Evaluation of hybrid GSC-based and ASSB-based beamforming methods applied to ultrasound imaging
The application of adaptive beamforming to biomedical ultrasound imaging has been an active research area in recent years. Adaptive beamforming techniques have the capability of achieving excellent resolution and sidelobe suppression, thus improving the quality of the ultrasound images. This quality...
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| Language: | English en |
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2012
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| Online Access: | http://hdl.handle.net/1828/4123 |
| Summary: | The application of adaptive beamforming to biomedical ultrasound imaging has been an active research area in recent years. Adaptive beamforming techniques have the capability of achieving excellent resolution and sidelobe suppression, thus improving the quality of the ultrasound images. This quality improvement, however, comes at a high computational cost. The work presented in this thesis aims to answer the following basic question: Can we reduce the computational complexity of adaptive beamforming without a significant degradation of the image quality? Our objective is to explore a combination of low-complexity non-adaptive beamforming, such as the conventional Delay-and-Sum (DAS) method, with high-complexity adaptive beamforming, such as the standard Minimum-Variance Distortionless Response (MVDR) method implemented using the Generalized Sidelobe Canceller (GSC). Such a combination should have the lower computational complexity than adaptive beamforming, but it should also offer the image quality comparable to that obtained using adaptive beamforming. In addition to the adaptive GSC-based MVDR beamforming method, we also investigate the performance of the so-called Adaptive Single Snapshot Beamformer (ASSB), which is relatively unexplored in the ultrasound imaging literature.
The main idea behind our approach to combining a non-adaptive beamformer with an adaptive one is based on the use of the data-dependent variable known as the coherence factor. The resulting hybrid beamforming method can be summarized as follows: For each input snapshot to be beamformed, calculate the corresponding coherence factor; if the coherence factor is below a certain threshold, use non-adaptive DAS beamforming, otherwise use adaptive (GSC-based or ASSB-based) beamforming. We have applied this simple switching scheme to the simulated B-mode ultrasound images of the 12-point and point-scatterer-cyst phantoms that are commonly used in the ultrasound imaging literature to evaluate the image quality. Our simulation results show that, in comparison to optimal high-complexity always-adaptive beamforming, our hybrid beamformer can yield significant computational savings that range from 59% to 99%, while maintaining the image quality (measured in terms of resolution and contrast) within a 5% degradation margin. === Graduate |
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