A review of computer aided detection in mammography

Janine Katzen; Katerina Dodelzon

doi:10.1016/j.clinimag.2018.08.014

A review of computer aided detection in mammography

Clin Imaging. 2018 Nov-Dec:52:305-309. doi: 10.1016/j.clinimag.2018.08.014. Epub 2018 Sep 7.

Authors

Janine Katzen¹, Katerina Dodelzon²

Affiliations

¹ Department of Radiology, Weill Cornell Medicine, 425 E 61st Street, New York, NY 10065, United States of America. Electronic address: jak9072@med.cornell.edu.
² Department of Radiology, Weill Cornell Medicine, 425 E 61st Street, New York, NY 10065, United States of America.

PMID: 30216858
DOI: 10.1016/j.clinimag.2018.08.014

Abstract

Breast screening with mammography is widely recognized as the most effective method of detecting early breast cancer and has consistently demonstrated a 20-40% decrease in mortality among screened women. Despite this, the sensitivity of mammography ranges between 70 and 90%. Computer aided detection (CAD) is an artificial intelligence (AI) technique that utilizes pattern recognition to highlight suspicious features on imaging and marks them for the radiologist to review and interpret. It aims to decrease oversights made by interpreting radiologists. Here we review the efficacy of CAD and potential future directions.

Keywords: Computer aided detection; Mammography.

Publication types

Review

MeSH terms

Artificial Intelligence*
Breast / diagnostic imaging*
Breast Neoplasms / diagnosis*
Early Detection of Cancer / methods*
Female
Humans
Mammography / methods*
Radiographic Image Interpretation, Computer-Assisted / methods*