An adaptive clutter rejection method based on AR model in color flow imaging

The ultrasound Doppler signal scattered from blood is heavily corrupted by the clutter signal reflected from slowly moving muscular tissue. The Doppler frequency shift of blood flow and clutter in different parts of human body greatly changes. Therefore, if a fixed wall filter is selected, the optimal filtering effect can not be attained. An adaptive clutter rejection method is proposed in this paper, which consists of a weak clutter rejector and a 2-order AR estimator. The clutter and blood power thresholds were preliminary defined in the weak clutter rejector. The echo power is compared with the two pre-defined thresholds, and the result was used to select an appropriate wall filter. The output of the weak clutter rejector is estimated by a 2-order AR estimator and two poles are acquired. The low frequency pole denotes the clutter signal and the high frequency pole denotes the blood signal. Before the AR estimation, a static signal is added to avoid producing split spectral peaks. It is illustrated in the simulation that the proposed method can detect the slower blood flow with smaller variance compared with the traditional wall filtering method.