Skip to main content

Enhanced Identification of different types of Microcalcifcations using the wavelet transform Method

  • Conference paper
Digital Mammography
  • 198 Accesses

Abstract

Microcalcifications and Clustered microcalcifications are known to be the first sign of a development of an eventual cancer. They appear as small and bright region with irregular shape in the breast. Their diversity in their shape, their directionality, their size and localisation in a dense mammogram confirm the major difficulty of their detection. The aim of our scheme is the deĀ¬velopment of a method for the detection of all type of microcalcifications. The wavelet transform has recently emerged as a powerful tool for non-stationary signal analysis, its discrete version is closely related to filter banks. Also, multiresolution signal analysis has been used in image processing. This paper uses the relationship between these two techniques to provide a method of enhancing all type of microcalcifications. The digital mammograms are first processed by the wavelet transform with its multiresolution analysis. The enhancement of the microcalcifications is assured for each different type by using for an appropriate wavelet coefficients.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Nishikawa RM, Jiang Y, Giger ML et al ā€œPerformance of Automated CAD schemes for the Detection and Classification of Clustered Microcalcifications.ā€ In: Gale AG, Ashley SM, Dance DR, Cairns AY eds. Digital Mammography. Amsterdam, Elsevier Science, 1994; pp. 13ā€“20.

    Google ScholarĀ 

  2. H.Chan, K. Doi, S. Galhotra, CJ. Vyborny, H. MacMahon, PM Jokich ā€œImage feature analysis and computer-aided disgnosis in digital radiography. 1. Automated detection of mi- crocalcifications in mammography ā€ Med Phys 1987; 14: 538ā€“548.

    ArticleĀ  PubMedĀ  CASĀ  Google ScholarĀ 

  3. H. Yoshida, K. Doi, and R. M. Nishikawa, K. Muto, and M. Tsuda ā€œApplication of the wavelet transform to automated detection of clustered microcalcifications in digital mamĀ¬mograms.ā€ Acad. Reports of Tokyo Institute of Polytecnics 16: 24ā€“37, 1994.

    Google ScholarĀ 

  4. M.L. Gal, G. Ghavanne, D. Pellier ā€œValeur diagnostique des microcalcifications groupĆ©es dĆ©couvertes par mammographic (Ć  propos de 227 cas avec vĆ©rification histologique et sans tumeur palpableā€ Cancer (Paris) Masson, 71(1):57 Bull, 1994.

    Google ScholarĀ 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

Ā© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Oussena, B., Griche, A., Bounatiro, K., Henni, A., Alt, R. (2003). Enhanced Identification of different types of Microcalcifcations using the wavelet transform Method. In: Peitgen, HO. (eds) Digital Mammography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59327-7_50

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-59327-7_50

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-63936-4

  • Online ISBN: 978-3-642-59327-7

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics