Department of Electronic Engineering, Sogang University, Seoul, Korea.
Ultrasound Med Biol. 2010 Mar;36(3):480-7. doi: 10.1016/j.ultrasmedbio.2009.11.008. Epub 2010 Feb 4.
Clutter rejection is essential for accurate flow estimation in ultrasound color Doppler imaging. In this article, we present a new adaptive clutter rejection (ACR) technique where an optimum filter is dynamically selected depending upon the underlying clutter characteristics (e.g., tissue acceleration and power). We compared the performance of the ACR method with other adaptive methods, i.e., down-mixing (DM) and adaptive clutter filtering (ACF), using in vivo data acquired from the kidney, liver and common carotid artery. With the kidney data, the ACR method provided an average improvement of 3.05 dB and 1.7 dB in flow signal-to-clutter ratio (SCR) compared with DM and ACF, respectively. With the liver data, SCR was improved by 2.75 dB and 1.8 dB over DM and ACF while no significant improvement with ACR was found in the common carotid artery data. Thus, the proposed adaptive method could provide more accurate flow estimation by improving clutter rejection in abdominal ultrasound color Doppler imaging pending validation.
杂波抑制对于超声彩色多普勒成像中准确的流量估计至关重要。在本文中，我们提出了一种新的自适应杂波抑制（ACR）技术，根据底层杂波特性（例如组织加速度和功率）动态选择最优滤波器。我们使用从肾脏、肝脏和颈总动脉采集的体内数据，将 ACR 方法的性能与其他自适应方法（即下混频（DM）和自适应杂波滤波（ACF））进行了比较。对于肾脏数据，与 DM 和 ACF 相比，ACR 方法分别提供了 3.05 dB 和 1.7 dB 的平均流量信号杂波比（SCR）提高。对于肝脏数据，与 DM 和 ACF 相比，SCR 分别提高了 2.75 dB 和 1.8 dB，而在颈总动脉数据中，ACR 并没有显著改善。因此，该自适应方法可以通过提高腹部超声彩色多普勒成像中的杂波抑制来提供更准确的流量估计，这有待验证。
