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Lesion Visibility in Low Dose Tomosynthesis

  • Andrew P. Smith
  • Loren Niklason
  • Baorui Ren
  • Tao Wu
  • Chris Ruth
  • Zhenxue Jing
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)

Abstract

Visibility of lesions in mammography are significantly reduced by the presence of anatomical, or structure, noise. Breast tomosynthesis offers the possibility of reducing this noise. We have compared the detection of low contrast and microcalcification objects with tomosynthesis imaging as a function of dose to full field digital mammography (FFDM) performed at a standard screening dose. The measurements were performed with a variety of phantoms and complex backgrounds. The complex backgrounds greatly reduced object visibility using FFDM; much less so for the tomosynthesis images. In summary, visibility of low contrast objects using tomosynthesis was superior to visibility of these objects in FFDM, even when the tomosynthesis imaging was performed at 1/4 or less of a FFDM dose. Tomosynthesis also showed superior visibility to FFDM for 160-180 micron microcalcifications at 1/2 the FFDM dose.

Keywords

Complex Background Lesion Visibility Structure Noise Standard Breast Full Field Digital Mammography 
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

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    Kopans, D.B.: Breast Imaging, 2nd edn. Lippincott-Raven (1998)Google Scholar
  2. 2.
    Artinis Contrast-Detail Phantom CDMAM 3.4, http://www.artinis.com
  3. 3.
    RMI-180 Contrast-Detail Phantom Gammex RMI, http://www.gammex.com
  4. 4.
    Smith, A.P., Ren, B., Ruth, C., DeFreitas, K., Shaw, I., Jing, Z., Stein, J.A.: Initial Experience with Selenia Full Field Digital Breast Tomosynthesis. In: Pisano, E. (ed.) Proceedings of IWDM 2004, Durham North Carolina (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Andrew P. Smith
    • 1
  • Loren Niklason
    • 1
  • Baorui Ren
    • 1
  • Tao Wu
    • 1
  • Chris Ruth
    • 1
  • Zhenxue Jing
    • 1
  1. 1.Hologic IncBedfordUSA

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