The present invention relates generally to the field of digital mammography, and more particularly to an automated fibro-glandular (FG) tissue segmentation in full digital mammography using a fuzzy logic framework.
Screening mammography is considered to be one of the most reliable and cost-effective methods for the early detection of breast cancer. Breasts are composed of both fatty and fibro-glandular (FG) tissues. Radiologists often look to the FG regions in the breast, to study the patterns and look for abnormalities.
Breast FG density (BD) refers to the prevalence of fibro-glandular tissue in the breast as it appears on a mammogram, and BD estimation is often preceded by FG segmentation. FG tissues may appear in different contrast levels due to many factors, such as projection, mammogram paddle compression force and particular device specifications. At low densities, other anatomic parts, for example, blood vessels and Cooper ligaments strongly resemble the FG tissues in their brightness pattern.
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