Clutter Removal of Doppler Ultrasound Signal Using Double Density Discrete Wavelet Transform

The strong clutter induced by stationary and slow moving tissue structures may distort the low frequency components of spectrogram and degrade the precision of clinical indices. A new wavelet method, the double density discrete wavelet transform (DD-DWT) combining the semisoft shrinkage function and a threshold with local variance estimation, is proposed for removing adaptively clutter components from Doppler ultrasound signals. The new method is tested with both simulated and in vivo Doppler blood signals, and compared with conventional high pass filter (HPF). The improvements in sonogram and signal-to-clutter (S/C) ratio of Doppler signals filtered by new method over HPF are noticeable. For the simulated signal with S/C ratio -20 dB, the improvement in S/C ratio is 22.51 dB by new method, but 22.05 dB by HPF. The low frequency part of resultant sonograms verifies that the new method can effectively remove clutter components and retain more low flow signal simultaneously.