Kibria Md Golam, Hasan Md Kamrul
Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh.
Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh.
Ultrasonics. 2015 Aug;61:88-102. doi: 10.1016/j.ultras.2015.04.001. Epub 2015 Apr 18.
In this paper, a novel real-time kernel-based and gradient-based Phase Root Seeking (PRS) algorithm for ultrasound elastography is proposed. The signal-to-noise ratio of the strain image resulting from this method is improved by minimizing the cross-correlation discrepancy between the pre- and post-compression radio frequency signals with an adaptive temporal stretching method and employing built-in smoothing through an exponentially weighted neighborhood kernel in the displacement calculation. Unlike conventional PRS algorithms, displacement due to tissue compression is estimated from the root of the weighted average of the zero-lag cross-correlation phases of the pair of corresponding analytic pre- and post-compression windows in the neighborhood kernel. In addition to the proposed one, the other time- and frequency-domain elastography algorithms (Ara et al., 2013; Hussain et al., 2012; Hasan et al., 2012) proposed by our group are also implemented in real-time using Java where the computations are serially executed or parallely executed in multiple processors with efficient memory management. Simulation results using finite element modeling simulation phantom show that the proposed method significantly improves the strain image quality in terms of elastographic signal-to-noise ratio (SNRe), elastographic contrast-to-noise ratio (CNRe) and mean structural similarity (MSSIM) for strains as high as 4% as compared to other reported techniques in the literature. Strain images obtained for the experimental phantom as well as in vivo breast data of malignant or benign masses also show the efficacy of our proposed method over the other reported techniques in the literature.
本文提出了一种用于超声弹性成像的基于实时内核和梯度的新型相位寻根（PRS）算法。通过采用自适应时间拉伸方法最小化压缩前后射频信号之间的互相关差异，并在位移计算中通过指数加权邻域内核进行内置平滑处理，该方法得到的应变图像的信噪比得到了提高。与传统的PRS算法不同，组织压缩引起的位移是根据邻域内核中一对相应的解析压缩前和压缩后窗口的零滞后互相关相位的加权平均值的根来估计的。除了本文提出的算法外，我们团队提出的其他时域和频域弹性成像算法（Ara等人，2013年；Hussain等人，2012年；Hasan等人，2012年）也使用Java实时实现，其中计算可以在多个处理器上串行执行或并行执行，并具有高效的内存管理。使用有限元建模模拟体模的模拟结果表明，与文献中其他报道的技术相比，对于高达4%的应变，该方法在弹性成像信噪比（SNRe）、弹性成像对比噪声比（CNRe）和平均结构相似性（MSSIM）方面显著提高了应变图像质量。从实验体模以及恶性或良性肿块的体内乳腺数据获得的应变图像也显示了我们提出的方法相对于文献中其他报道技术的有效性。
