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超声应变流成像中的自适应杂波抑制滤波

Adaptive clutter rejection filtering in ultrasonic strain-flow imaging.

作者信息

Kargel Christian, Höbenreich Gernot, Trummer Birgit, Insana Michael F

机构信息

Department of Medical Information Technology at the Carinthia Tech. Institute, University of Applied Sciences, Austria.

出版信息

IEEE Trans Ultrason Ferroelectr Freq Control. 2003 Jul;50(7):824-35. doi: 10.1109/tuffc.2003.1214502.

DOI:10.1109/tuffc.2003.1214502
PMID:12894916
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2715560/
Abstract

This paper introduces strain-flow imaging as a potential new technique for investigating vascular dynamics and tumor biology. The deformation of tissues surrounding pulsatile vessels and the velocity of fluid in the vessel are estimated from the same data set. The success of the approach depends on the performance of a digital filter that must separate echo signal components caused by flow from tissue motion components that vary spatially and temporally. Eigenfilters, which are an important tool for naturally separating signal components adaptively throughout the image, perform very well for this task. The method is examined using two tissue-mimicking flow phantoms that provide stationary and moving clutter associated with pulsatile flow.

摘要

本文介绍了应变流成像技术，它是一种用于研究血管动力学和肿瘤生物学的潜在新技术。脉动血管周围组织的变形和血管内流体的速度可从同一数据集估算得出。该方法的成功取决于数字滤波器的性能，该滤波器必须将由流动引起的回波信号分量与随空间和时间变化的组织运动分量区分开来。特征滤波器是一种在整个图像中自适应自然分离信号分量的重要工具，在这项任务中表现出色。使用两个模拟组织的流动体模对该方法进行了检验，这两个体模提供了与脉动流相关的静态和动态杂波。

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