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    New Fourier-domain beamformers improve ultrasound image quality by enhancing contrast and reducing noise. These methods offer faster computation than traditional dynamic receive focusing (DRF) for convex probes.

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    Area of Science:

    • Medical Imaging
    • Ultrasound Technology
    • Signal Processing

    Background:

    • Convex probes are essential for deep abdominal imaging, offering wide fields of view.
    • Ultrafast ultrasound imaging utilizes broader wavefronts like plane and spherical waves.
    • Current methods using convex arrays and spherical wavefronts suffer from suboptimal image quality due to a lack of transmit focus.

    Purpose of the Study:

    • To develop novel Fourier-domain beamformers for non-steered and steered diverging wave imaging with convex probes.
    • To improve image quality, specifically contrast and contrast-to-noise ratio (CNR), in ultrasound imaging.
    • To evaluate the computational efficiency of the proposed methods compared to dynamic receive focusing (DRF).

    Main Methods:

    • Proposed two novel Fourier-domain beamformers (vs1 and vs2) for non-steered diverging wave imaging.
    • Developed an explicit interpolation scheme for virtual-source-based steered diverging wave imaging.
    • Evaluated performance using simulations, phantom experiments, ex vivo bovine heart imaging, and in vivo human liver imaging.

    Main Results:

    • The proposed Fourier-domain beamformers (vs1, vs2) demonstrated superior contrast and resolution compared to DRF.
    • Significant CNR improvements were observed: up to 6.7 dB in vitro, 8.4 dB ex vivo, and 6.7 dB in vivo.
    • Computation time was reduced by 2-73 times for vs1 and 4-216 times for vs2 compared to DRF.

    Conclusions:

    • The novel Fourier-domain beamformers significantly enhance ultrasound image quality for convex probes.
    • These methods provide substantial improvements in contrast and CNR with reduced computational cost.
    • The proposed techniques offer a promising advancement for clinical abdominal and liver imaging.