Quadrature Doppler ultrasound signal denoising based on adaptive representations

The spectrogram of Doppler ultrasound signal has been widely used in the clinical diagnosis. The additional frequency component arising from noise will produce an adverse effect on the subjective analysis of the spectrogram and its quantitative analysis. Two approaches based on the adaptive representations including the adapted local cosine transform (CPD) and the wavelet packet (WPD), combined with the garrote thresholding, are proposed to denoising quadrature Doppler ultrasound signal. At first, to avoid the phase distortion induced by denoising the complex Doppler ultrasound signal directly, the directional information is extracted from the quadrature signal. And then the denoising methods based on the adaptive representations are performed on the forward and reverse flow signals, respectively. At last, the estimated signal is reconstructed from the denoised signals using Hilbert transform. The simulation results have shown that these approaches are superior to ones based on the wavelet transform, especially under low SNR circumstances, and moreover, the denoising method using the CPD has achieved the best performance.