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Adaptive ultrasound imaging to improve the visualization of spine and associated structures

University of British Columbia

Visualizing vertebrae or other bone structures clearly in ultrasound imaging is important for many clinical applications such as ultrasound-guided spinal needle injections and scoliosis detection. Another growing research topic is fusing ultrasound with other imaging modalities to get the benefit from each modality. In such approaches, tissue with strong interfaces, such as bones, are typically extracted and used as the feature for registration. Among those applications, the spine is of particular interest in this thesis. Although such ultrasound applications are promising, clear visualization of spine structures in ultrasound imaging is difficult due to factors such as specular reflection, off-axis energy and reverberation artifacts. The received channel ultrasound data from the spine are often tilted even after delay correction, resulting in signal cancellation during the beamforming process. Conventional beamformers are not designed to tackle this issue. In this thesis, we propose three beamforming methods dedicated to improve the visualization of spine structures. These methods include an adaptive beamforming method which utilizes the accumulated phase change across the receive aperture as the beamforming weight. Then, we propose a log-Gabor based directional filtering method to regulate the tilted channel data back to the beamforming direction to avoid bone signal cancellation. Finally, we present a closed-loop beamforming method which feeds back the location of the spine to the beamforming process so that backscattered bone signals can be aligned prior-to the beamforming. Field II simulation, phantom and in vivo results confirm significant contrast improvement of spinal structures compared with the conventional delay-and-sum beamforming and other adaptive beamforming methods.

Text

2018-10-16

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/67582

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/