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Converting One Set of Mammograms to Simulate a Range of Detector Imaging Characteristics for Observer Studies

  • Alistair Mackenzie
  • David R. Dance
  • Oliver Diaz
  • Annabel Barnard
  • Kenneth C. Young
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7361)

Abstract

A methodology for adjusting mammographic images taken on a given imaging system to simulate their appearance if taken on a different system for use in observer studies is presented. The process involves adjusting the image sharpness and noise, which takes into account the detector, breast thickness, and beam quality. The method has been tested by converting images acquired using an a-Se detector of a CDMAM test object and ‘Rachel’ anthropomorphic breast phantom. They were degraded to appear as if acquired using a computed radiography (CR) detector. Good agreement was achieved in the resulting threshold gold thickness for the simulated CR images with measured real values for CDMAM images. Power spectra comparisons of real and simulated images of the ‘Rachel’ phantom agree with an average difference of 4%. This tool in conjunction with observer studies can be used to understand the effects of the detector characteristics on cancer detection in mammography.

Keywords

simulation noise power spectra modulation transfer function 

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References

  1. 1.
    Mackenzie, A., Dance, D.R., Workman, A., Yip, M., Wells, K., Young, K.C.: Development and validation of a method for converting images to appear with noise and sharpness characteristics of a different detector and X-ray system. Med. Phys. 39, 2721–2734 (2012)CrossRefGoogle Scholar
  2. 2.
    Boone, J.M., Fewell, T.R., Jennings, R.J.: Molybdenum, rhodium, and tungsten anode spectral models using interpolating polynomials with application to mammography. Med. Phys. 24, 1863–1874 (1997)CrossRefGoogle Scholar
  3. 3.
    Berger, M.J., Hubbell, J.H., Seltzer, S.M., Chang, J., Coursey, J.S., et al.: XCOM: Photon cross sections database. NIST Standard Reference Database 8, 87-3597 (1998)Google Scholar
  4. 4.
    Dance, D.R., Skinner, C.L., Young, K.C., Beckett, J.R., Kotre, C.J.: Additional factors for the estimation of mean glandular breast dose using the UK mammography dosimetry protocol. Phys. Med. Biol. 45, 3225–3240 (2000)CrossRefGoogle Scholar
  5. 5.
    Young, K.C., Alsager, A., Oduko, J.M., Bosmans, H., Verbrugge, B., et al.: Evaluation of software for reading images of the CDMAM test object to assess digital mammography systems. In: Proc. SPIE, vol. 6913, pp. 69131C-1–69131C-11 (2008)Google Scholar
  6. 6.
    Warren, L.M., Mackenzie, A., Cooke, J., Given-Wilson, R., Wallis, M.G., et al.: Mammographic calcification cluster detection and threshold gold thickness measurements. In: Proc. SPIE, vol. 8313, p. 83130J (2012)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alistair Mackenzie
    • 1
    • 2
  • David R. Dance
    • 1
    • 2
  • Oliver Diaz
    • 3
  • Annabel Barnard
    • 1
    • 2
  • Kenneth C. Young
    • 1
    • 2
  1. 1.Royal Surrey County HospitalNational Coordinating Centre for the Physics of MammographyGuildfordUK
  2. 2.Department of PhysicsUniversity of SurreyGuildfordUK
  3. 3.Centre for Vision, Speech and Signal Processing, Faculty of Engineering and Physical SciencesUniversity of SurreyGuildfordUK

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