Komatsu Masaaki, Sakai Akira, Dozen Ai, Shozu Kanto, Yasutomi Suguru, Machino Hidenori, Asada Ken, Kaneko Syuzo, Hamamoto Ryuji
Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
Division of Medical AI Research and Development, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan.
Biomedicines. 2021 Jun 23;9(7):720. doi: 10.3390/biomedicines9070720.
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.
人工智能（AI）在医学研究和应用中的应用越来越广泛。美国食品药品监督管理局及其他国家的相关机构已陆续批准了多种医疗人工智能设备。超声（US）成像在广泛的医学领域中普遍使用。然而，与其他医学成像模态相比，基于人工智能的超声成像分析及其临床应用尚未取得稳步进展。由于超声成像的手动操作和声学阴影等特性问题，导致图像质量控制存在困难。在本综述中，我们将从临床和基础两个角度介绍医学人工智能在超声成像研究方面的全球趋势。我们还将讨论超声图像预处理、适用于超声成像分析的精巧算法、用于获取知情同意的人工智能可解释性、医疗人工智能设备的审批流程，以及基于人工智能的超声诊断支持技术临床应用的未来前景。
