Morphological component analysis for sparse regularization in plane wave imaging

Adrien Besson; Rafael E. Carrillo; Dimitris Perdios; Eric F. Bezzam; Marcel Arditi; Yves Wiaux; Jean-Philippe Thiran

doi:10.1109/ULTSYM.2016.7728896

Morphological component analysis for sparse regularization in plane wave imaging

Adrien Besson, Rafael E. Carrillo, Dimitris Perdios, Eric F. Bezzam, Marcel Arditi, Yves Wiaux, Jean-Philippe Thiran

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

60 Downloads (Pure)

Abstract

Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-posed problem resulting from the acoustic wave propagation. In the following work, a new sparse regularization method is proposed which includes a component-based modelling of the radio-frequency images as well as a point-spread-function-adaptive sparsity prior. The proposed method, evaluated on the PICMUS dataset,outperforms the classical DAS in terms of contrast and resolution.

Original language	English
Title of host publication	2016 IEEE International Ultrasonics Symposium (IUS)
Publisher	IEEE
ISBN (Electronic)	9781467398978
DOIs	https://doi.org/10.1109/ULTSYM.2016.7728896
Publication status	Published - 3 Nov 2016
Event	2016 IEEE International Ultrasonics Symposium - VINCI Convention Center, Tours, France Duration: 18 Sept 2016 → 21 Sept 2016

Publication series

Name	IEEE International Ultrasonics Symposium : proceedings
Publisher	IEEE
ISSN (Print)	1948-5727

Conference

Conference	2016 IEEE International Ultrasonics Symposium
Abbreviated title	IUS 2016
Country/Territory	France
City	Tours
Period	18/09/16 → 21/09/16

Keywords

Compressed sensing
Plane wave
Sparse regularization

ASJC Scopus subject areas

Acoustics and Ultrasonics

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10.1109/ULTSYM.2016.7728896

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Cite this

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title = "Morphological component analysis for sparse regularization in plane wave imaging",

abstract = "Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-posed problem resulting from the acoustic wave propagation. In the following work, a new sparse regularization method is proposed which includes a component-based modelling of the radio-frequency images as well as a point-spread-function-adaptive sparsity prior. The proposed method, evaluated on the PICMUS dataset,outperforms the classical DAS in terms of contrast and resolution.",

keywords = "Compressed sensing, Plane wave, Sparse regularization",

author = "Adrien Besson and Carrillo, {Rafael E.} and Dimitris Perdios and Bezzam, {Eric F.} and Marcel Arditi and Yves Wiaux and Jean-Philippe Thiran",

year = "2016",

month = nov,

day = "3",

doi = "10.1109/ULTSYM.2016.7728896",

language = "English",

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publisher = "IEEE",

booktitle = "2016 IEEE International Ultrasonics Symposium (IUS)",

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note = "2016 IEEE International Ultrasonics Symposium, IUS 2016 ; Conference date: 18-09-2016 Through 21-09-2016",

}

Besson, A, Carrillo, RE, Perdios, D, Bezzam, EF, Arditi, M, Wiaux, Y & Thiran, J-P 2016, Morphological component analysis for sparse regularization in plane wave imaging. in 2016 IEEE International Ultrasonics Symposium (IUS)., 7728896, IEEE International Ultrasonics Symposium : proceedings, IEEE, 2016 IEEE International Ultrasonics Symposium, Tours, France, 18/09/16. https://doi.org/10.1109/ULTSYM.2016.7728896

TY - GEN

T1 - Morphological component analysis for sparse regularization in plane wave imaging

AU - Besson, Adrien

AU - Carrillo, Rafael E.

AU - Perdios, Dimitris

AU - Bezzam, Eric F.

AU - Arditi, Marcel

AU - Wiaux, Yves

AU - Thiran, Jean-Philippe

PY - 2016/11/3

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N2 - Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-posed problem resulting from the acoustic wave propagation. In the following work, a new sparse regularization method is proposed which includes a component-based modelling of the radio-frequency images as well as a point-spread-function-adaptive sparsity prior. The proposed method, evaluated on the PICMUS dataset,outperforms the classical DAS in terms of contrast and resolution.

AB - Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-posed problem resulting from the acoustic wave propagation. In the following work, a new sparse regularization method is proposed which includes a component-based modelling of the radio-frequency images as well as a point-spread-function-adaptive sparsity prior. The proposed method, evaluated on the PICMUS dataset,outperforms the classical DAS in terms of contrast and resolution.

KW - Compressed sensing

KW - Plane wave

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M3 - Conference contribution

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T3 - IEEE International Ultrasonics Symposium : proceedings

BT - 2016 IEEE International Ultrasonics Symposium (IUS)

PB - IEEE

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Y2 - 18 September 2016 through 21 September 2016

ER -

Morphological component analysis for sparse regularization in plane wave imaging

Abstract

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Keywords

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