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Type: Artigo de periódico
Title: Segmentation of breast tumors in mammograms using fuzzy sets
Author: Guliato, D
Rangayyan, RM
Carnielli, WA
Zuffo, JA
Desautels, JEL
Abstract: Defining criteria to determine precisely the boundaries of masses in mammograms is a difficult task. The problem is compounded by the fact that most malignant tumors possess fuzzy boundaries with a slow and extended transition from a dense core region to the surrounding less-dense tissues. We propose two segmentation methods that incorporate fuzzy concepts. The first method determines the boundary of a mass or tumor by region growing after a preprocessing step based on fuzzy sets to enhance the region of interest (ROI). Contours provided by the method have demonstrated a good match with the contours drawn by a radiologist, as indicated by good agreement between the two sets of contours for 47 mammograms. The second segmentation method is a fuzzy region-growing method that takes into account the uncertainty present around the boundaries of tumors. The difficult step of deciding on a crisp boundary is obviated in the proposed method. Measures of inhomogeneity computed from the pixels present in a suitably defined fuzzy ribbon have indicated potential use in classifying the masses and tumors as benign or malignant, with a sensitivity of 0.8 and a specificity of 0.9. (C) 2003 SPIE and IST.
Country: EUA
Editor: Is&t & Spie
Rights: fechado
Identifier DOI: 10.1117/1.1579017
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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