Recent developments in computer vision has led to a number of automated approaches for Doppler angle estimation.  \citet{Hirsch2006} presented a multi-scale approach for estimating the vessel's flow direction by principal component analysis. More recently, \citet{Saad_2008} described a computer vision approach to automate the Doppler angle estimation. The approach starts with the segmentation of blood vessels in ultrasound color Doppler images. The segmentation step is followed by an estimation technique for the Doppler angle(\(\theta\)) based on a skeleton representation of the segmented vessel. Statistical regression analysis showed strong agreement between the manual and automated methods. They further hypothesized that the automation of the Doppler angle will enhance the workflow of the ultrasound Doppler exam and achieve more standardized clinical outcome.