Ultrasound image reconstruction from compressed measurements using approximate message passing

J. H. Kim; A. Basarab; P. R. Hill; D. R. Bull; D. Kouamé; A. Achim

doi:10.1109/EUSIPCO.2016.7760310

Ultrasound image reconstruction from compressed measurements using approximate message passing

J. H. Kim, A. Basarab, P. R. Hill, D. R. Bull, D. Kouamé, A. Achim

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

7 Citations (Scopus)

379 Downloads (Pure)

Abstract

In this paper we propose a novel framework for compressive sampling reconstruction of biomedical ultrasonic images based on the Approximate Message Passing (AMP) algorithm. AMP is an iterative algorithm that performs image reconstruction through image denoising within a compressive sampling framework. In this work, our aim is to evaluate the merits of several combinations of a denoiser and a transform domain, which are the two main factors that determine the recovery performance. In particular, we investigate reconstruction performance in the spatial, DCT, and wavelet domains. We compare the results with existing reconstruction algorithms already used in ultrasound imaging and quantify the performance improvement.

Original language	English
Title of host publication	2016 24th European Signal Processing Conference, EUSIPCO 2016
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	557-561
Number of pages	5
ISBN (Electronic)	9780992862657
DOIs	https://doi.org/10.1109/EUSIPCO.2016.7760310
Publication status	Published - 1 Dec 2016
Event	24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary Duration: 28 Aug 2016 → 2 Sept 2016

Conference

Conference	24th European Signal Processing Conference, EUSIPCO 2016
Country/Territory	Hungary
City	Budapest
Period	28/08/16 → 2/09/16

Keywords

AMP
Compressive sampling
Image denoising
IRLS
Nonconvex optimization
Ultrasonic images

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title = "Ultrasound image reconstruction from compressed measurements using approximate message passing",

abstract = "In this paper we propose a novel framework for compressive sampling reconstruction of biomedical ultrasonic images based on the Approximate Message Passing (AMP) algorithm. AMP is an iterative algorithm that performs image reconstruction through image denoising within a compressive sampling framework. In this work, our aim is to evaluate the merits of several combinations of a denoiser and a transform domain, which are the two main factors that determine the recovery performance. In particular, we investigate reconstruction performance in the spatial, DCT, and wavelet domains. We compare the results with existing reconstruction algorithms already used in ultrasound imaging and quantify the performance improvement.",

keywords = "AMP, Compressive sampling, Image denoising, IRLS, Nonconvex optimization, Ultrasonic images",

author = "Kim, {J. H.} and A. Basarab and Hill, {P. R.} and Bull, {D. R.} and D. Kouam{\'e} and A. Achim",

year = "2016",

month = dec,

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doi = "10.1109/EUSIPCO.2016.7760310",

language = "English",

pages = "557--561",

booktitle = "2016 24th European Signal Processing Conference, EUSIPCO 2016",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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note = "24th European Signal Processing Conference, EUSIPCO 2016 ; Conference date: 28-08-2016 Through 02-09-2016",

}

Kim, JH, Basarab, A, Hill, PR , Bull, DR, Kouamé, D & Achim, A 2016, Ultrasound image reconstruction from compressed measurements using approximate message passing. in 2016 24th European Signal Processing Conference, EUSIPCO 2016. Institute of Electrical and Electronics Engineers (IEEE), pp. 557-561, 24th European Signal Processing Conference, EUSIPCO 2016, Budapest, Hungary, 28/08/16. https://doi.org/10.1109/EUSIPCO.2016.7760310

Ultrasound image reconstruction from compressed measurements using approximate message passing. / Kim, J. H.; Basarab, A.; Hill, P. R. et al.
2016 24th European Signal Processing Conference, EUSIPCO 2016. Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 557-561.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Ultrasound image reconstruction from compressed measurements using approximate message passing

AU - Kim, J. H.

AU - Basarab, A.

AU - Hill, P. R.

AU - Bull, D. R.

AU - Kouamé, D.

AU - Achim, A.

PY - 2016/12/1

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N2 - In this paper we propose a novel framework for compressive sampling reconstruction of biomedical ultrasonic images based on the Approximate Message Passing (AMP) algorithm. AMP is an iterative algorithm that performs image reconstruction through image denoising within a compressive sampling framework. In this work, our aim is to evaluate the merits of several combinations of a denoiser and a transform domain, which are the two main factors that determine the recovery performance. In particular, we investigate reconstruction performance in the spatial, DCT, and wavelet domains. We compare the results with existing reconstruction algorithms already used in ultrasound imaging and quantify the performance improvement.

AB - In this paper we propose a novel framework for compressive sampling reconstruction of biomedical ultrasonic images based on the Approximate Message Passing (AMP) algorithm. AMP is an iterative algorithm that performs image reconstruction through image denoising within a compressive sampling framework. In this work, our aim is to evaluate the merits of several combinations of a denoiser and a transform domain, which are the two main factors that determine the recovery performance. In particular, we investigate reconstruction performance in the spatial, DCT, and wavelet domains. We compare the results with existing reconstruction algorithms already used in ultrasound imaging and quantify the performance improvement.

KW - AMP

KW - Compressive sampling

KW - Image denoising

KW - IRLS

KW - Nonconvex optimization

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M3 - Conference Contribution (Conference Proceeding)

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BT - 2016 24th European Signal Processing Conference, EUSIPCO 2016

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T2 - 24th European Signal Processing Conference, EUSIPCO 2016

Y2 - 28 August 2016 through 2 September 2016

ER -

Ultrasound image reconstruction from compressed measurements using approximate message passing

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