Skip to main content

Breast Density Dependent Computer Aided Detection

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 4046)

Abstract

This paper describes initial steps towards the development of a Computer Aided Detection (CAD) system based on breast density pattern classes. We present evidence that the sensitivity and specificity of such a system will improve if it is developed for, and applied to, specific breast density classes.

Keywords

  • Breast Density
  • Digital Mammography
  • Topographic Representation
  • Mammographic Parenchymal Pattern
  • Breast Pattern

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (Canada)
  • 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Illustrated Breast Imaging Reporting and Data System (BI-RADS). American College of Radiology, 3rd edn. (1998)

    Google Scholar 

  2. Astley, S.: Computer-based detection and prompting of mammographic abnormalities. British Journal of Radiology 77, 194–200 (2004)

    CrossRef  Google Scholar 

  3. Astley, S., Gilbert, F.: Computer-aided detection in mammography. Clinical Radiology 59, 390–399 (2004)

    CrossRef  Google Scholar 

  4. Astley, S., Mistry, T., Boggis, C., Hiller, V.: Should we use humans or a machine to pre-screen mammograms? In: Peitgen, H.-O. (ed.) Sixth International Workshop in Digital Mammography, pp. 476–480. Springer, Heidelberg (2002)

    Google Scholar 

  5. Heath, M., Bowyer, K., Kopans, D., Moore, R., Kegelmeyer, P.: The digital database for screening mammography. In: Yaffe, M. (ed.) Fifth International Workshop on Digital Mammography, pp. 457–460. Medical Physics Publishing (2000)

    Google Scholar 

  6. Highnam, R., Brady, M.: Mammographic Image Analysis. Kluwer Academic Publishers, Dordrecht (1999)

    MATH  Google Scholar 

  7. Hong, B., Brady, M.: A topographic representation for mammogram segmentation. In: MICCAI, vol. 2, pp. 730–737 (2003)

    Google Scholar 

  8. Petroudi, S., Brady, M.: Classification of mammographic texture patterns. In: Seventh International Workshop on Digital Mammography. Medical Physics Publishing (2004)

    Google Scholar 

  9. Petroudi, S., Kadir, T., Brady, M.: Automatic classification of mammographic parenchymal patterns: A statistical approach. In: Proceedings of EMBC, International Conference on Engineering in Medicine and Biology, pp. 798–801. IEEE, Los Alamitos (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Petroudi, S., Brady, M. (2006). Breast Density Dependent Computer Aided Detection. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_5

Download citation

  • DOI: https://doi.org/10.1007/11783237_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35625-7

  • Online ISBN: 978-3-540-35627-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics