Abstract
Adaptive beamforming methods, most based on the minimum variance(MV), are widely used in medical ultrasound imaging because of their significant improvement in image quality, especially the imaging resolution, compared with conventional delay-and-sum(DAS) beamformer. Recently, a new eigenspace-based MV(EIBMV) beamformer has been proposed to enhance the image contrast which is not satisfactory in MV beamforming, by utilizing the eigenstructure of the covariance matrix. principal component analysis was introduced to solve the problem of computational complexity existing in MV-based beamformers. Besides, Multi-Apodization with Cross-correlation(MAX) is also a novel beamforming technique, utilizing multiple pairs of complementary receive apodizaions for clutter and sidelobes suppression whereas maintaining the lateral resolution. By contrast, Null Subtraction Imaging(NSI) uses different on-receive apodizations on copies of the same image, contributing more in improving lateral resolution than that in reducing sidelobe levels. Thus in this work, combining the PCI, EIBMV, MAX and NSI together, we proposed a fast adaptive beamforming to realize clutter and sidelobes suppression, contrast and resolution improvement, computation complexity reduction simultaneously. And we verify the effectiveness of the proposed method by using simulated and experimental RF data—point targets as well as cyst phantoms.
Published Version
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