A review of computer aided detection in mammography

被引：58

作者：

Katzen, Janine ^{[1
]}

Dodelzon, Katerina ^{[1
]}

机构：

[1] Weill Cornell Med, Dept Radiol, 425 E 61st St, New York, NY 10065 USA

来源：

CLINICAL IMAGING | 2018年 / 52卷

关键词：

Mammography; Computer aided detection; DIGITAL BREAST TOMOSYNTHESIS; SCREENING MAMMOGRAPHY; DETECTION SYSTEM; CANCER-DETECTION; DIAGNOSTIC-ACCURACY; CLUSTERED MICROCALCIFICATIONS; COST-EFFECTIVENESS; FILM MAMMOGRAPHY; DETECTION CAD; RECALL RATES;

D O I：

10.1016/j.clinimag.2018.08.014

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

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.

引用

页码：305 / 309

页数：5

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