Skip to main content

Determining Correspondence Between Views

  • Chapter
Digital Mammography

Part of the book series: Computational Imaging and Vision ((CIVI,volume 13))

Abstract

Two-view breast screening using cranio-caudal (CC) and medio-lateral oblique (MLO) mammograms has been shown to detect more cancers and lead to less women being recalled to assessment [11], [12] than one-view screening. However, matching signs between two views of the same breast can be a difficult task due to the changing geometry and, crucially, the effects of breast compression. If it were only the geometry that were changing the matching problem would reduce to being one of wide-angle stereo [1]. In this paper we develop a model-based method for finding a curve in the medio-lateral oblique mammogram which corresponds to the potential positions of a point marked in the cranio-caudal mammogram. A more mathematical version of this paper is in [7]. Related work on this problem [10], [9] does not explicitly consider compression. However, work on analysis of stomach x-rays [6] has shown the possibilities of modelling 3D deformations using a model-based approach.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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. O.D. Faugeras. Three-dimensional computer vision: a geometric viewpoint. MIT Press, 1993.

    Google Scholar 

  2. R. P. Highnam and J. M. Brady. Mammographic image processing (In Preparation). Kluwer International, 1998.

    Google Scholar 

  3. R. P. Highnam, J. M. Brady, and B. J. Shepstone. Mammographic image analysis. Euro. I. Radiology, 24:20–32, 1997.

    Article  CAS  Google Scholar 

  4. R. P. Highnam, J. M. Brady, and B. J. Shepstone. Estimating compressed breast thickness. In N. Karssemeijer, editor, 4th International Workshop on Digital Mammography, Nijmegen, Netherlands, 1998. Kluwer Academic Publishers.

    Google Scholar 

  5. R. P. Highnam, B. J. Shepstone, and J. M. Brady. Mammograms at different compression plate widths for the detection of breast cancer. In Radiology and Oncology 91, Work in Progress, page 3. British Institute of Radiology, 1991.

    Google Scholar 

  6. Y. Kita. Elastic-model driven analysis of several views of a deformable cylindrical object. IEEE trans. Pattern Anal. & Mach. Intell, 18, 12:1150–1162, 1996.

    Article  Google Scholar 

  7. Y. Kita, R. P. Highnam, and J. M. Brady. Correspondence between two different views of x-ray mammograms using simulation of breast deformation. In Computer Vision and Pattern Recognition Conference, Santa Barbara, California, USA, June 1998. Computer Society Press.

    Google Scholar 

  8. R. Novak. Transformation of the female breast during compression at mammography with special reference to the importance for localization of a lesion. PhD thesis, Department of Diagnostic Radiology at Lakarhuset and Karolinska Sjukhuset, Sweden, 1989. Acta Radiologica Supplement 371.

    Google Scholar 

  9. E. A. Sickles. Practical solutions to common mammographie problems: tailoring the examination. Amer. I. Roentgenology, 2:333–356, 1988.

    Google Scholar 

  10. W. Spiesberger. Mammogram inspection by computer. IEEE Biomedical Engineering, 26:213–219, 1979.

    Article  CAS  Google Scholar 

  11. N. J. Wald, P. Murphy, and P. Major et al. UKCCCR multicentre randomized controlled trial of one and two view mammography in breast cancer screening. British Medical lournal, 311:1189–1193, 1995.

    Article  CAS  Google Scholar 

  12. K. C. Young, M. G. Wallis, R. G. Blanks, and S. M. Moss. Influence on number of views and mammographie film density on the detection of invasive cancers: results from the NHS breast screening programme. British I. Radiology, 70:482–488, 1997.

    CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Highnam, R., Kita, Y., Brady, M., Shepstone, B., English, R. (1998). Determining Correspondence Between Views. In: Karssemeijer, N., Thijssen, M., Hendriks, J., van Erning, L. (eds) Digital Mammography. Computational Imaging and Vision, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5318-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-94-011-5318-8_18

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-6234-3

  • Online ISBN: 978-94-011-5318-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics