The l1 measure of image reconstruction subject to motion corrupted k-space data

Cishen Zhang; Zai Yangt; Lihua Xie

doi:10.1109/ICCA.2013.6565201

The l₁ measure of image reconstruction subject to motion corrupted k-space data

Cishen Zhang
, Zai Yangt
, Lihua Xie

Swinburne University of Technology
Nanyang Technological University

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

Abstract

For reconstruction of a nonnegative real valued object based on scanned data in the k-space, it is shown that the l₁ norm of the original motionless object is minimum among that of all objects with combined translational and rotational motions and is a sensitive measure of the object motions. These results provide an insight and theoretical fundamental for applying the l₁ optimization to the motion correction problem for image reconstruction in various practical applications.

Original language	English
Title of host publication	2013 10th IEEE International Conference on Control and Automation, ICCA 2013
Pages	1133-1137
Number of pages	5
DOIs	https://doi.org/10.1109/ICCA.2013.6565201
State	Published - 2013
Externally published	Yes
Event	2013 10th IEEE International Conference on Control and Automation, ICCA 2013 - Hangzhou, China Duration: 12 Jun 2013 → 14 Jun 2013

Publication series

Name	IEEE International Conference on Control and Automation, ICCA
ISSN (Print)	1948-3449
ISSN (Electronic)	1948-3457

Conference

Conference	2013 10th IEEE International Conference on Control and Automation, ICCA 2013
Country/Territory	China
City	Hangzhou
Period	12/06/13 → 14/06/13

Keywords

Image reconstruction
Motion correction
The l norm
k-space data

Access to Document

10.1109/ICCA.2013.6565201

Cite this

@inproceedings{0a6a2c2332cb49c095114fe23eab6487,

title = "The l1 measure of image reconstruction subject to motion corrupted k-space data",

abstract = "For reconstruction of a nonnegative real valued object based on scanned data in the k-space, it is shown that the l1 norm of the original motionless object is minimum among that of all objects with combined translational and rotational motions and is a sensitive measure of the object motions. These results provide an insight and theoretical fundamental for applying the l1 optimization to the motion correction problem for image reconstruction in various practical applications.",

keywords = "Image reconstruction, Motion correction, The l norm, k-space data",

author = "Cishen Zhang and Zai Yangt and Lihua Xie",

year = "2013",

doi = "10.1109/ICCA.2013.6565201",

language = "英语",

isbn = "9781467347075",

series = "IEEE International Conference on Control and Automation, ICCA",

pages = "1133--1137",

booktitle = "2013 10th IEEE International Conference on Control and Automation, ICCA 2013",

note = "2013 10th IEEE International Conference on Control and Automation, ICCA 2013 ; Conference date: 12-06-2013 Through 14-06-2013",

}

Zhang, C, Yangt, Z & Xie, L 2013, The l₁ measure of image reconstruction subject to motion corrupted k-space data. in 2013 10th IEEE International Conference on Control and Automation, ICCA 2013., 6565201, IEEE International Conference on Control and Automation, ICCA, pp. 1133-1137, 2013 10th IEEE International Conference on Control and Automation, ICCA 2013, Hangzhou, China, 12/06/13. https://doi.org/10.1109/ICCA.2013.6565201

The l₁ measure of image reconstruction subject to motion corrupted k-space data. / Zhang, Cishen; Yangt, Zai; Xie, Lihua.
2013 10th IEEE International Conference on Control and Automation, ICCA 2013. 2013. p. 1133-1137 6565201 (IEEE International Conference on Control and Automation, ICCA).

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

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AU - Yangt, Zai

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AB - For reconstruction of a nonnegative real valued object based on scanned data in the k-space, it is shown that the l1 norm of the original motionless object is minimum among that of all objects with combined translational and rotational motions and is a sensitive measure of the object motions. These results provide an insight and theoretical fundamental for applying the l1 optimization to the motion correction problem for image reconstruction in various practical applications.

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KW - Motion correction

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