Twofold minimum variance beamforming for enhanced ultrasound imaging

Area of Science:

• Ultrasound Imaging
• Medical Imaging
• Signal Processing

Background:

• Minimum variance (MV) beamforming requires accurate estimation of the received data's covariance matrix.
• Spatial smoothing is commonly used in ultrasound for covariance estimation but reduces effective aperture and limits resolution.
• Existing methods face limitations in achieving optimal resolution and contrast in ultrasound imaging.

Purpose of the Study:

• To propose and evaluate a new adaptive beamforming configuration to overcome the limitations of spatial smoothing in ultrasound imaging.
• To improve the resolution and contrast of ultrasound images by enhancing the minimum variance beamforming technique.

Main Methods:

• A twofold configuration of MV beamforming was developed, combining subarray outputs adaptively.
• The proposed method utilizes an adaptive MV-like beamformer for combining subarray outputs, unlike simple summation.
• This approach results in a fully adaptive beamformer with improved signal processing capabilities.

Main Results:

• The novel method demonstrated superior attenuation of off-axis signals compared to conventional MV beamforming on point target phantoms.
• Results showed a reduced mainlobe width and decreased sidelobe levels, indicating enhanced resolution.
• Simulations on a cyst phantom confirmed the method's superiority over MV in improving image contrast.

Conclusions:

• The proposed adaptive beamforming method significantly improves resolving capability and contrast in ultrasound imaging compared to conventional MV.
• These improvements were achieved despite a slight increase in reflectivity coefficient estimation errors when steering vector errors were present.
• The method offers a promising advancement for high-resolution and high-contrast ultrasound imaging applications.