Joint reconstruction of noisy high-resolution MR image sequences

Justin P. Haldar; Zhi Pei Liang

doi:10.1109/ISBI.2008.4541105

Joint reconstruction of noisy high-resolution MR image sequences

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

Abstract

Quantitative MR studies often utilize sequences of coregistered images, where the contrast in each image frame is experimentally manipulated to enable the regression of important physical parameters. However, the potential of these experiments has been limited for high-resolution biological studies because of long acquisition times and limited signal-tonoise ratio. This work presents a new approach for the reconstruction of an image sequence from noisy data, using a statistical model that incorporates an implicit line-site prior to take advantage of the high level of inter-frame correlation between spatial image features. Reconstructions are efficiently computed using a globally-convergent half-quadratic iterative algorithm, and the proposed optimization procedure enables precise characterization of resolution and noise properties.

Original language	English (US)
Title of host publication	2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, Proceedings, ISBI
Pages	752-755
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2008.4541105
State	Published - Sep 10 2008
Event	2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France Duration: May 14 2008 → May 17 2008

Publication series

Name	2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Other

Other	2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Country	France
City	Paris
Period	5/14/08 → 5/17/08

Keywords

Denoising
Half-quadratic regularization
Image reconstruction
Image sequences
Magnetic resonance imaging

ASJC Scopus subject areas

Biomedical Engineering

Access to Document

10.1109/ISBI.2008.4541105

Fingerprint Dive into the research topics of 'Joint reconstruction of noisy high-resolution MR image sequences'. Together they form a unique fingerprint.

Cite this

Haldar, J. P., & Liang, Z. P. (2008). Joint reconstruction of noisy high-resolution MR image sequences. In 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI (pp. 752-755). [4541105] (2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI). https://doi.org/10.1109/ISBI.2008.4541105

Joint reconstruction of noisy high-resolution MR image sequences. / Haldar, Justin P.; Liang, Zhi Pei.

2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI. 2008. p. 752-755 4541105 (2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI).

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

Haldar, JP & Liang, ZP 2008, Joint reconstruction of noisy high-resolution MR image sequences. in 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI., 4541105, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI, pp. 752-755, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI, Paris, France, 5/14/08. https://doi.org/10.1109/ISBI.2008.4541105

@inproceedings{aa2cc3b7171b4ebe8995e3627887cdf0,

title = "Joint reconstruction of noisy high-resolution MR image sequences",

abstract = "Quantitative MR studies often utilize sequences of coregistered images, where the contrast in each image frame is experimentally manipulated to enable the regression of important physical parameters. However, the potential of these experiments has been limited for high-resolution biological studies because of long acquisition times and limited signal-tonoise ratio. This work presents a new approach for the reconstruction of an image sequence from noisy data, using a statistical model that incorporates an implicit line-site prior to take advantage of the high level of inter-frame correlation between spatial image features. Reconstructions are efficiently computed using a globally-convergent half-quadratic iterative algorithm, and the proposed optimization procedure enables precise characterization of resolution and noise properties.",

keywords = "Denoising, Half-quadratic regularization, Image reconstruction, Image sequences, Magnetic resonance imaging",

author = "Haldar, {Justin P.} and Liang, {Zhi Pei}",

year = "2008",

month = sep,

day = "10",

doi = "10.1109/ISBI.2008.4541105",

language = "English (US)",

isbn = "9781424420032",

series = "2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI",

pages = "752--755",

booktitle = "2008 5th IEEE International Symposium on Biomedical Imaging",

note = "2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI ; Conference date: 14-05-2008 Through 17-05-2008",

}

TY - GEN

T1 - Joint reconstruction of noisy high-resolution MR image sequences

AU - Haldar, Justin P.

AU - Liang, Zhi Pei

PY - 2008/9/10

Y1 - 2008/9/10

N2 - Quantitative MR studies often utilize sequences of coregistered images, where the contrast in each image frame is experimentally manipulated to enable the regression of important physical parameters. However, the potential of these experiments has been limited for high-resolution biological studies because of long acquisition times and limited signal-tonoise ratio. This work presents a new approach for the reconstruction of an image sequence from noisy data, using a statistical model that incorporates an implicit line-site prior to take advantage of the high level of inter-frame correlation between spatial image features. Reconstructions are efficiently computed using a globally-convergent half-quadratic iterative algorithm, and the proposed optimization procedure enables precise characterization of resolution and noise properties.

AB - Quantitative MR studies often utilize sequences of coregistered images, where the contrast in each image frame is experimentally manipulated to enable the regression of important physical parameters. However, the potential of these experiments has been limited for high-resolution biological studies because of long acquisition times and limited signal-tonoise ratio. This work presents a new approach for the reconstruction of an image sequence from noisy data, using a statistical model that incorporates an implicit line-site prior to take advantage of the high level of inter-frame correlation between spatial image features. Reconstructions are efficiently computed using a globally-convergent half-quadratic iterative algorithm, and the proposed optimization procedure enables precise characterization of resolution and noise properties.

KW - Denoising

KW - Half-quadratic regularization

KW - Image reconstruction

KW - Image sequences

KW - Magnetic resonance imaging

UR - http://www.scopus.com/inward/record.url?scp=51049095896&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=51049095896&partnerID=8YFLogxK

U2 - 10.1109/ISBI.2008.4541105

DO - 10.1109/ISBI.2008.4541105

M3 - Conference contribution

AN - SCOPUS:51049095896

SN - 9781424420032

T3 - 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

SP - 752

EP - 755

BT - 2008 5th IEEE International Symposium on Biomedical Imaging

T2 - 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI

Y2 - 14 May 2008 through 17 May 2008

ER -