Narrow Vascular Doppler Ultrasound Blood Flow Information Extraction Method

It's observed that atherosclerotic lesions preferentially occur in arteries and arterioles in regions of high curvature or where there are bifurcations and junctions. After the atherosclerosis and plaque has developed to the point where it significantly narrows the vessel (stenosis), the flow through them compromised, which reduces the supply of blood to vessels downstream. The plaque may fracture and rupture, which leads to the stroke or cerebral infarct.The endarterectomy, angioplasty and medicine are usually adopted for the treatment of arterial stenoses with different degree. The degree of stenosis is estimated by using the DSA, MRA, CTA and ultrasound system. The DSA is still the golden standard for diagnoses of arterial stenoses. Because of the non-invasion, convenience and cheap cost, ultrasound systems are usually the best choice for screening and tracing cases. Various methods based on the morphology and hemodynamics were developed for the quantification of the degree of stenosis by using ultrasound techniques. The ultrasound imaging is used to measure the diameter of vessel, which can be visualized but with a poor precision and reproducibility. The quantitative analysis of the spectral disturbance of Doppler ultrasound signals from the outlet of the stenosis gets the better performance.The past research work of arterial stenoses with Doppler ultrasound technique was focused on the physical experiments and the clinical experiments based on the analysis of the spectral features of Doppler signals. There is still lack of objective and accurate research about the relationship between the blood flow status changes caused by stenoses and the features of Doppler signals. Although the computer simulating method for Doppler ultrasound signals has been successfully applied to normal blood flow analyses, there are still no systematic report about the research of Doppler signals from stenoses because of the modeling complexity of such Doppler ultrasound signals. According to this background, we carried out some further research work about the diagnosis of the arterial stenosis based on Doppler ultrasound techniques. First, two simplified stenosis models were tried in our work, and an approach for simulating Doppler ultrasound signals from stenoses was proposed based on the knowledge combination of the fluid mechanics and signal processing, whichimproved the understanding of the fluid field within the stenosis and the features of Doppler ultrasound signals from stenoses.Since the existence of noise in Doppler ultrasound signals may reduce the estimation precision of the maximum frequency, the mean frequency and the spectral width, which further do harm to the diagnostic precision, a Doppler ultrasound signal denoising algorithm based on the wavelet frame was introduced. Sometime, there are still some signals with high amplitude from the arterial wall or the surrounding tissues. Two novel methods were proposed to remove the arterial wall effects: one is that a fixed target canceller was introduced to cancel the wall signal in audio Doppler ultrasound signals; the other is that the blood and wall signal was separated in the time-scale representation.In order to improve the precision of the blood flow rate and the maximum velocity, which are two important indices in stenosis diagnoses, methods for quantitative measurement of the blood flow velocity with Doppler ultrasound and the maximum frequency estimation in spectrograms were advanced in our work. The velocity calculation with the re-correction got a satisfied precision of measurements within a wide range of the angle. A method based on the wavelet analysis was proposed to estimate the maximum frequency in spectrograms. Furthermore, the transient features of the maximum frequency waveform from carotid arteries were analyzed by using the wavelet transform. The clinic experiments showed that the new features may be more sensitive than the conventional spectrogram indices for some diseases.Finally, the applications of the wavelet analysis in the Dopp...