Artificial Intelligence in Breast Imaging

Xin Wang, Nikita Moriakov, Yuan Gao, Tianyu Zhang, Luyi Han, Ritse M. Mann*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademic

Abstract

The development and implementation of artificial intelligence (AI) for breast imaging have been ongoing for several decades and have played an important role in clinical practice. With the emergence and maturity of deep learning (DL) algorithms, the application of AI technology in medical imaging has gradually moved to a higher level and broader range. It may break the performance bottleneck of traditional computer-aided detection/diagnosis (CAD) systems. This chapter reviews the three domains of clinical use cases for AI techniques in breast imaging, including risk assessment for screening, breast cancer detection and classification for diagnosis, and therapy selection and outcome prediction for interventions. As for future directions, it is necessary to improve the AI-based system’s interpretability and performance in a clinical application and maximize its clinical impact.
Original languageEnglish
Title of host publicationBreast Imaging
Subtitle of host publicationDiagnosis and Intervention
EditorsMichael Fuchsjager, Elizabeth Morris, Thomas Helbich
PublisherU. S. Joint Publications Research Service
Pages435-453
Number of pages19
DOIs
Publication statusPublished - 1 Jan 2022

Publication series

SeriesMedical radiology
ISSN0942-5373

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