Abstract: Renal artery ultrasonic Doppler blood flow velocity signal extraction is a prerectuisite for the feature extraclion of blood flow velocity signals. And features of renal artery ultrasonic Doppler blood flow velocity signals are important means for curly renal arterial stenosis (RAS) diagnosis. I}o extract signals from ultrasonic images the locally adapfive confidence connected segmentation method was proposed to separate the signal region and the background. The segmentation is impactful even with intensity inhomogencity and strong noise. For the segmented image, the connected components labeling was used to fill small gaps and to eliminate the impact of interference information. The extracted signal was corrected according to its local statistics, and filtered for noise smoothing with Mean Shift All these result in a robust signal sequence extraction of blood flow velocity in renal artery. The experimental results show that the signal sequence of blood flow velocity in renal artery can be extracted accurately and robustly with this method.

Key words: Ultrasonic doppler, Image, Confidence connected, Segmentation, Flow signals