Iterative fuzzy segmentation for an accurate delimitation of the breast region

A Touil, K Kalti - Computer methods and programs in biomedicine, 2016 - Elsevier
A Touil, K Kalti
Computer methods and programs in biomedicine, 2016Elsevier
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) …
Abstract
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.
Elsevier
以上显示的是最相近的搜索结果。 查看全部搜索结果