Iterative fuzzy segmentation for an accurate delimitation of the breast region.
In mammographic images, extracting different anatomical structures and tissues types is a critical requirement for the breast cancer diagnosis. For instance, separating breast and background regions increases the accuracy and efficiency of mammographic processing algorithms. In this paper, we propose a new region-based method to properly segment breast and background regions in mammographic images. These regions are estimated by an Iterative Fuzzy Breast Segmentation method (IFBS). Based on the Fuzzy C-Means (FCM) algorithm, IFBS method iteratively increases the precision of an initially extracted breast region. This proposal is evaluated using the MIAS database. Experimental results show high accuracy and reliability in breast extraction when compared with Ground-Truth (GT) images.
Computer Science Department, Faculty of Science of Monastir, Tunisia. Electronic address: asmaa.touil@gmail.com.
Asma
A
Touil
Computer Science Department, Faculty of Science of Monastir, Tunisia. Electronic address: karim.kalti@gmail.com.
Karim
K
Kalti
D001940:Breast / Q000000981:diagnostic imaging*; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D008327:Mammography
Breast skin-line; Fuzzy C-Means clustering; Mammography