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MammoAid

  • Nanying LiangEmail author
  • Srinath Sridharan
  • James Mah Tzia Liang
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 48)

Abstract

Breast cancer is the most commonly diagnosed cancer in females worldwide. At present, mammography is the best non-intrusive way for breast cancer detection. It is well established that mammographic density (MD) is an independent and robust factor for breast cancer risk assessment [1]. Breast cancer risk assessment is useful in personalizing mammography screening and in helping patients make informed decision about the ways of reducing breast cancer risk. Currently, MD estimation is done manually or semiautomatically (Cumulus [2], for example). This leads to intra- and inter-reader variations in MD estimation, and hence limits its application in breast cancer risk assessment.

Keywords

mammographic density segmentation artificial intelligence breast cancer 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nanying Liang
    • 1
    Email author
  • Srinath Sridharan
    • 1
  • James Mah Tzia Liang
    • 1
  1. 1.Institute for Infocomm Research, Agency for Science, Technology and ResearchSingaporeSingapore

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