A compressed beamforming framework for ultrafast ultrasound imaging

Adrien Besson, Rafael E Carrillo, Dimitris Perdios, Marcel Arditi, Olivier Bernard, Yves Wiaux, Jean-Philippe Thiran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Classical beamforming methods, based on Delay- And-Sum (DAS) require an extensive number of samples and delay calculations to obtain high-quality images. Compressed Beamforming (CB) proposes an alternative to DAS, based on compressed sensing, which aims at reducing the data rate. However, proposed CB approaches induce a computationally heavy measurement model that hampers their attractiveness for iterative image reconstruction. In this paper, a CB framework, applicable to either radio-frequency or in-phase quadrature data and for both plane wave and diverging wave compounding, is described. The proposed framework exploits a computationally light measurement model which leads to tractable reconstruction. It solves a convex problem and assumes sparsity in a wavelet- based model to achieve high-quality image reconstruction from measurements acquired with only few transducer elements.
Original languageEnglish
Title of host publicationIUS Proceedings 2016
Number of pages4
Publication statusPublished - 2016
Event2016 IEEE International Ultrasonics Symposium - VINCI Convention Center, Tours, France
Duration: 18 Sept 201621 Sept 2016


Conference2016 IEEE International Ultrasonics Symposium
Abbreviated titleIUS 2016


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