A novel quadrature clutter rejection approach based on multivariate empirical mode decomposition (MEMD), which is an extension of empirical mode decomposition (EMD) to multivariate for processing multichannel signals, is proposed in this paper to suppress the quadrature clutter signals induced by the vascular wall and the surrounding stationary or slowly moving tissues in composite Doppler ultrasound signals, and extract more blood flow components with low velocities. In this approach, the MEMD algorithms, which include the bivariate empirical mode decomposition with a nonuniform sampling scheme for adaptive selection of projection directions (NS_BEMD) and the trivariate empirical mode decomposition with noise assistance (NA_TEMD), are directly employed to adaptively decompose the complex-valued quadrature composite signals echoed from both bidirectional blood flow and moving wall into a small number of zero-mean rotation components, which are defined as complex intrinsic mode functions (CIMFs). Then the relevant CIMFs contributed to blood flow components are automatically distinguished in terms of the break of the CIMFs’ power, and then directly added up to give the quadrature blood flow signal. Specific simulation and human subject experiments are taken up to demonstrate the advantages and limitations of this novel method for quadrature clutter rejection in bidirectional Doppler ultrasound signals. Due to eliminating the extra errors induced by the Hilbert transform or complex FIR filter algorithms used in the traditional clutter rejection approaches based on the directional separation process, the proposed method provides improved accuracy for clutter rejection, and preserve more slow blood blow components, which could be helpful to early diagnose arterial diseases. 
A novel quadrature clutter rejection approach based on the multivariate empirical mode decomposition for bidirectional Doppler ultrasound signals