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基于约束最小二乘法的医学超声最佳变迹设计 第二部分:仿真结果

Optimal apodization design for medical ultrasound using constrained least squares part II: simulation results.

作者信息

Guenther Drake A, Walker William F

机构信息

University of Virginia, Department of Biomedical Engineering, Charlottesville, USA.

出版信息

IEEE Trans Ultrason Ferroelectr Freq Control. 2007 Feb;54(2):343-58. doi: 10.1109/tuffc.2007.248.

Abstract

In the first part of this work, we introduced a novel general ultrasound apodization design method using constrained least squares (CLS). The technique allows for the design of system spatial impulse responses with narrow mainlobes and low sidelobes. In the linear constrained least squares (LCLS) formulation, the energy of the point spread function (PSF) outside a certain mainlobe boundary was minimized while maintaining a peak gain at the focus. In the quadratic constrained least squares (QCLS) formulation, the energy of the PSF outside a certain boundary was minimized, and the energy of the PSF inside the boundary was held constant. In this paper, we present simulation results that demonstrate the application of the CLS methods to obtain optimal system responses. We investigate the stability of the CLS apodization design methods with respect to errors in the assumed wave propagation speed. We also present simulation results that implement the CLS design techniques to improve cystic resolution. According to novel performance metrics, our apodization profiles improve cystic resolution by 3 dB to 10 dB over conventional apodizations such as the flat, Hamming, and Nuttall windows. We also show results using the CLS techniques to improve conventional depth of field (DOF).

摘要

在本研究的第一部分,我们介绍了一种使用约束最小二乘法(CLS)的新型通用超声变迹设计方法。该技术能够设计出具有窄主瓣和低旁瓣的系统空间脉冲响应。在线性约束最小二乘法(LCLS)公式中,在保持焦点处峰值增益的同时,使点扩散函数(PSF)在某个主瓣边界之外的能量最小化。在二次约束最小二乘法(QCLS)公式中,使PSF在某个边界之外的能量最小化,并使边界内PSF的能量保持恒定。在本文中,我们展示了模拟结果,这些结果证明了CLS方法在获得最佳系统响应方面的应用。我们研究了CLS变迹设计方法相对于假定波传播速度误差的稳定性。我们还展示了实施CLS设计技术以提高囊性分辨率的模拟结果。根据新的性能指标,我们的变迹剖面相对于诸如平坦窗、汉明窗和努塔尔窗等传统变迹,可将囊性分辨率提高3 dB至10 dB。我们还展示了使用CLS技术提高传统景深(DOF)的结果。

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