Noise reduction for doppler ultrasound signal based on the adapted local cosine transform and the garrote thresholding method

Abstract

In this paper, a novel approach, using the adapted local cosine transform combined with the non-negative garrote thresholding, is proposed to remove noise from the Doppler ultrasound signal. In the proposed approach, the local cosine transform is first performed on the signal of interest followed by a search algorithm to select the best basis. Then the coefficients of the obtained best basis are thresholded based on the non-negative garrote thresholding method. By means of the thresholded coefficients of the best basis, the signal is reconstructed. In the simulation study, the estimation precisions of the mean frequency waveform and the spectral width waveform are studied for the signal after denoising. The simulation and clinical results have shown that the proposed approach is superior to ones based on the wavelet transform, especially under low signal-to-noise ratio (SNR) circumstances.