Skip to main content

Cognition Network Technology for Automated Holistic Analysis in Mammography

  • Conference paper
Bildverarbeitung für die Medizin 2007

Abstract

Digital mammography and comprehensive breast cancer screening approaches have led to the generation of a vast amount of image data. Since the visual inspection of a large set of images is expensive and to some extend also subjective, new methods for fully automated mammography image analysis are needed. The Definiens Cognition Network Technology (CNT) solves the image analysis problem by simulating human cognition processes using knowledge based and context dependent processing. It represents processed image data, image processing methods, and image objects and their definitions in a unified model which incorporates elements from semantic networks, description logics and functional programming. We present first steps towards a successful application of this technology on automated detection of masses and calcifications according to the ACR BI-RADS™ standard.

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

Access this chapter

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. Athelogou M. Amobi 2 Abschlussbericht. Bayerische Forschungsstiftung; 2004.

    Google Scholar 

  2. Schaepe A, Urbani M, Leiderer R, Athelogou M. Fraktal hierarchische, prozess-und objektbasierte Bildanalyse. Procs BVM 2003.

    Google Scholar 

  3. Schoenmayer R, Athelogou M, et al. Automatisierte Segmentierung der Seitenventrikel des menschlichen Gehirns aus kernspintomographischen Datensaetzen. Procs BVM 2003; 83–87.

    Google Scholar 

  4. ACR BI-RADS Mammography. Deutsche Roentgengesellschaft, Thieme; 2006.

    Google Scholar 

  5. Sampat M, Markey M, Bovik A. Handbook of Image and Video Processing. Academic Press; 2005. 1195–1217.

    Google Scholar 

  6. Thangavel K, Karnan M, et al. Automatic detection of microcalcification in mammograms: A review. ICGST GVIP 2005;(5).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Schmidt, G. et al. (2007). Cognition Network Technology for Automated Holistic Analysis in Mammography. In: Horsch, A., Deserno, T.M., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2007. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71091-2_57

Download citation

Publish with us

Policies and ethics