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_version / Electrical and Electronic Engineering / Master / Master of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/174484 |
| Date | January 2011 |
| Creators | Chan, Lok-sang, 陳樂生 |
| Contributors | Yu, ACH, Cheung, PYS |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Source | http://hub.hku.hk/bib/B47753043 |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
Page generated in 0.0014 seconds