Title of article
Fuzzy logic in computer-aided breast cancer diagnosis: analysis of lobulation
Author/Authors
Boris Kovalerchuk، نويسنده , , Boris and Triantaphyllou، نويسنده , , Evangelos and Ruiz، نويسنده , , James F and Clayton، نويسنده , , Jane، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 1997
Pages
11
From page
75
To page
85
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.
Keywords
breast cancer , Feature formalization , NEURAL NETWORKS , image recognition , Fuzzy Logic
Journal title
Artificial Intelligence In Medicine
Serial Year
1997
Journal title
Artificial Intelligence In Medicine
Record number
1842033
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