基于蝶形搜索的二维自相关血流速度估计方法

应用血流速度估计的彩色血流成像技术在血管疾病诊断中发挥着重要作用.在血流速度估计中,传统的基于二维自相关模型的方法会产生混叠,而更准确的蝶形搜索方法则十分耗时.提出一种二维自相关模型和蝶形搜索结合的血流速度估计方法.首先采用二维自相关函数模型利用相位信息进行超声血流速度估计,得到一个存在混叠的速度估计值序列,再通过采用基于正交信号成分的蝶形搜索方法,由速度序列确定蝴蝶线,每条蝴蝶线通过计算选择出真实的速度估计值.该方法不但实现了对血流速度估计混叠的抑制,还显少了计算量,其有效性得到仿真结果的验证.

2 -D correlation model blood velocity estimation approach based on butterfly search

Blood velocity estimation is employed in color flow imaging that plays a major role in the diagnosis of vascular diseases. In blood velocity estimation, the popular 2-D correlation model based approach produces velocity ambiguity and more accurate approach based on butterfly search is time-consuming. A hybrid butterfly search and 2-D correlation model based approach was proposed to produce blood velocity estimation. Using the phase information of traditional 2-D correlation function model to estimate ultrasound blood velocity, a velocity estimation value sequence was formed. Then butterfly search based on orthogonal signal was applied to the sequence, butterfly line was decided by every sequence value and true velocities were chosen by calculating every point in the butterfly line. This approach evidently reduces calculation time with suppressing velocity ambiguity. Simulation results demonstrate the effectiveness of the approach.