Gaussian wavelet based dynamic filtering (GWDF) method for medical ultrasound systems

In this paper, a novel dynamic filtering method using Gaussian wavelet filters is proposed to remove noise from ultrasound echo signal. In the proposed method, a mother wavelet is first selected with its central frequency (CF) and frequency bandwidth (FB) equal to those of the transmitted signal. The actual frequency of the received signal at a given depth is estimated through the autocorrelation technique. Then the mother wavelet is dilated using the ratio between the transmitted central frequency and the actual frequency as the scale factor. The generated daughter wavelet is finally used as the dynamic filter at this depth. Frequency-demodulated Gaussian wavelet is chosen in this paper because its power spectrum is well-matched with that of the transmitted ultrasound signal. The proposed method is evaluated by simulations using Field II program. Experiments are also conducted out on a standard ultrasound phantom using a 192-element transducer with the center frequency of 5 MHz. The phantom contains five point targets, five circular high scattering regions with diameters of 2, 3, 4, 5, 6 mm respectively, and five cysts with diameters of 6, 5, 4, 3, 2 mm respectively. Both simulation and experimental results show that optimal signal-to-noise ratio (SNR) can be obtained and useful information can be extracted along the depth direction irrespective of the diagnostic objects.