Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction.

Details

Serval ID
serval:BIB_E7B58839A7E1
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction.
Journal
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Author(s)
Besson A., Perdios D., Martinez F., Chen Z., Carrillo R.E., Arditi M., Wiaux Y., Thiran J.P.
ISSN
1525-8955 (Electronic)
ISSN-L
0885-3010
Publication state
Published
Issued date
03/2018
Peer-reviewed
Oui
Volume
65
Number
3
Pages
339-355
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution to the image reconstruction problem. An alternative to DAS consists in using iterative techniques, which require both an accurate measurement model and a strong prior on the image under scrutiny. Toward this goal, much effort has been deployed in formulating models for US imaging, which usually require a large amount of memory to store the matrix coefficients. We present two different techniques, which take advantage of fast and matrix-free formulations derived for the measurement model and its adjoint, and rely on sparsity of US images in well-chosen models. Sparse regularization is used for enhanced image reconstruction. Compressed beamforming exploits the compressed sensing framework to restore high-quality images from fewer raw data than state-of-the-art approaches. Using simulated data and in vivo experimental acquisitions, we show that the proposed approach is three orders of magnitude faster than non-DAS state-of-the-art methods, with comparable or better image quality.

Pubmed
Web of science
Create date
26/03/2018 16:47
Last modification date
20/08/2019 16:10
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