[Self-adaptive beamforming method based on plane wave ultrasound imaging]

Area of Science:

• Medical Imaging
• Signal Processing
• Acoustics

Context:

• Improving ultrasound imaging quality is crucial for diagnostics.
• Plane wave ultrasound imaging offers high frame rates but faces resolution and contrast challenges.
• Adaptive beamforming is key to overcoming these limitations.

Purpose:

• To develop an optimized minimum variance (MV) beamforming algorithm tailored for plane wave ultrasound imaging.
• To enhance image resolution, contrast, and signal-to-noise ratio.
• To validate the algorithm's effectiveness through simulations.

Summary:

• An optimized minimum variance (MV) algorithm was developed by integrating subband beamforming and forward-backward spatial smoothing in the frequency domain.
• Simulations using MATLAB demonstrated superior performance of the Optimized MV method compared to Conventional MV, DAS boxcar, and Linear scan.
• Key metrics like full width at half maximum (0.08 dB) and peak side-lobe level (-41.1 dB) showed significant improvements.

Impact:

• The proposed algorithm substantially improves image resolution and contrast in plane wave ultrasound imaging.
• Offers a significant advancement over conventional minimum variance and delay-and-sum methods.
• Enhances diagnostic capabilities in ultrasound applications.