Artificial intelligence in breast ultrasonography

Citations

WEB OF SCIENCE

39
Citations

SCOPUS

48

초록

Although breast ultrasonography is the mainstay modality for differentiating between benign and malignant breast masses, it has intrinsic problems with false positives and substantial interobserver variability. Artificial intelligence (AI), particularly with deep learning models, is expected to improve workflow efficiency and serve as a second opinion. AI is highly useful for performing three main clinical tasks in breast ultrasonography: detection (localization/segmentation), differential diagnosis (classification), and prognostication (prediction). This article provides a current overview of AI applications in breast ultrasonography, with a discussion of methodological considerations in the development of AI models and an up-to-date literature review of potential clinical applications.

키워드

Artificial intelligence; Breast neoplasm; Ultrasonography; Convolutional neural network; Breast diseases; LESION DETECTION; ALGORITHM; US; CLASSIFICATION; EXPLANATIONS; INFORMATION; MAMMOGRAPHY; PERFORMANCE; DENSITY; LEXICON
제목
Artificial intelligence in breast ultrasonography
저자
Kim, Jaeil; Kim, Hye Jung; Kim, Chanho; Kim, Won Hwa
DOI
10.14366/usg.20117
발행일
2021-04
유형
Review
저널명
Ultrasonography
권
40
호
2
페이지
183 ~ 190