Background Pectoral muscle removal is a fundamental preliminary step in computer-aided
diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source …

Mammographic textures show promise as breast cancer risk predictors, distinct from
mammographic density. Yet, there is a lack of comprehensive evidence to determine the …

Mammography interpretation is challenging with high error rates. This study aims to reduce
the errors in mammography reading by mapping diagnostic errors against global …

Background and objectives: The computerized analysis of mammograms for the
development of quantitative biomarkers is a growing field with applications in breast cancer …

Breast cancer develops when cells in your breast multiply and expand out of control,
resulting in a lump of tissue known as a tumor. Feeling a lump, observing a change in breast …

Purpose To assess the association between breast cancer risk and mammographic
parenchymal measures obtained using a fully-automated, publicly available software …

Purpose Accurate pectoral muscle removal is critical in mammographic breast density
estimation and many other computer-aided algorithms. We propose a novel approach to …

Introduction For women of the same age and body mass index, increased mammographic
density is one of the strongest predictors of breast cancer risk. There are multiple methods of …

Purpose Worldwide, female breast cancer is the fifth leading cause of death. Digital Breast
Tomosynthesis (DBT) is increasingly involved in the routine diagnosis of breast cancer …

Purpose This research on breast cancer risk assessment aims to develop models that
predict the likelihood of breast cancer. In recent years, the computerized analysis of visual …