P6B-8 Utility of Template-based Filtering Methods to Improve Accuracy of Echo PIV for Multi-Component Blood Velocity Measurements

In Echo PIV technique, the microbubbles are seeded in flows and traced by ultrasound B-mode imaging technique, from which the successive microbubble images are then cross- correlated to generate two-dimensional (2D) velocity map showing the flow pattern. The initial in vitro studies showed the utility of this technique in accurately measuring 2D velocity vectors in a variety of opaque flows. Although the method appears promising, improving signal-to-noise ratio (SNR) of backscatter data continues to be an important area of further study. By applying the current available filters, such as band pass filter, matched filter, or deconvolution technique, we found neither of them improves the accuracy of velocity measurement very well, although the particle images could be enhanced. In this paper, we introduce here a new RF filtering technique: Cross-correlation based Template Matching Filter (CTMF). This method involves cross-correlation between a template signal (Gaussian weighted pulse) and the target signal (ultrasound RF signal). The resulting correlation index is then thresholded to increase precision in obtaining bubble position information. The position information is incorporated into the bubble detection procedure to produce the improved pulse signal. Both the threshold and the template signals would have effects on particle image quality. Therefore, both factors are studied to optimize those values. In order to evaluate the performance of the proposed method on improving the measurement accuracy of Echo PIV, a rotating flow experiment was carried out and a series of RF data were acquired for post-processing We compared the particle images by applying different filters, including CTMF, convolution and wiener filter, respectively; also the vector maps based on different filter induced particle images were compared. The results show the best performance from the proposed filter, both on particle image and vector map accuracy, with vector outliers reduced from 15-18- % for the conventional filters to less than 5% for CTMF.