Adaptive Spatiotemporal Clutter Rejection Based on Casorati-Singular Value Decompositionfor Ultrafast Plane-wave Doppler Imaging

Abstract

By using compounded plane wave, it enables the high-frame-rate acquisition of synchronous ultrasonic samples in the all field of view. However, classical clutter filters fail to deal with these big synchronous imaging datasets. In this study, an improved adaptive clutter rejection algorithm based on Casorati Singular Value Decomposition (Casorati-SVD) is proposed to take full advantage of synchronous datasets. The first step is to construct a Casorati matrix based on a block of plane-wave data and perform singular value decomposition on this Casorati matrix. Then the key point is to adaptively determine the cufoff thresholds according to Doppler frequency and energy of component signals and the blood flow signal is extracted through auto-generated filter. Finally, adaptive SVD filtering on each block is performed and the final flow signals are reconstructed from all blocks. To assess its ability in noise suppression, the proposed method is applied to blood flow echos obtained from phantom, arm artery and rabbit brain. These results demonstrate the improved method has 4.4% to 50% higher Signal-to-Noise-Ratio (SNR) and 4.7% to 55.9% Contrast-to-Noise-Ratio (CNR) than conventional Casorati-SVD methods. In conclusion, this method realizes spatial adaptive filtering and can be significant for development of clinical blood flow imaging.