    • 2
  • Anne E. Weston
    • 2
  • Lucy M. Collinson
    • 2
  • Constantino Carlos Reyes-Aldasoro
    • 1
    Email author
  1. 1.Research Centre for Biomedical Engineering, School of Mathematics, Computer Science and EngineeringCity, University of LondonLondonUK
  2. 2.Electron Microscopy Science Technology PlatformThe Francis Crick InstituteLondonUK

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