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Linearization of Mammograms Using Parameters Derived from Noise Characteristics

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Information Processing in Medical Imaging (IPMI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3565))

Abstract

A method is proposed for converting digitized mammograms to a normalized representation, in which pixel values are linearly related to the logarithm of x-ray exposure. This method is based on a signal dependent noise model. By exploiting this model unknown parameters of the non-linear response of the film-screen system can be estimated from signal dependence of the image noise. The method was applied to a series of 1372 mammograms acquired over a period of 8 years. Sudden changes in estimated parameters corresponded well with the introduction of new film-screen systems.

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References

  1. Highnam, R.P., Brady, J.M., Shepstone, B.J.: A representation for mammographic image processing. Med Imag Analysis 1, 1–18, 3 (1996)

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Author information

Authors and Affiliations

  1. Department of Radiology, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB, Nijmegen, The Netherlands

    Nico Karssemeijer, Peter R. Snoeren & Wei Zhang

Authors
  1. Nico Karssemeijer
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  2. Peter R. Snoeren
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  3. Wei Zhang
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, The University of Iowa, IA 52242, Iowa City

    Gary E. Christensen

  2. Department of Electrical and Computer Engineering, University of Iowa, IA 52242, Iowa City, USA

    Milan Sonka

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© 2005 Springer-Verlag Berlin Heidelberg

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Cite this paper

Karssemeijer, N., Snoeren, P.R., Zhang, W. (2005). Linearization of Mammograms Using Parameters Derived from Noise Characteristics. In: Christensen, G.E., Sonka, M. (eds) Information Processing in Medical Imaging. IPMI 2005. Lecture Notes in Computer Science, vol 3565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11505730_22

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  • DOI: https://doi.org/10.1007/11505730_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26545-0

  • Online ISBN: 978-3-540-31676-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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