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1 IRIT - Institut de recherche en informatique de Toulouse

Abstract : Beamforming BF in ultrasound US imaging has significant impact on the quality of the final image, controlling its resolution and contrast. Despite its low spatial resolution and contrast, delay-and-sum DAS is still extensively used nowadays in clinical applications, due to its real-time capabilities. The most common alternatives are minimum variance MV method and its variants, which overcome the drawbacks of DAS, at the cost of higher computational complexity that limits its utilization in real-time applications. In this paper, we propose to perform BF in US imaging through a regularized inverse problem based on a linear model relating the reflected echoes to the signal to be recovered. Our approach presents two major advantages: 1 its flexibility in the choice of statistical assumptions on the signal to be beamformed Laplacian and Gaussian statistics are tested herein and 2 its robustness to a reduced number of pulse emissions. The proposed framework is flexible and allows for choosing the right tradeoff between noise suppression and sharpness of the resulted image. We illustrate the performance of our approach on both simulated and experimental data, with in vivo examples of carotid and thyroid. Compared with DAS, MV, and two other recently published BF techniques, our method offers better spatial resolution, respectively contrast, when using Laplacian and Gaussian priors.

Keywords : Linear inverse problems Adaptive beamforming BF Basis pursuit BP Beamspace processing Least squares LS





Autor: Teodora Szasz - Adrian Basarab - Denis Kouamé -

Fuente: https://hal.archives-ouvertes.fr/



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