The rise of ultrafast ultrasound imaging-with plane or diverging waves - paved the way to new applications of ultrasound in biomedical applications. However, propagation through complex layers (typically fat, muscle, and bone) hinder considerably the image quality, especially because of sound speed heterogeneities. In difficult-to-image patients, in the case of the hepatic steatosis for instance, a good image and a reliable sound speed quantification are crucial to provide a powerful non-invasive diagnosis tool. In this work, we proposed to adapt the singular value decomposition (SVD) beamformer method for diverging waves and thus present a novel aberration correction approach for widely used curved arrays. We probed its efficiency experimentally bothin vitroandin vivo. Besides the proposed matrix formalism, we explored the physical meaning of the SVD of ultrafast data. Finally, we demonstrated the ability of the technique to improve the image quality and offer new perspectives particularly in quantitative liver imaging.
Keywords: SVD beamformer; aberration correction; diverging waves; singular value decomposition; sound speed.
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