Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI

Jianwu Li; Jinpeng Zhou; Qiang Tu; Javaria Ikram; Zhengchao Dong

doi:10.1007/978-3-319-46687-3_57

Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI

Jianwu Li^*, Jinpeng Zhou, Qiang Tu, Javaria Ikram, Zhengchao Dong

^*Corresponding author for this work

School of Computer Science and Technology

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

1 Citation (Scopus)

Abstract

We presented new reconstruction algorithms for compressed sensing magnetic resonance imaging (CS-MRI) based on the combination of the fast composite splitting algorithm (FCSA) and complex dual-tree wavelet transform (DT-CWT) and on the combination of FCSA and double density dual-tree wavelet transform (DDDT-DWT), respectively. We applied the bivariate thresholding to these two combinations. The proposed methods not only inherit the effectiveness and fast convergence of FCSA but also improve the sparse representation of both point-like and curve-like features. Experimental results validate the effectiveness and efficiency of the proposed methods.

Original language	English
Title of host publication	Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings
Editors	Kenji Doya, Kazushi Ikeda, Minho Lee, Akira Hirose, Seiichi Ozawa, Derong Liu
Publisher	Springer Verlag
Pages	517-525
Number of pages	9
ISBN (Print)	9783319466866
DOIs	https://doi.org/10.1007/978-3-319-46687-3_57
Publication status	Published - 2016
Event	23rd International Conference on Neural Information Processing, ICONIP 2016 - Kyoto, Japan Duration: 16 Oct 2016 → 21 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9947 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	23rd International Conference on Neural Information Processing, ICONIP 2016
Country/Territory	Japan
City	Kyoto
Period	16/10/16 → 21/10/16

Keywords

Composite splitting
Compressed sensing
Double density dual-tree wavelet
Dual-tree wavelet
MRI

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10.1007/978-3-319-46687-3_57

Cite this

Li, J., Zhou, J., Tu, Q., Ikram, J., & Dong, Z. (2016). Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI. In K. Doya, K. Ikeda, M. Lee, A. Hirose, S. Ozawa, & D. Liu (Eds.), Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings (pp. 517-525). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9947 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46687-3_57

Li, Jianwu ; Zhou, Jinpeng ; Tu, Qiang et al. / Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI. Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. editor / Kenji Doya ; Kazushi Ikeda ; Minho Lee ; Akira Hirose ; Seiichi Ozawa ; Derong Liu. Springer Verlag, 2016. pp. 517-525 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI",

abstract = "We presented new reconstruction algorithms for compressed sensing magnetic resonance imaging (CS-MRI) based on the combination of the fast composite splitting algorithm (FCSA) and complex dual-tree wavelet transform (DT-CWT) and on the combination of FCSA and double density dual-tree wavelet transform (DDDT-DWT), respectively. We applied the bivariate thresholding to these two combinations. The proposed methods not only inherit the effectiveness and fast convergence of FCSA but also improve the sparse representation of both point-like and curve-like features. Experimental results validate the effectiveness and efficiency of the proposed methods.",

keywords = "Composite splitting, Compressed sensing, Double density dual-tree wavelet, Dual-tree wavelet, MRI",

author = "Jianwu Li and Jinpeng Zhou and Qiang Tu and Javaria Ikram and Zhengchao Dong",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 23rd International Conference on Neural Information Processing, ICONIP 2016 ; Conference date: 16-10-2016 Through 21-10-2016",

year = "2016",

doi = "10.1007/978-3-319-46687-3_57",

language = "English",

isbn = "9783319466866",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "517--525",

editor = "Kenji Doya and Kazushi Ikeda and Minho Lee and Akira Hirose and Seiichi Ozawa and Derong Liu",

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Li, J, Zhou, J, Tu, Q, Ikram, J & Dong, Z 2016, Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI. in K Doya, K Ikeda, M Lee, A Hirose, S Ozawa & D Liu (eds), Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9947 LNCS, Springer Verlag, pp. 517-525, 23rd International Conference on Neural Information Processing, ICONIP 2016, Kyoto, Japan, 16/10/16. https://doi.org/10.1007/978-3-319-46687-3_57

Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI. / Li, Jianwu; Zhou, Jinpeng; Tu, Qiang et al.
Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. ed. / Kenji Doya; Kazushi Ikeda; Minho Lee; Akira Hirose; Seiichi Ozawa; Derong Liu. Springer Verlag, 2016. p. 517-525 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9947 LNCS).

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

TY - GEN

T1 - Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI

AU - Li, Jianwu

AU - Zhou, Jinpeng

AU - Tu, Qiang

AU - Ikram, Javaria

AU - Dong, Zhengchao

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - We presented new reconstruction algorithms for compressed sensing magnetic resonance imaging (CS-MRI) based on the combination of the fast composite splitting algorithm (FCSA) and complex dual-tree wavelet transform (DT-CWT) and on the combination of FCSA and double density dual-tree wavelet transform (DDDT-DWT), respectively. We applied the bivariate thresholding to these two combinations. The proposed methods not only inherit the effectiveness and fast convergence of FCSA but also improve the sparse representation of both point-like and curve-like features. Experimental results validate the effectiveness and efficiency of the proposed methods.

AB - We presented new reconstruction algorithms for compressed sensing magnetic resonance imaging (CS-MRI) based on the combination of the fast composite splitting algorithm (FCSA) and complex dual-tree wavelet transform (DT-CWT) and on the combination of FCSA and double density dual-tree wavelet transform (DDDT-DWT), respectively. We applied the bivariate thresholding to these two combinations. The proposed methods not only inherit the effectiveness and fast convergence of FCSA but also improve the sparse representation of both point-like and curve-like features. Experimental results validate the effectiveness and efficiency of the proposed methods.

KW - Composite splitting

KW - Compressed sensing

KW - Double density dual-tree wavelet

KW - Dual-tree wavelet

KW - MRI

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DO - 10.1007/978-3-319-46687-3_57

M3 - Conference contribution

AN - SCOPUS:84992641017

SN - 9783319466866

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 517

EP - 525

BT - Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings

A2 - Doya, Kenji

A2 - Ikeda, Kazushi

A2 - Lee, Minho

A2 - Hirose, Akira

A2 - Ozawa, Seiichi

A2 - Liu, Derong

PB - Springer Verlag

T2 - 23rd International Conference on Neural Information Processing, ICONIP 2016

Y2 - 16 October 2016 through 21 October 2016

ER -

Li J, Zhou J, Tu Q, Ikram J, Dong Z. Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI. In Doya K, Ikeda K, Lee M, Hirose A, Ozawa S, Liu D, editors, Neural Information Processing - 23rd International Conference, ICONIP 2016, Proceedings. Springer Verlag. 2016. p. 517-525. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46687-3_57

Fast dual-tree wavelet composite splitting algorithms for compressed sensing MRI

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