• DocumentCode
    3242802
  • Title

    Fuzzy logic in digital mammography: analysis of lobulation

  • Author

    Kovalerchuk, Boris ; Triantaphyllou, Evangelos ; Ruiz, James F. ; Clayton, J.

  • Author_Institution
    Dept. of Ind. Eng., Louisiana State Univ., Baton Rouge, LA, USA
  • Volume
    3
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    1726
  • Abstract
    This paper illustrates how the fuzzy logic approach can be used to formalize the American College of Radiology (ACR) breast imaging reporting lexicon. In current practice radiologists make a relatively subjective determination for many terms from the lexicon related to breast cancer diagnosis. Lobulation and microlobulation of nodules are important features in breast cancer diagnosis based on mammographic analysis by using the ACR lexicon. We offer an approach for formalizing the distinction of these features and also formalize the description of the intermediate cases between lobulated and microlobulated masses. In this paper it is shown that fuzzy logic can be an effective tool in dealing with this kind of problems. The proposed formalization creates a base for the next two steps: (i) the automatic extraction of the related primitives from the image, and (ii) the detection of lobulated and microlobulated masses based on these primitives
  • Keywords
    fuzzy logic; breast cancer diagnosis; digital mammography; fuzzy logic; lobulation; mammographic analysis; microlobulation; Algorithm design and analysis; Breast cancer; Detection algorithms; Educational institutions; Fuzzy logic; Intelligent networks; Mammography; Neural networks; Radiology; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-3645-3
  • Type

    conf

  • DOI
    10.1109/FUZZY.1996.552630
  • Filename
    552630