Aiming at rejecting nonstationary clutter originating from slow moving vessels and surrounding tissues

a singular-spectral-weighting-based clutter suppression method for color ultrasound Doppler imaging is presented in this paper.First

a Hankel data matrix is created from each slow-time ensemble.Then

the singular value decomposition is performed to obtain the orthogonal basis functions for regression filtering.The coefficients of the filter are adaptively computed by a modified sigmoid function from the power normalized singular spectral

which allows for means to detect regions of clutter artifacts with high specificity.To analyze the efficacy of the proposed adaptive filter

in-vitro experiments were carried out.For the experiments

raw CFI data were acquired by a commercial ultrasound system (Sonix RP

Ultrasonix Inc.).Then

blood flow parameters are estimated from an estimate of the lag-one auto correlator of the filtered signal.The reconstructed flow and power images verifies that the proposed method outperforms other tested methods in rejecting high intense nonstationary clutter

which leads to improved distinguishing between blood and tissue regions.