Adaptive flow detector and estimator for ultrasound high frame rate vector flow imaging

Cardiovascular diseases is a leading cause of death worldwide and improvement of the corresponding screening tool is the best way to deal with this clinical problem. In this thesis we attempted to develop a framework of ultrasound high frame rate vector flow imaging (VFI) by emphasizing on the design of corresponding flow detector and flow estimator. We believe that the high temporal resolution and the complex blood flow visualization ability of high frame rate VFI enables it to be further developed as a reliable flow imaging modality for cardiological examination. In order to achieve high temporal resolution, fast data acquisition algorithm was applied in the framework. Doppler signals acquired using this acquisition algorithm have two unique characteristics comparing with conventional data acquisition algorithm: (1) widen spectral bandwidth and (2) greater clutter to blood signal ratio. These signal characteristics give rise to unique signal processing. In addition, complex blood flow pattern, which is common in cardiological examination, induces extra challenges in implementing high frame rate VFI. In this thesis, flow detector which is adaptive to different flow scenarios and high dynamic range 2D flow estimator were presented. The proposed flow detector employes K-means++ clustering algorithm to classify clutter components from acquired Doppler signals. As a performance analysis, Field II simulation studies were performed by a parabolic flow phantom (flow velocity: 10mm/s to 200mm/s; tissue motion: 10mm/s; beam-flow angle: 60?). The post-filtered Doppler power map and BCR were used as qualitative and quantitativemeasures of detectors performance. Analyzed result has indicated that, as compared with clutter downmixing detector and eigen-based detector, the proposed flow detector could classify and suppress clutter component more effectively. Results also suggested that the proposed flow detector is more adaptive to slow flow scenarios where existing flow detectors failed to distinguish between blood and clutter components. For the proposed flow estimator, it was characterized by the interpolation of speckle tracking results in Lagrangian reference frame. The estimation bias and RMS error were calculated for different flow scenarios (flow velocity: 100mm/s to 500mm/s; beam-flow angle: 15? to 60?). It was found that the proposed flow estimator provides higher dynamic range than conventional speckle tracking-based flow estimator. Nonetheless, it is also observed that the estimation variances and errors increases in slow flow scenarios. In order to demonstrate the medical potential of the proposed high frame rate VFI framework. A carotid bifurcation simulation model with realistic blood flow pattern calculated using computational fluid dynamic software was applied in the performance evaluation study. In the VFI image obtained, complex blood flow pattern was readily visualized. In contrast, conventional ultrasound flow imaging was only able to estimate axial velocity map and thus lead to many ambiguities in analyzing the complex blood flow pattern. It proved that ultrasound high frame rate VFI has the potential to be further developed into a new cardiological examination technique.published_or_final_versionElectrical and Electronic EngineeringMasterMaster of Philosoph