Real-time imaging based quantification of microbubbles concentration and velocity vector quality evaluation using texture analysis method for ultrasonic particle image velocimetry technique

Previous studies showed that the concentration of ultrasound contrast agents (UCAs) during imaging would impact greatly on the accuracy of flow velocity measurements using ultrasonic particle image velocimetry (Echo PIV) technique. This paper presents a texture-based method to identify the optimum concentration of UCAs for Echo PIV. The first-order and seconded-order texture features, standard deviation, contrast, energy and homogeneity, are extracted from ultrasound images of in vitro rotational flow (10MHz) and in vivo rat (30MHz) common carotid arterial flow with UCAs at various concentrations. The results show that the optimum UCAs concentration is 0.8~2×10
³
bubbles/ml in vitro and 1~5×10
⁵
bubbles/ml in vivo, therein high accurate velocity vectors are obtained by Echo PIV. Otherwise, poor quality velocity vectors are yielded. The accuracy of K-nearest neighbor classifier reaches 86.4% in vitro. Thus, texture features could be used to identify the optimum UCAs concentration in real time for Echo PIV.