篇名 | An Improved Parametric Relaxation Approach to Blood Flow Signal Estimation with Single-Ensemble Samples in Color Flow Imaging |
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卷期 | 33:3 |
作者 | Zhiyuan Shen 、 Naizhang Feng 、 Yi Shen 、 Chin-Hui Lee |
頁次 | 309-318 |
關鍵字 | parametric model 、 relaxation 、 single-ensemble samples 、 blood flow estimation 、 EI 、 SCI |
出刊日期 | 201306 |
DOI | 10.5405/jmbe.1368 |
In color flow imaging, it is a challenging work to accurately extract blood flow information from ultrasound Doppler echoes dominated by strong clutter components. Conventional non-parametric estimators usually cause flow velocity estimation biases since clutter rejection filters often distort parts of blood flows or fail to suppress clutter adequately. In this paper, a parametric estimation framework called relaxation (RELAX) is proposed to directly extract blood flow information from raw ultrasound Doppler signals. RELAX constructs an exponential model to approximate single-ensemble ultrasound Doppler echoes and solves for its parameters in a decoupled manner. The principal Doppler frequencies of the clutter and the blood flow obtained by RELAX are independent of the corresponding phase shifts. A parameter selection algorithm based on the energy ratio is proposed to determine the number of principal components. A series of simulations shows that the proposed RELAX approach can achieve accurate velocity estimation of blood flow. The mean overall errors obtained by RELAX are 30% lower compared to those obtained using state-of-the-art non-parametric methods using eigen-decomposition based filters. RELAX also eliminates the effect caused by white noise and achieves an extremely low estimation variance of low-velocity blood flow (< 15cm/s) compared to those obtained using competing methods. Clinical experiment results show that the RELAX method leads to the highest blood flow energy and blood-to-clutter energy ratio among those obtained using the discussed methods.