title: Eigenspace-based beamformer using oblique signal subspace projection for ultrasound plane-wave imaging.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Saeid
authors.initials: S
authors.lastname: Aliabadi
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China. yywang@fudan.edu.cn.|Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention (MICCAI) of Shanghai, Shanghai, 200433, China. yywang@fudan.edu.cn.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China. jhyu@fudan.edu.cn.|Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention (MICCAI) of Shanghai, Shanghai, 200433, China. jhyu@fudan.edu.cn.
authors.forename: Jinhua
authors.initials: J
authors.lastname: Yu
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Jinxin
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Guo
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Shun
authors.initials: S
authors.lastname: Zhang
mesh_terms: D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D019047:Phantoms, Imaging; D059629:Signal-To-Noise Ratio; D014463:Ultrasonography
keywords: Beamforming; Eigenspace-based minimum variance; Oblique projection matrix; Signal subspace; Ultrasound plane-wave imaging