Objective: The purpose of this article is to compare traditional versus machine learning-based computer-aided detection (CAD) platforms in breast imaging with a focus on mammography, to underscore limitations of traditional CAD, and to highlight potential solutions in new CAD systems under development for the future.
Conclusion: CAD development for breast imaging is undergoing a paradigm shift based on vast improvement of computing power and rapid emergence of advanced deep learning algorithms, heralding new systems that may hold real potential to improve clinical care.
Keywords: artificial intelligence; breast; computer-aided detection; computer-aided diagnosis; mammography; texture analysis.