A sparse reconstruction framework for Fourier-based plane wave imaging

Adrien Besson, Miaomiao Zhang, Francois Varray, Herve Liebgott, Denis Friboulet, Yves Wiaux, Jean-Philippe Thiran, Rafael E. Carrillo, Olivier Bernard

Research output: Contribution to journalArticle

19 Citations (Scopus)
39 Downloads (Pure)

Abstract

Ultrafast imaging based on plane-wave (PW) in- sonification is an active area of research due to its capability of reaching high frame rates. Among PW imaging methods, Fourier-based approaches have demonstrated to be competitive compared to traditional delay and sum methods. Motivated by the success of compressed sensing techniques in other Fourier imaging modalities, like magnetic resonance imaging, we propose a new sparse regularization framework to reconstruct high quality ultrasound images. The framework takes advantage of both the ability to formulate the imaging inverse problem in the Fourier domain and the sparsity of ultrasound images in a sparsifying domain. We show, by means of simulations, in vitro and in vivo data, that the proposed framework significantly reduces image artifacts, i.e. measurement noise and side lobes, compared to classical methods, leading to an increase of the image quality.
Original languageEnglish
Pages (from-to)2092-2106
Number of pages15
JournalIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
Volume63
Issue number12
Early online date4 Oct 2016
DOIs
Publication statusPublished - Dec 2016

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