Jiang J, Hall T J
Department of Medical Physics, University of Wisconsin-Madison, 1300 University Avenue, 1530 MSC, Madison, WI 53706, USA.
Phys Med Biol. 2007 Jul 7;52(13):3773-90. doi: 10.1088/0031-9155/52/13/008. Epub 2007 May 29.
Ultrasound-based mechanical strain imaging systems utilize signals from conventional diagnostic ultrasound systems to image tissue elasticity contrast that provides new diagnostically valuable information. Previous works (Hall et al 2003 Ultrasound Med. Biol. 29 427, Zhu and Hall 2002 Ultrason. Imaging 24 161) demonstrated that uniaxial deformation with minimal elevation motion is preferred for breast strain imaging and real-time strain image feedback to operators is important to accomplish this goal. The work reported here enhances the real-time speckle tracking algorithm with two significant modifications. One fundamental change is that the proposed algorithm is a column-based algorithm (a column is defined by a line of data parallel to the ultrasound beam direction, i.e. an A-line), as opposed to a row-based algorithm (a row is defined by a line of data perpendicular to the ultrasound beam direction). Then, displacement estimates from its adjacent columns provide good guidance for motion tracking in a significantly reduced search region to reduce computational cost. Consequently, the process of displacement estimation can be naturally split into at least two separated tasks, computed in parallel, propagating outward from the center of the region of interest (ROI). The proposed algorithm has been implemented and optimized in a Windows system as a stand-alone ANSI C++ program. Results of preliminary tests, using numerical and tissue-mimicking phantoms, and in vivo tissue data, suggest that high contrast strain images can be consistently obtained with frame rates (10 frames s(-1)) that exceed our previous methods.
基于超声的机械应变成像系统利用传统诊断超声系统的信号来成像组织弹性对比度,从而提供新的具有诊断价值的信息。先前的研究(Hall等人,2003年,《超声医学与生物学》,第29卷,第427页;Zhu和Hall,2002年,《超声成像》,第24卷,第161页)表明,对于乳腺应变成像,具有最小仰角运动的单轴变形是首选,并且向操作员提供实时应变图像反馈对于实现这一目标很重要。本文报道的工作通过两项重大改进增强了实时散斑跟踪算法。一个根本变化是,所提出的算法是基于列的算法(一列由与超声束方向平行的数据行定义,即A线),而不是基于行的算法(一行由与超声束方向垂直的数据行定义)。然后,来自其相邻列的位移估计为在显著减小的搜索区域中的运动跟踪提供了良好的指导,以降低计算成本。因此,位移估计过程可以自然地分为至少两个独立的任务,并行计算,从感兴趣区域(ROI)的中心向外传播。所提出的算法已在Windows系统中作为独立的ANSI C++程序实现并进行了优化。使用数值和组织模拟体模以及体内组织数据进行的初步测试结果表明,以超过我们先前方法的帧率(10帧/秒)可以持续获得高对比度应变图像。