Standard and complete lexicon that takes into account the different malignancy factors for characterization of mammography, ultrasound and MRI as defined by the American College of Radiology (ACR) in 1998. It classifies mammograms into six categories according to the degree of suspicion of their pathological character.
Published in Chapter:
Breast Cancer Diagnosis With Mammography: Recent Advances on CBMR-Based CAD Systems
Abir Baâzaoui (SIIVA, LIMTIC Laboratory, Institut Supérieur d'Informatique El Manar, Université de Tunis El Manar, Tunisia) and Walid Barhoumi (Ecole Nationale d'Ingénieurs de Carthage, Université de Carthage, Tunisia & SIIVA, LIMTIC Laboratory, Institut Supérieur d'Informatique El Manar, Université de Tunis El Manar, Tunisia)
Copyright: © 2021
|Pages: 21
DOI: 10.4018/978-1-7998-3456-4.ch006
Abstract
Breast cancer, which is the second-most common and leading cause of cancer death among women, has witnessed growing interest in the two last decades. Fortunately, its early detection is the most effective way to detect and diagnose breast cancer. Although mammography is the gold standard for screening, its difficult interpretation leads to an increase in missed cancers and misinterpreted non-cancerous lesion rates. Therefore, computer-aided diagnosis (CAD) systems can be a great helpful tool for assisting radiologists in mammogram interpretation. Nonetheless, these systems are limited by their black-box outputs, which decreases the radiologists' confidence. To circumvent this limit, content-based mammogram retrieval (CBMR) is used as an alternative to traditional CAD systems. Herein, authors systematically review the state-of-the-art on mammography-based breast cancer CAD methods, while focusing on recent advances in CBMR methods. In order to have a complete review, mammography imaging principles and its correlation with breast anatomy are also discussed.