Committee on Medical Physics, Department of Radiology, The University of Chicago, 5841 S Maryland Avenue, MC2026, Chicago, IL 60637, USA.
Committee on Medical Physics, Department of Radiology, The University of Chicago, 5841 S Maryland Avenue, MC2026, Chicago, IL 60637, USA.
Radiol Clin North Am. 2021 Nov;59(6):1027-1043. doi: 10.1016/j.rcl.2021.07.010.
This article gives a brief overview of the development of artificial intelligence in clinical breast imaging. For multiple decades, artificial intelligence (AI) methods have been developed and translated for breast imaging tasks such as detection, diagnosis, and assessing response to therapy. As imaging modalities arise to support breast cancer screening programs and diagnostic examinations, including full-field digital mammography, breast tomosynthesis, ultrasound, and MRI, AI techniques parallel the efforts with more complex algorithms, faster computers, and larger data sets. AI methods include human-engineered radiomics algorithms and deep learning methods. Examples of these AI-supported clinical tasks are given along with commentary on the future.
本文简要概述了人工智能在临床乳房成像中的发展。几十年来，人工智能 (AI) 方法已经被开发出来并应用于乳房成像任务，如检测、诊断和评估治疗反应。随着成像方式的出现，以支持乳腺癌筛查计划和诊断检查，包括全数字化乳腺 X 线摄影、乳腺断层合成、超声和 MRI，人工智能技术与更复杂的算法、更快的计算机和更大的数据集一起发展。AI 方法包括人工设计的放射组学算法和深度学习方法。本文还给出了这些人工智能支持的临床任务的例子，并对未来进行了评论。
