Mirzaei Morteza, Asif Amir, Rivaz Hassan
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:2071-2074. doi: 10.1109/EMBC44109.2020.9175426.
Ultrasound elastography is a non-invasive technique for detecting pathological alterations in tissue. It is known that pathological alteration of tissue often has a direct impact on its elastic modulus, which can be revealed using elastography. For estimating elastic modulus, we need to estimate both axial and lateral displacement accurately. Current state of the art elastography techniques provide a substantially less accurate lateral displacement field as compared to the axial displacement field. One of the most important factors in poor lateral estimation is a low sampling frequency in the lateral direction. In this paper, we use synthetic aperture beamforming to benefit from its capability of high sampling frequency in the lateral direction. We compare highly sampled data and focused line per line beam formed data by feeding them to our recently published elastography method, OVERWIND [1]. According to simulation and phantom experiments, not only the lateral displacement estimation is substantially improved, but also the axial displacement estimation is improved.
超声弹性成像术是一种用于检测组织病理改变的非侵入性技术。众所周知,组织的病理改变通常会直接影响其弹性模量,而弹性成像术能够揭示这种变化。为了估计弹性模量,我们需要精确估计轴向和横向位移。与轴向位移场相比,当前最先进的弹性成像技术所提供的横向位移场的准确性要低得多。横向估计不佳的最重要因素之一是横向方向上的采样频率较低。在本文中,我们使用合成孔径波束形成技术,以利用其在横向方向上的高采样频率能力。我们将高采样数据和逐行聚焦线波束形成数据输入到我们最近发表的弹性成像方法OVERWIND [1]中进行比较。根据模拟和体模实验,不仅横向位移估计得到了显著改善,轴向位移估计也有所提高。