Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Adrien Besson; Rafael E Carrillo; Olivier Bernard; Yves Wiaux; Jean-Philippe Thiran

doi:10.1109/ICIP.2016.7532811

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Adrien Besson, Rafael E Carrillo, Olivier Bernard, Yves Wiaux, Jean-Philippe Thiran

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

26 Citations (Scopus)

124 Downloads (Pure)

Abstract

The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with promising results, practical implementations are hard to achieve due to the impossibility to mimic random sampling on a US probe and to the high memory requirements of the measurement model. In this paper, we propose a CS framework for US imaging based on an easily implementable acquisition scheme and on a delay-and-sum measurement model.

Original language	English
Title of host publication	2016 IEEE International Conference on Image Processing (ICIP)
Publisher	IEEE
Pages	2509-2513
Number of pages	5
ISBN (Print)	9781467399616
DOIs	https://doi.org/10.1109/ICIP.2016.7532811
Publication status	Published - 19 Aug 2016
Event	23rd IEEE International Conference on Image Processing - Phoenix Convention Center, Phoenix, United States Duration: 25 Sept 2016 → 28 Sept 2016

Conference

Conference	23rd IEEE International Conference on Image Processing
Abbreviated title	ICIP 2016
Country/Territory	United States
City	Phoenix
Period	25/09/16 → 28/09/16

Access to Document

10.1109/ICIP.2016.7532811

Download pdfAccepted author manuscript, 658 KB

Cite this

@inproceedings{d3af24ac1f1a457f99781f5fb14031f2,

title = "Compressed delay-and-sum beamforming for ultrafast ultrasound imaging",

abstract = "The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with promising results, practical implementations are hard to achieve due to the impossibility to mimic random sampling on a US probe and to the high memory requirements of the measurement model. In this paper, we propose a CS framework for US imaging based on an easily implementable acquisition scheme and on a delay-and-sum measurement model.",

author = "Adrien Besson and Carrillo, {Rafael E} and Olivier Bernard and Yves Wiaux and Jean-Philippe Thiran",

year = "2016",

month = aug,

day = "19",

doi = "10.1109/ICIP.2016.7532811",

language = "English",

isbn = "9781467399616",

pages = "2509--2513",

booktitle = "2016 IEEE International Conference on Image Processing (ICIP)",

publisher = "IEEE",

address = "United States",

note = "23rd IEEE International Conference on Image Processing, ICIP 2016 ; Conference date: 25-09-2016 Through 28-09-2016",

}

TY - GEN

T1 - Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

AU - Besson, Adrien

AU - Carrillo, Rafael E

AU - Bernard, Olivier

AU - Wiaux, Yves

AU - Thiran, Jean-Philippe

PY - 2016/8/19

Y1 - 2016/8/19

N2 - The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with promising results, practical implementations are hard to achieve due to the impossibility to mimic random sampling on a US probe and to the high memory requirements of the measurement model. In this paper, we propose a CS framework for US imaging based on an easily implementable acquisition scheme and on a delay-and-sum measurement model.

AB - The theory of compressed sensing (CS) leverages upon structure of signals in order to reduce the number of samples needed to reconstruct a signal, compared to the Nyquist rate. Although CS approaches have been proposed for ultrasound (US) imaging with promising results, practical implementations are hard to achieve due to the impossibility to mimic random sampling on a US probe and to the high memory requirements of the measurement model. In this paper, we propose a CS framework for US imaging based on an easily implementable acquisition scheme and on a delay-and-sum measurement model.

UR - http://www.scopus.com/inward/record.url?scp=85006791235&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2016.7532811

DO - 10.1109/ICIP.2016.7532811

M3 - Conference contribution

SN - 9781467399616

SP - 2509

EP - 2513

BT - 2016 IEEE International Conference on Image Processing (ICIP)

PB - IEEE

T2 - 23rd IEEE International Conference on Image Processing

Y2 - 25 September 2016 through 28 September 2016

ER -

Compressed delay-and-sum beamforming for ultrafast ultrasound imaging

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this