Noble J A
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Headington, Oxford OX3 7DQ, UK.
Proc Inst Mech Eng H. 2010;224(2):307-16. doi: 10.1243/09544119JEIM604.
Ultrasound image segmentation deals with delineating the boundaries of structures, as a step towards semi-automated or fully automated measurement of dimensions or for characterizing tissue regions. Ultrasound tissue characterization (UTC) is driven by knowledge of the physics of ultrasound and its interactions with biological tissue, and has traditionally used signal modelling and analysis to characterize and differentiate between healthy and diseased tissue. Thus, both aim to enhance the capabilities of ultrasound as a quantitative tool in clinical medicine, and the two end goals can be the same, namely to characterize the health of tissue. This article reviews both research topics, and finds that the two fields are becoming more tightly coupled, even though there are key challenges to overcome in each area, influenced by factors such as more open software-based ultrasound system architectures, increased computational power, and advances in imaging transducer design.
超声图像分割涉及勾勒结构边界,这是迈向尺寸半自动或全自动测量或组织区域特征化的一步。超声组织表征(UTC)是由超声物理学及其与生物组织相互作用的知识驱动的,传统上使用信号建模和分析来表征和区分健康组织和病变组织。因此,两者都旨在增强超声作为临床医学定量工具的能力,并且两个最终目标可能相同,即表征组织的健康状况。本文回顾了这两个研究主题,发现这两个领域的联系越来越紧密,尽管每个领域都存在关键挑战,这些挑战受到诸如基于软件的超声系统架构更加开放、计算能力增强以及成像换能器设计进步等因素的影响。