Biomedical Engineering Graduate Program, Western University, London, Ontario, Canada.
Ultrasound Med Biol. 2012 Aug;38(8):1429-39. doi: 10.1016/j.ultrasmedbio.2012.03.017. Epub 2012 May 12.
The wall-filter selection curve method is proposed to objectively identify a cut-off velocity that minimizes artifacts in power Doppler images. A selection curve, which is constructed by plotting the color pixel density (CPD) as a function of the cut-off velocity, exhibits characteristic intervals hypothesized to include the optimum cut-off velocity. This article presents an improved implementation of the method that automatically detects characteristic intervals in a selection curve and selects an operating point cut-off velocity along a characteristic interval. The method is applied to subregions within the Doppler image to adapt the cut-off velocity to local variations in vascularity. The method's performance is evaluated in 30-MHz power Doppler images of a four-vessel flow phantom. At high (>5 mm/s) flow velocities, qualitative improvements in vessel delineation are achieved and the CPD in the resulting images is accurate to within 3% of the vascular volume fraction of the phantom.
提出了一种壁滤波选择曲线方法，以客观地识别最小化彩色能量多普勒图像伪影的截止速度。选择曲线是通过绘制颜色像素密度（CPD）作为截止速度的函数而构建的，其呈现出假设包含最佳截止速度的特征区间。本文提出了一种改进的方法实现方式，该方法可自动检测选择曲线中的特征区间，并沿特征区间选择一个工作点截止速度。该方法应用于多普勒图像的子区域内，以适应血管局部变化的截止速度。该方法在 30MHz 功率多普勒图像的四血管流动模型中进行了性能评估。在高（>5mm/s）流速下，血管边界的定性改善得以实现，并且得到的图像中的 CPD 与模型的血管容积分数的准确性在 3%以内。
