Plane wave imaging (PWI) has significantly advanced ultrasound diagnostics by enabling high frame rates and real-time capabilities critical for applications such as cardiac imaging and elastography. However, its clinical utility remains constrained by inherent trade-offs between spatial resolution, contrast, and frame rate, particularly when using a limited number of transmissions. Existing solutions, such as pixel-level apodization or angle-dependent transmit apodization (ADTA), either impose prohibitive computational costs or restrict adaptability to small fields of view (FOV). To address these limitations, we propose a genetic algorithm (GA)-based framework for depth-dependent transmit apodization optimization in PWI. Our approach models the spatial contribution of each plane-wave transmission via a continuous parametric function, reducing the optimization dimensionality. The multi-objective GA simultaneously minimizes the full width at half maximum (FWHM) and peak sidelobe level (PSL), achieving resolution enhancement and artifact suppression across the entire FOV. Experimental validation using a Verasonics Vantage 256 system and an L74 linear probe on a tissue-mimicking phantom demonstrates the feasibility of the approach using only seven steered transmissions.
Genetic Algorithm-Optimized Apodization for Ultrafast Plane-Wave Compounding
Alzein Z.;Caviglia D. D.
2025-01-01
Abstract
Plane wave imaging (PWI) has significantly advanced ultrasound diagnostics by enabling high frame rates and real-time capabilities critical for applications such as cardiac imaging and elastography. However, its clinical utility remains constrained by inherent trade-offs between spatial resolution, contrast, and frame rate, particularly when using a limited number of transmissions. Existing solutions, such as pixel-level apodization or angle-dependent transmit apodization (ADTA), either impose prohibitive computational costs or restrict adaptability to small fields of view (FOV). To address these limitations, we propose a genetic algorithm (GA)-based framework for depth-dependent transmit apodization optimization in PWI. Our approach models the spatial contribution of each plane-wave transmission via a continuous parametric function, reducing the optimization dimensionality. The multi-objective GA simultaneously minimizes the full width at half maximum (FWHM) and peak sidelobe level (PSL), achieving resolution enhancement and artifact suppression across the entire FOV. Experimental validation using a Verasonics Vantage 256 system and an L74 linear probe on a tissue-mimicking phantom demonstrates the feasibility of the approach using only seven steered transmissions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



