Algorithm and Architecture Design of Eigen-based Doppler Engine in Ultrasound Systems
Date Issued
2012
Date
2012
Author(s)
Zhan, Cheng-Zhou
Abstract
Ultrasonic imaging is a well-established imaging modality that has the advantages of cost-effectiveness, non-invasiveness, rapid imaging, and portability. color Doppler imaging is a well-established Doppler ultrasound mode and very valuable for visualizing in the real-time distribution of blood flow in a specific region of interest. The blood velocity can be detected by measuring the Doppler frequency shift of the echoes back-scattered from the moving blood. Nevertheless, the portability of current high-frequency ultrasonic imaging systems is insufficient. This will be more and more unacceptable since it is inconvenient and sometimes harmful for patients to go to the hospital for diagnoses. The high cost also reduces the popularity of such medical devices. Moreover, in ambulances or battlefields, portable devices supporting immediate diagnosis can greatly increase the survival rate.
Furthermore, the traditional Doppler engine needs complex parameter settings, it is inconvenient for the user, and it would not work when the users are not familiar with parameter settings for particular environment. Therefore, we simplify complex operations and enhance the efficiency. These features improve the convenience and efficiency of the portable ultrasound systems. The blood signals are generally much weaker than tissue and background noises, so that various filters are required to mitigate the noises.
The clutter filtering in the Doppler flow imaging is utilized to suppress the great tissue noises. The performance of the clutter filtering will remarkably affect the results of the Doppler flow imaging. Compared with the traditional high-pass filters adopted as clutter filters, singular-value-based or eigenvalue-based filters are proposed for signal-adaptive properties and high de-noising performance. Nevertheless, the high computational complexity and long computational time are still the main limitations for real-time Doppler flow imaging.
There are three main topics in this work. In the first part, the joint-decision mechanism with trace-back verification scheme is proposed to improve the performance of the eigen-based clutter filtering. After receiving the ultrasonic signals of the region of interest, the joint-decision mechanism is proposed to divide the signal spaces as clutter-noise space and blood-signal space according to the properties of eigenvalues and corresponding frequencies. In addition, the trace-back verification scheme is proposed according to the correlation of successive Doppler frames. The performance is 2-5 dB better than that of referenced works.
In the second part of this work, a nonlinear soft-decision thresholding after clutter filtering is proposed. The thresholding scheme is conventionally utilized to eliminate the remaining tissue or background noises after the clutter filters. Compared with the traditional hard-decision thresholding, we use the statistical properties of bloods and tissues for nonlinear thresholding. We use the maximum likelihood (ML) and maximum a posteriori (MAP) tests for decision. There is about 5-10 dB performance improvements compared with that of the referenced works.
In the third part, a superlinear-convergence singular-value-decomposition (SL-SVD) algorithm is proposed with properties of high-speed and low total computational complexity. The SL-SVD may be used to mitigate the problems of computational complexity and processing time in the singular-value-based or eigenvalue-based filters as clutter filters. The hardware is also implemented in 90 nm technology. The implementation results of SL-SVD has 20-40 times throughput compared with that of referenced works. The design is also capable of supporting different sizes of matrixes.
Subjects
ultrasound
blood flow
Doppler
Type
thesis
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