"Fuzzy Logic in Computer-Aided Breast Cancer
Diagnosis: Analysis of Lobulation"
Artificial Intelligence in Medicine,, 1997, No. 11, pp. 75-85.
B. Kovalerchuk, E. Triantaphyllou, J.F. Ruiz, and J. Clayton
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.