Foroughi Pezhman, Rivaz Hassan, Fleming Ioana N, Hager Gregory D, Boctor Emad M
Dept. of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Med Image Comput Comput Assist Interv. 2010;13(Pt 2):9-16. doi: 10.1007/978-3-642-15745-5_2.
This paper presents a robust framework for freehand ultrasound elastography to cope with uncertainties of freehand palpation using the information from an external tracker. In order to improve the quality of the elasticity images, the proposed method selects a few image pairs such that in each pair the lateral and out-of-plane motions are minimized. It controls the strain rate by choosing the axial motion to be close to a given optimum value. The tracking data also enables fusing multiple strain images that are taken roughly from the same location. This method can be adopted for various trackers and strain estimation algorithms. In this work, we show the results for two tracking systems of electromagnetic (EM) and optical tracker. Using phantom and ex-vivo animal experiments, we show that the proposed techniques significantly improve the elasticity images and reduce the dependency to the hand motion of user.
本文提出了一种用于徒手超声弹性成像的稳健框架,以利用来自外部跟踪器的信息来应对徒手触诊的不确定性。为了提高弹性图像的质量,该方法选择了几对图像,使得每对图像中的横向和平面外运动最小化。它通过选择轴向运动使其接近给定的最佳值来控制应变率。跟踪数据还能够融合大致从相同位置获取的多个应变图像。该方法可用于各种跟踪器和应变估计算法。在这项工作中,我们展示了电磁(EM)和光学跟踪器这两种跟踪系统的结果。通过使用仿体和离体动物实验,我们表明所提出的技术显著改善了弹性图像,并减少了对用户手部运动的依赖性。