Abstract

Singular value decomposition (SVD)-based filters have become the norm for clutter filtering in ultrasound blood flow applications but are computationally expensive and susceptible to large and fast tissue motion. Randomized SVD (rSVD) has later been shown to successfully accelerate filtering of in vivo stationary tissues. However, little is known about its performance on ultrafast echocardiography, which produces thousands of frames to assess complex myocardial deformation and blood dynamics. Neither has its inherently robust randomized scheme been proven in any ultrasound blood flow imaging methods. This study thus proposed to employ rSVD as a fast and robust clutter filter for ultrafast echocardiograms prior to power Doppler analysis. Ultrafast echocardiograms of nine normal human hearts were acquired in vivo by our cascaded synthetic aperture imaging method. One subject was additionally scanned under four different sonographic signal-to-noise ratio (SNR) levels. Contrast ratio (CR) and contrast-to-noise ratio (CNR) of in vivo power Doppler images obtained from filtered ultrafast echocardiograms were calculated, and their mean and standard deviation within a cardiac cycle represented temporal average and variation of contrast resolution, respectively. Our in vivo results showed that rSVD accelerated clutter filtering by 12-fold and provided significantly better local contrast (mean CNR values: p < 0.001) while being equally effective (mean CR values: p=0.20) compared with full-SVD. rSVD yielded smaller standard deviations of CR (1.32 dB vs. 5.49 dB) and CNR (1.27 dB vs. 5.49 dB) than full-SVD in the lowest SNR scenario, thus substantiating its superior robustness. Our findings suggest using rSVD in ultrafast echocardiographic blood dynamics analysis.

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