Skip to main content
SpringerLink
Log in

Graph-Based Quantification of Astrocytes

  • Conference paper
Bildverarbeitung für die Medizin 2006

Part of the book series: Informatik aktuell ((INFORMAT))

Abstract

Astroglial cells in the central nervous system (CNS) are able to change their morphology and shape after different kinds of stimuli. We have developed a method for the structural description of astrocytes based on their representation as undirected simple graphs. The underlying image processing chain and the algorithm for the graph construction are presented and the graph parameters for the quantitative structural description of the astrocytes are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Franke H, Krügel U, Grosche J, Illes P. Immunoreactivity for glial fibrillary acidic protein and P2 receptor expression on astrocytes in vivo. Drug Development Research 2003;59(1):175–189.

    Article  Google Scholar 

  2. Richardson WH. Bayesian-based iterative method of image restoration. Journal of the Optical Society of America A 1972;62(1):55–59.

    Article  Google Scholar 

  3. Lucy LB. An iterative technique for the rectification of observed distributions. Astronomical Journal 1974;79:745–754.

    Article  Google Scholar 

  4. Gonzalez RC, Woods RE. Digital Image Processing. Prentice Hall; 2002.

    Google Scholar 

  5. Cychosz JM. Efficient Binary Image Thinning using Neighborhood Maps. In: Heckbert Paul, editor. Graphics Gems IV. Academic Press; 1994. p. 465–473.

    Google Scholar 

  6. Dijkstra EW. A note on two problems in connexion with graphs. Numerische Mathematik 1959;1:269–271.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Interdisziplinäres Zentrum für Bioinformatik, Universität Leipzig, 04107, Leipzig

    Ulf-Dietrich Braumann & Jens-Peer Kuska

  2. Rudolf-Boehm-Institut für Pharmakologie und Toxikologie, Universität Leipzig, 04107, Leipzig

    Heike Franke

  3. Institut für Rechtsmedizin, Universität Leipzig, 04103, Leipzig

    Jan Hengstler & Marco Weber

  4. Zentrum für Toxikologie, Universität Leipzig, 04107, Leipzig

    Jan Hengstler

Authors
  1. Ulf-Dietrich Braumann
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Heike Franke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jan Hengstler
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jens-Peer Kuska
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marco Weber
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institut für Medizinische Informatik, Universitätsklinikum Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg

    Heinz Handels  & Jan Ehrhardt  & 

  2. Institut für Medizinische Statistik und Epidemiologie, Technische Universität München, Klinikum rechts der Isar, Ismaninger Straße 22, 81675, München

    Alexander Horsch

  3. Abteilung für Medizinische und Biologische Informatik / H0100, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg

    Hans-Peter Meinzer

  4. Institut für Medizinische Informatik, Biometrie und Epidemiologie Campus Benjamin Franklin, Charité — Universitätsmedizin Berlin, Hindenburgdamm 30, 12000, Berlin

    Thomas Tolxdorff

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Braumann, UD., Franke, H., Hengstler, J., Kuska, JP., Weber, M. (2006). Graph-Based Quantification of Astrocytes. In: Handels, H., Ehrhardt, J., Horsch, A., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2006. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32137-3_77

Download citation

Publish with us

Policies and ethics

Search

Navigation