The aim of this paper is to review existing approaches to the automatic detection and
segmentation of masses in mammographic images, highlighting the key-points and main …

Digital mammography systems allow manipulation of fine differences in image contrast by
means of image processing algorithms. Different display algorithms have advantages and …

It has been shown that the accuracy of mammographic abnormality detection methods is
strongly dependent on the breast tissue characteristics, where a dense breast drastically …

The pectoral muscle represents a predominant density region in most medio-lateral oblique
(MLO) views of mammograms; its inclusion can affect the results of intensity-based image …

This paper presents a method for automatic breast pectoral muscle segmentation in
mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired …

Mammograms are X-ray images of the breast which are used to detect breast cancer. When
mammograms are analyzed by computer, the pectoral muscle should preferably be …

Evaluating the previous work is an important part of developing segmentation methods for
the image analysis techniques. The aim of this paper is to give a review of digital image …

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause
(s) of breast cancer still remains unknown. Early detection, precise identification of women at …

Studies reported in the literature indicate that the increase in the breast density is one of the
strongest indicators of developing breast cancer. In this paper, we present an approach to …

Mammograms are X-ray images of human breast which are normally used to detect breast
cancer. The presence of pectoral muscle in mammograms may disturb the detection of …