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                     | Search=au:kovalerchuk  | Results= 2 records  | Record=1]
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        RECORD NO.:  97412949
            AUTHOR:  Kovalerchuk B; Triantaphyllou E; Ruiz JF; Clayton J
           ADDRESS:  Department of Industrial Engineering, Louisiana State
                     University, Baton Rouge 70803-6409, USA.
             TITLE:  Fuzzy logic in computer-aided breast cancer diagnosis:
                     analysis of lobulation.
            SOURCE:  Artif Intell Med (BUP), 1997 Sep; 11 (1): 75-85
          LANGUAGE:  English
      COUNTRY PUB.:  NETHERLANDS
      ANNOUNCEMENT:  9712
         PUB. TYPE:  JOURNAL ARTICLE
          ABSTRACT:  This paper illustrates how a fuzzy logic approach can be
                     used to formalize terms in the American College of Radiology
                     (ACR) Breast Imaging 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 two
                     important features in the ACR lexicon. We offer an approach
                     for formalizing the distinction of these features and also
                     formalize the description of 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 problem. The proposed formalization
                     creates a basis for the next three steps (i) extended
                     verification with blinded comparison studies. (ii) the
                     automatic extraction of the related primitives from the
                     image, and (iii) the detection of lobulated and
                     microlobulated masses based on these primitives.
     MESH HEADINGS:  Breast Neoplasms--radiography (RA)/diagnosis (*DI); *Fuzzy
                     Logic; *Image Interpretation, Computer-Assisted; Neural
                     Networks (Computer); Female; Human; Support, U.S. Gov't, Non-
                     P.H.S.
      STANDARD NO.:  0933-3657
             DATES:  Entered 971016

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