Artificial intelligence and machine learning for medical imaging: A technology review.
Artificial intelligence and machine learning for medical imaging: A technology review.
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DOI：
10.1016/j.ejmp.2021.04.016
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发表时间：
2021-03
期刊：
影响因子：
--
通讯作者：
Lee JA
中科院分区：
文献类型：
--
作者：
Barragán-Montero A;Javaid U;Valdés G;Nguyen D;Desbordes P;Macq B;Willems S;Vandewinckele L;Holmström M;Löfman F;Michiels S;Souris K;Sterpin E;Lee JA
由于颠覆性的技术进步和令人印象深刻的实验结果，人工智能(AI)最近已经成为一个非常流行的流行语，特别是在图像分析和处理领域。在医学方面，放射学、病理学或肿瘤学等以图像为中心的专业已经抓住了机遇，并在研发方面做出了相当大的努力，以将人工智能的潜力转化为临床应用。随着人工智能成为典型医学成像分析任务(如诊断、分割或分类)的更主流工具，安全有效地使用临床人工智能应用程序的关键部分依赖于知情的从业者。这篇综述的目的是介绍人工智能的基本技术支柱，以及最先进的机器学习方法及其在医学成像中的应用。此外，我们还讨论了新的发展趋势和未来的研究方向。这将帮助读者了解AI方法现在如何成为任何医学图像分析工作流程中的普遍工具，并为基于AI的解决方案的临床实施铺平道路。
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence of disruptive technical advances and impressive experimental results, notably in the field of image analysis and processing. In medicine, specialties where images are central, like radiology, pathology or oncology, have seized the opportunity and considerable efforts in research and development have been deployed to transfer the potential of AI to clinical applications. With AI becoming a more mainstream tool for typical medical imaging analysis tasks, such as diagnosis, segmentation, or classification, the key for a safe and efficient use of clinical AI applications relies, in part, on informed practitioners. The aim of this review is to present the basic technological pillars of AI, together with the state-of-the-art machine learning methods and their application to medical imaging. In addition, we discuss the new trends and future research directions. This will help the reader to understand how AI methods are now becoming an ubiquitous tool in any medical image analysis workflow and pave the way for the clinical implementation of AI-based solutions.
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影响因子：
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作者：
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DOI：
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作者：
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DOI：
10.1093/jamia/ocy017
发表时间：
2018-08-01
期刊：
Journal of the American Medical Informatics Association : JAMIA
影响因子：
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