Improvement in Multi-Angle Plane Wave Image Quality Using Minimum Variance Beamforming with Adaptive Signal Coherence

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Conventional coherent plane wave compounding (CPWC) in ultrasound imaging offers limited quality due to standard delay-and-sum beamforming.
• Delay-multiply-and-sum (DMAS) enhances image quality by incorporating signal coherence but often degrades background speckle.
• Existing DMAS methods apply a global coherence value, impacting overall image quality and contrast-to-noise ratio (CNR).

Purpose of the Study:

• To introduce an adaptive DMAS (ADMAS) algorithm for ultrasound multi-angle plane wave imaging.
• To maintain background speckle quality and CNR by adapting signal coherence to local image characteristics.
• To combine ADMAS with minimum variance (MV) beamforming for improved image resolution.

Main Methods:

• Developed the adaptive DMAS (ADMAS) algorithm, making signal coherence dependent on local image regions.
• Integrated ADMAS with minimum variance (MV) beamforming, optimizing MV estimation along the plane wave transmit angle (Tx).
• Evaluated the TxMV-ADMAS beamforming method using the PICMUS dataset for multi-angle plane wave imaging.

Main Results:

• TxMV-ADMAS significantly improved image quality compared to CPWC.
• While conventional DMAS improved resolution (0.57mm to 0.24mm) and contrast (27.0dB to 38.0dB), it reduced CNR (12.8 to 11.3).
• The proposed ADMAS algorithm restored CNR to CPWC levels while maintaining enhanced resolution and contrast.

Conclusions:

• The proposed TxMV-ADMAS beamforming method effectively enhances ultrasound image resolution and contrast.
• ADMAS preserves background speckle quality and CNR, overcoming limitations of conventional global coherence methods.
• This adaptive approach offers superior image quality for multi-angle plane wave ultrasound imaging.