Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.

翻译：超声（US）凭借其无创、无辐射及实时成像等优势，已成为临床诊疗中应用最广泛的模态之一。然而，手持式超声检查高度依赖操作者经验。机器人超声系统（RUSS）旨在通过提供可重复性来克服这一缺陷，同时提升操作灵活性，并实现智能化的解剖结构与病灶感知成像。除改善诊断效果外，RUSS还具有为缺乏资深超声技师的人群提供医疗干预的潜力。本文将RUSS分为遥操作型与自主型两类进行归类。针对遥操作型RUSS，我们分别总结了其技术进展与临床评估。随后，本综述重点回顾了近年来自主机器人超声成像的相关研究。研究表明，机器学习与人工智能是实现患者及流程特异性、运动与形变感知的智能机器人图像采集的关键技术。我们还发现，针对自主RUSS的人工智能研究已引导学界深入理解并建模专家超声技师的语义推理与操作行为，我们将其称为“超声语言”的恢复过程。自主机器人超声采集的这一衍生研究成果，其价值与机器人超声检查本身的技术进步同等重要。本文通过系统梳理底层技术，为工程师与临床医生提供对RUSS的全面认知。