Aliabadi Saeid, Wang Yuanyuan, Yu Jinhua, Zhao Jinxin, Guo Wei, Zhang Shun
Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention (MICCAI) of Shanghai, Shanghai, 200433, China.
Biomed Eng Online. 2016 Nov 24;15(1):127. doi: 10.1186/s12938-016-0244-4.
The Eigenspace-based beamformers, by orthogonal projection of signal subspace, can remove a large part of the noise, and provide better imaging contrast upon the minimum variance beamformer. However, wrong estimate of signal and noise component may bring dark-spot artifacts and distort the signal intensity. The signal component and noise and interference components are considered uncorrelated in conventional eigenspace-based beamforming methods. In ultrasound imaging, however, signal and noise are highly correlated. Therefore, the oblique projection instead of orthogonal projection should be taken into account in the denoising procedure of eigenspace-based beamforming algorithm.
In this paper, we propose a novel eigenspace-based beamformer based on the oblique subspace projection that allows for consideration of the signal and noise correlation. Signal-to-interference-pulse-noise ratio and an eigen-decomposing scheme are investigated to propose a new signal and noise subspaces identification. To calculate the beamformer weights, the minimum variance weight vector is projected onto the signal subspace along the noise subspace via an oblique projection matrix.
We have assessed the performance of proposed beamformer by using both simulated software and real data from Verasonics system. The results have exhibited the improved imaging qualities of the proposed beamformer in terms of imaging resolution, speckle preservation, imaging contrast, and dynamic range.
Results have shown that, in ultrasound imaging, oblique projection is more sensible and effective than orthogonal subspace projection. Better signal and speckle preservation could be obtained by oblique projection compare to orthogonal projection. Also shadowing artifacts around the hyperechoic targets have been eliminated. Implementation the new subspace identification has enhanced the imaging resolution of the minimum variance beamformer due to the increasing the signal power in direction of arrival. Also it has offered better sidelobe suppression and a higher dynamic range.
基于特征空间的波束形成器通过信号子空间的正交投影,可以去除大部分噪声,并在最小方差波束形成器的基础上提供更好的成像对比度。然而,对信号和噪声分量的错误估计可能会带来暗斑伪像并扭曲信号强度。在传统的基于特征空间的波束形成方法中,信号分量与噪声和干扰分量被认为是不相关的。然而,在超声成像中,信号和噪声是高度相关的。因此,在基于特征空间的波束形成算法的去噪过程中应考虑斜投影而非正交投影。
在本文中,我们提出了一种基于斜子空间投影的新型基于特征空间的波束形成器,该波束形成器考虑了信号和噪声的相关性。研究了信干噪比和特征分解方案,以提出一种新的信号和噪声子空间识别方法。为了计算波束形成器权重,通过斜投影矩阵将最小方差权重向量沿噪声子空间投影到信号子空间上。
我们使用模拟软件和来自Verasonics系统的真实数据评估了所提出波束形成器的性能。结果表明,在所提出的波束形成器的成像分辨率、斑点保留、成像对比度和动态范围方面,成像质量得到了改善。
结果表明,在超声成像中,斜投影比正交子空间投影更合理、更有效。与正交投影相比,斜投影可以获得更好的信号和斑点保留。此外,高回声目标周围的阴影伪像已被消除。由于增加了到达方向上的信号功率,实施新的子空间识别提高了最小方差波束形成器的成像分辨率。它还提供了更好的旁瓣抑制和更高的动态范围。