title: Amplitude and phase estimator combined with the Wiener postfilter for medical ultrasound imaging.
abstract: BACKGROUND
  The adaptive amplitude and phase estimator (APES) has been introduced in medical ultrasound imaging to calculate the amplitude of the desired signal more robustly than other adaptive beamformers like minimum variance (MV). This beamformer minimizes the optimization problem of MV by replacing the estimated array covariance matrix by the interferences plus noise covariance matrix. On the other hand, the Wiener postfilter as a post-weighting factor, which will be multiplied to the final weight vector of the beamformer, estimates the power of the desired signal and the power of the interferences plus noise to improve the contrast.
  
  
  METHODS
  The proposed method is a combination of the APES beamformer with the Wiener postfilter which uses the capabilities of the APES beamformer for accurate estimation of the amplitude of the desired signal and the Wiener postfilter in suppressing sidelobes. Specifically, we used the interferences plus the noise covariance matrix estimated in the APES beamformer to obtain an APES-based Wiener postfilter and obtained the APES + Wiener weight vector by multiplying the APES-based Wiener postfilter to the standard APES weight vector.
  
  
  RESULTS
  To evaluate the proposed APES + Wiener beamformer, we tested the proposed method on simulated and experimental datasets. The results of a simulated wire phantom demonstrate that the proposed beamformer can resolve two point scatterers better than the standard APES beamformer, even if the points are placed near each other. Simulating a cyst phantom shows that the APES + Wiener beamformer improves the contrast of the resulting images by about 4.5 dB by estimating the interior of the cyst better than the standard APES.
  
  
  CONCLUSIONS
  The evaluation of the proposed beamformer on an experimental dataset confirms the results of simulations, in which the proposed beamformer improves the resolution and contrast in comparison with the standard APES beamformer.
authors.affiliation: Department of Biomedical Engineering, Tarbiat Modares University, Jalal Ale Ahmad Highway, P.O. Box 14115-111, Tehran, Iran.
authors.forename: Ali Mohades
authors.initials: AM
authors.lastname: Deylami
authors.affiliation: Department of Biomedical Engineering, Tarbiat Modares University, Jalal Ale Ahmad Highway, P.O. Box 14115-111, Tehran, Iran. babakmasl@modares.ac.ir.
authors.forename: Babak Mohammadzadeh
authors.initials: BM
authors.lastname: Asl
mesh_terms: D003198:Computer Simulation; D003560:Cysts / Q000000981:diagnostic imaging; D066264:Datasets as Topic; D006801:Humans; D008954:Models, Biological; D019047:Phantoms, Imaging; D012815:Signal Processing, Computer-Assisted; D014463:Ultrasonography / Q000295:instrumentation / Q000379:methods*
keywords: Adaptive beamformer; Medical ultrasound imaging; Minimum variance; Phase and amplitude estimator; Wiener postfilter