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KMID : 1114620210180020076
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Journal of the Korean Society for Breast Screening
2021 Volume.18 No. 2 p.76 ~ p.80
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Applications of Artificial Intelligence in Automated Breast Ultrasound
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Oh Kang-Rok
Lee Si-Eun
Kim Eun-Kyung
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Abstract
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Automated breast ultrasound (ABUS) is becoming a powerful complementary imaging modality of mammography. Due to its enormous data size, the exploitation of ABUS computer-aided detection and diagnosis (CAD) systems is crucial in the time-consuming screening process. Conventional ABUS-CAD systems containing extensive image processing, hand-crafted feature extraction, and classification modules suffer from low generalization capability. Recently deep learning (DL) has been applied successfully in advanced ABUS-CAD systems given sufficient data and supplementary techniques such as data augmentation and transfer learning. In this study, we investigate underlying artificial intelligence techniques of ABUS-CAD systems with their clinical applications in the literature.
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KEYWORD
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Breast, Automated Breast Ultrasound, Artificial Intelligence, Computer-Aided Detection, Computer-Aided Diagnosiss
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