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Volumetric Breast Density Estimation on Mammograms Using Breast Tissue Equivalent Phantoms – An Update

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

Abstract

Methods for improving the accuracy of a technique for estimating volumetric breast density are described. A breast tissue-equivalent phantom encompassing a range of thicknesses and compositions of tissue is used to evaluate the sources of error in the technique. The image acquisition parameters that can affect the accuracy of calibration are considered, and sensitivity to these factors is evaluated. The robustness of the technique was tested by obtaining calibration images on 24 mammography machines, at 18 different sites, over a period of 3 years. The ability to use a single calibration on all machines of a given model type was assessed by comparing effective linear attenuation coefficients of fat and fibroglandular tissues, derived from the calibration phantom images obtained from various machines.

Keywords

  • Mammographic Density
  • Beam Hardening
  • Calibration Image
  • Fibroglandular Tissue
  • Mammography Unit

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.

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References

  1. Wolfe, J.N.: Risk for Breast Cancer Development Determined by Mammographic Parenchymal Pattern. Cancer 37, 2486–2492 (1976)

    CrossRef  Google Scholar 

  2. Boyd, N.F., Byng, J.W., Yaffe, M.J.: Quantitative Classification of Mammographic Densities and Breast Cancer Risk: Results From the Canadian National Breast Screening Study. Journal of the National Cancer Institute 87, 670–675 (1995)

    CrossRef  Google Scholar 

  3. Highnam, R., Brady, M., Shepstone, B.: A Representation for Mammographic Image Processing. Medical Image Analysis 1, 1–18 (1996)

    CrossRef  Google Scholar 

  4. Blot, L., Zwiggelaar, R.: A volumetric approach to glandularity estimation in mammography: a feasibility study. Physics in Medicine and Biology 50, 695–708 (2005)

    CrossRef  Google Scholar 

  5. Pawluczyk, O., Augustine, B.J., Yaffe, M.J., Mawdsley, G.E.: A volumetric method for estimation of breast density on digitized screen-film mammograms. Medical Physics 30, 352–364 (2003)

    CrossRef  Google Scholar 

  6. Johns, P.C., Yaffe, M.J.: X-ray Characterisation of normal and neoplastic breast tissues. Physics in Medicine and Biology 32, 675–695 (1987)

    CrossRef  Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Augustine, B.J., Mawdsley, G.E., Boyd, N.F., Yaffe, M.J. (2006). Volumetric Breast Density Estimation on Mammograms Using Breast Tissue Equivalent Phantoms – An Update. 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_3

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  • DOI: https://doi.org/10.1007/11783237_3

  • 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)

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