Abstract

Ultrasound Particle image velocimetry (UPIV) is a non-invasive flow measurement technique where acousticopaque flow tracers are injected into a working fluid and ensonified to create ultrasound images. These images are processed using PIV cross-correlation based algorithms to measure the velocity field (Kim et al., 2004). UPIV is useful for opaque flows, primarily where complex flows exist, accordingly, it is used in many industrial and clinical research applications such as studying intracardiac flow (Crase et al., 2007). Furthermore, the measurement provides suitable temporal and spatial resolutions for improved diagnostic metrics. Mentioned applications and the sensitive diagnostic industrial and clinical decisions made based on these measurements intensifies the importance of characterizing the UPIV measurement accuracy and associated uncertainty. However, quantifying UPIV measurement uncertainty is non-trivial due to the complexity of possible uncertainty sources, their combination, and propagation through the measurement chain.
 The formation of a particle image by ultrasound significantly differs from optical imaging, introducing unique aspects to image quality that must be considered. Particle images are formed across several ultrasound scan lines, yielding an elliptical particle image shape. Furthermore, the particle’s reflected pressure wave is converted to a digital signal that undergoes signal modulation, and this process forms a non-Gaussian point spread function (PSF) along the scan line direction. Additionally, clusters of tracers produce a single, bright image intensity and speckle image pattern. Compared to conventional PIV images, UPIV incurs significantly higher image noise due to lack of filtration for the ultrasound reflection of the non-tracer obstacles.

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