An efficient subarray average delay multiply and sum beamformer algorithm in ultrasound imaging.

Area of Science:

• Medical Imaging
• Ultrasound Technology
• Signal Processing

Background:

• Delay multiply and sum (DMAS) beamformers offer improved contrast and resolution in medical ultrasound.
• DMAS beamformers face challenges with high computational complexity and energy loss.
• Existing methods neglect the autocorrelation component of echo signals, contributing to energy loss.

Purpose of the Study:

• To introduce a novel subarray average delay multiply and sum (SA-DMAS) beamformer.
• To reduce computational complexity while preserving the side lobe suppression of DMAS beamformers.
• To address the energy loss issue in DMAS by incorporating the autocorrelation component.

Main Methods:

• The proposed SA-DMAS beamformer integrates subarray averaging with the DMAS technique.
• Echo signal covariance matrices are estimated using subarray averaging.
• The method incorporates the autocorrelation component of echo signals into a covariance matrix framework.

Main Results:

• The SA-DMAS beamformer achieves a reduced computational complexity of O(9/2L^2), where L is the sub-array size.
• Simulations using point targets and cyst phantoms demonstrated the method's performance.
• Experimental validation using RF data confirmed the feasibility and validity of SA-DMAS.

Conclusions:

• The SA-DMAS beamformer offers a computationally efficient alternative for medical ultrasound imaging.
• It provides performance comparable to Minimum Variance (MV) and DMAS beamformers.
• The method effectively addresses limitations of traditional DMAS, enhancing ultrasound image processing.