A review of artificial intelligence in mammography

Meghan P Jairam; Richard Ha

doi:10.1016/j.clinimag.2022.05.005

A review of artificial intelligence in mammography

Clin Imaging. 2022 Aug:88:36-44. doi: 10.1016/j.clinimag.2022.05.005. Epub 2022 May 15.

Authors

Meghan P Jairam¹, Richard Ha²

Affiliations

¹ Vagelos College of Physicians & Surgeons, 630 West 168th Street, New York, NY 10032, United States.
² Associate Professor of Radiology, Director of Research and Education, Breast Imaging Section, Columbia University Medical Center, 622 West 168th Street, PB-1-301, New York, NY 10032, United States of America. Electronic address: rh2616@columbia.edu.

PMID: 35623118
DOI: 10.1016/j.clinimag.2022.05.005

Abstract

Breast cancer is the most common cancer among women worldwide. Mammography is the most widely used modality to detect breast cancer. Over the past decade, computer aided detection (CAD) powered by artificial intelligence (AI)/deep learning has shown significant increase in accuracy compared to the traditional CAD. In this review, we aim to summarize the latest developments in the field of AI and mammography and discuss where future progress may lie.

Keywords: Artificial intelligence; Breast cancer; Computer-aided detection; Mammography; Neural networks; Systematic review.

Publication types

Review

MeSH terms

Artificial Intelligence*
Breast Neoplasms* / diagnostic imaging
Female
Humans
Mammography