Towards Clinical Application of Artificial Intelligence in Ultrasound Imaging

被引:55
|
作者
Komatsu, Masaaki [1 ,2 ]
Sakai, Akira [3 ,4 ,5 ]
Dozen, Ai [2 ]
Shozu, Kanto [2 ]
Yasutomi, Suguru [3 ,4 ]
Machino, Hidenori [1 ,2 ]
Asada, Ken [1 ,2 ]
Kaneko, Syuzo [1 ,2 ]
Hamamoto, Ryuji [1 ,2 ,5 ]
机构
[1] RIKEN, Ctr Adv Intelligence Project, Canc Translat Res Team, Chuo Ku, 1-4-1 Nihonbashi, Tokyo 1030027, Japan
[2] Natl Canc Ctr, Div Med AI Res & Dev, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan
[3] Fujitsu Ltd, Artificial Intelligence Lab, Res Unit, Nakahara Ku, 4-1-1 Kamikodanaka, Kawasaki, Kanagawa 2118588, Japan
[4] RIKEN, Ctr Adv Intelligence Project, RIKEN AIP Fujitsu Collaborat Ctr, Chuo Ku, 1-4-1 Nihonbashi, Tokyo 1030027, Japan
[5] Tokyo Med & Dent Univ, Grad Sch Med & Dent Sci, Biomed Sci & Engn Track, Bunkyo Ku, 1-5-45 Yushima, Tokyo 1138510, Japan
关键词
ultrasound imaging; artificial intelligence; machine learning; deep learning; preprocessing; classification; detection; segmentation; explainability; BREAST-TUMOR SEGMENTATION; CONFIDENCE MAPS; DEEP; CLASSIFICATION; DIAGNOSIS; CANCER; ECHOCARDIOGRAPHY; ENHANCEMENT; LESIONS; IMAGES;
D O I
10.3390/biomedicines9070720
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Artificial intelligence (AI) is being increasingly adopted in medical research and applications. Medical AI devices have continuously been approved by the Food and Drug Administration in the United States and the responsible institutions of other countries. Ultrasound (US) imaging is commonly used in an extensive range of medical fields. However, AI-based US imaging analysis and its clinical implementation have not progressed steadily compared to other medical imaging modalities. The characteristic issues of US imaging owing to its manual operation and acoustic shadows cause difficulties in image quality control. In this review, we would like to introduce the global trends of medical AI research in US imaging from both clinical and basic perspectives. We also discuss US image preprocessing, ingenious algorithms that are suitable for US imaging analysis, AI explainability for obtaining informed consent, the approval process of medical AI devices, and future perspectives towards the clinical application of AI-based US diagnostic support technologies.
引用
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页数:20
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