Noise reduction for quadrature Doppler ultrasound signal based on the adapted local cosine transform

The spectral analysis of the Doppler ultrasound signal based on the spectrogram has been widely used in medicine for the assessment of blood flow in vessels. The additional frequency components arising from noise produces an adverse effect on the subjective study of the spectrogram and its quantitative analysis. A novel approach using the adapted local cosine transform, combined with the non-negative garrote thresholding method, is proposed to remove noise from the quadrature Doppler ultrasound signal. At first, the directional information is extracted from the quadrature signal. Then the denoising method based on the adapted local cosine transform is performed on the forward and reverse flow signals, respectively. At last, the estimated signal is reconstructed from the denoised signals using Hilbert transform. In the simulation study, the estimation precision of the mean frequency waveform and the spectral width waveform are studied for the signal after denoising. The simulation results for the simulated Doppler ultrasound signals have shown that this approach is superior to the one based on the wavelet transform, especially under low SNR conditions.