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3D normalized cross-correlation for estimation of the displacement field in ultrasound elastography

机译:超声弹性术中估计位移场的归一化交叉相关性

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This paper introduces a novel technique to estimate tissue displacement in quasi-static elastography. A major challenge in elastography is estimation of displacement (also referred to time-delay estimation) between pre-compressed and post-compressed ultrasound data. Maximizing normalized cross correlation (NCC) of ultrasound radio-frequency (RF) data of the pre- and post-compressed images is a popular technique for strain estimation due to its simplicity and computational efficiency. Several papers have been published to increase the accuracy and quality of displacement estimation based on NCC. All of these methods use 2D spatial windows in RF data to estimate NCC, wherein displacement is assumed to be constant within each window. In this work, we extend this assumption along the third dimension. Two approaches are proposed to get third dimension. In the first approach, we use temporal domain to exploit neighboring samples in both spatial and temporal directions. Considering temporal information is important since traditional and ultrafast ultrasound machines are, respectively, capable of imaging at more than 30 frame per second (fps) and 1000 fps. Another approach is to use time-delayed pre-beam formed data (channel data) instead of RF data. In this method information of all channels that are recorded as pre-beam formed data of each RF line will be considered as 3rd dimension. We call these methods as spatial temporal normalized cross correlation (STNCC) and channel data normalized cross correlation (CNCC) and show that they substantially outperforms NCC using simulation, phantom and in-vivo experiments. Given substantial improvements of results in addition to the relative simplicity of implementing STNCC and CNCC, the proposed approaches can potentially have a large impact in both academic and commercial work on ultrasound elastography.
机译:本文介绍了一种新颖的技术来估算准静态弹性术中的组织位移。弹性造影的主要挑战是预压缩和压缩后超声数据之间的位移(也提到时间延迟估计)的主要挑战。最大化超声波射频(RF)数据的归一化交叉相关(NCC)和压缩后图像的数据是由于其简单性和计算效率而具有应变估计的流行技术。已公布几篇论文,以提高基于NCC的位移估计的准确性和质量。所有这些方法都在RF数据中使用2D空间窗口来估计NCC,其中假设位移在每个窗口内是恒定的。在这项工作中,我们沿着第三维度扩展了这一假设。提出了两种方法来获得第三维度。在第一种方法中,我们使用时间域在空间和时间方向上利用相邻样本。考虑到时间信息很重要,因为传统和超速超声波机器分别能够以每秒30帧(FPS)和1000个FPS成像。另一种方法是使用时延的预束形成数据(信道数据)而不是RF数据。在该方法中,记录为每个RF线的预光束形成的所有通道的信息将被认为是第三维度。我们称这些方法称为空间时间归一化交叉相关(STNCC)和信道数据标准化交叉相关(CNCC),并表明它们使用模拟,幻像和体内实验表明它们大致优于NCC。由于实施STNCC和CNCC的相对简单性除了实现STNCC和CNCC的相对简单之外,拟议方法可能对超声弹性创造的学术和商业工作有很大影响。

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