Separable Beamforming For 3-D Medical Ultrasound Imaging

IEEE Transactions on Signal Processing(2015)

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摘要
Three-dimensional ultrasound imaging is a promising medical imaging technology because of its ease of use and improved accuracy in diagnosis. However, its high computational complexity and resulting high power consumption has precluded its use in hand-held applications. In this paper, we present a separable beamforming method that greatly reduces computational complexity. Our method is based on decomposing the delay term in a way that minimizes the root-mean-square error caused by the decomposition. We analyze tradeoffs between the approximation error caused by the decomposition and computational complexity. Then, we present enhancements to the Sonic Millip3De hardware accelerator for ultrasound beamforming to implement separable beamforming. Using hardware synthesis targeting standard cells in 45 nm, we show that the proposed method allows us to boost the Sonic Millip3De frame rate from 1-2 Hz to 32 Hz while maintaining power consumption at 15 W. We validate image quality of our method using cyst phantom simulations in Field II. Our evaluation demonstrates that the proposed separable beamforming method can produce 3-D images with high quality that are comparable to those generated by non-separable beamforming.
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standard cell targeting,sonic millip3de hardware accelerator enhancement,separable ultrasound beamforming,hand-held application,3D medical ultrasound imaging,diagnosis accuracy,high power consumption,Sonic Millip3De hardware accelerator enhancement,power consumption,computational complexity reduction,size 45 nm,three-dimensional ultrasound imaging,sonic millip3de frame rate,nonseparable beamforming,separable,biomedical ultrasonics,3-d ultrasound,3D image quality,beamforming,biomedical equipment,3d image quality,source separation,array signal processing,delay term decomposition,power 15 W,computational complexity,Field II,3-D ultrasound,cyst phantom simulation,Beamforming,3d medical ultrasound imaging,decomposition,root-mean-square error minimization,hardware synthesis,Sonic Millip3De frame rate,medical imaging technology,minimisation,hardware accelerator,approximation error,phantoms,field ii,medical image processing,power 15 w,mean square error methods
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