A model-based method with joint sparsity constraint for direct diffusion tensor estimation

Yanjie Zhu; Yin Wu; Yuanjie Zheng; Ed X. Wu; Leslie Ying; Dong Liang

doi:10.1109/ISBI.2012.6235597

A model-based method with joint sparsity constraint for direct diffusion tensor estimation

Yanjie Zhu
, Yin Wu
, Yuanjie Zheng
, Ed X. Wu
, Leslie Ying
, Dong Liang

Department of Biomedical Engineering

Shenzhen Institute of Advanced Technology
Chinese Academy of Sciences
University of Pennsylvania
The University of Hong Kong

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

9 Scopus citations

Abstract

Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.

Original language	English
Title of host publication	2012 9th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2012 - Proceedings
Pages	510-513
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2012.6235597
State	Published - 2012
Event	2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Barcelona, Spain Duration: May 2 2012 → May 5 2012

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012
Country/Territory	Spain
City	Barcelona
Period	05/2/12 → 05/5/12

Keywords

Diffusion tensor imaging (DTI)
distributed compressed sensing
joint sparsity constraint
modelbased (MB) method

Access to Document

10.1109/ISBI.2012.6235597

Cite this

Zhu, Y., Wu, Y., Zheng, Y., Wu, E. X., Ying, L., & Liang, D. (2012). A model-based method with joint sparsity constraint for direct diffusion tensor estimation. In 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings (pp. 510-513). Article 6235597 (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2012.6235597

@inproceedings{8428eee7427f48dea6883567caa32aaf,

title = "A model-based method with joint sparsity constraint for direct diffusion tensor estimation",

abstract = "Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.",

keywords = "Diffusion tensor imaging (DTI), distributed compressed sensing, joint sparsity constraint, modelbased (MB) method",

author = "Yanjie Zhu and Yin Wu and Yuanjie Zheng and Wu, \{Ed X.\} and Leslie Ying and Dong Liang",

year = "2012",

doi = "10.1109/ISBI.2012.6235597",

language = "English",

isbn = "9781457718588",

series = "Proceedings - International Symposium on Biomedical Imaging",

pages = "510--513",

booktitle = "2012 9th IEEE International Symposium on Biomedical Imaging",

note = "2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 ; Conference date: 02-05-2012 Through 05-05-2012",

}

Zhu, Y, Wu, Y, Zheng, Y, Wu, EX, Ying, L & Liang, D 2012, A model-based method with joint sparsity constraint for direct diffusion tensor estimation. in 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings., 6235597, Proceedings - International Symposium on Biomedical Imaging, pp. 510-513, 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012, Barcelona, Spain, 05/2/12. https://doi.org/10.1109/ISBI.2012.6235597

A model-based method with joint sparsity constraint for direct diffusion tensor estimation. / Zhu, Yanjie; Wu, Yin; Zheng, Yuanjie et al.
2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings. 2012. p. 510-513 6235597 (Proceedings - International Symposium on Biomedical Imaging).

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

TY - GEN

T1 - A model-based method with joint sparsity constraint for direct diffusion tensor estimation

AU - Zhu, Yanjie

AU - Wu, Yin

AU - Zheng, Yuanjie

AU - Wu, Ed X.

AU - Ying, Leslie

AU - Liang, Dong

PY - 2012

Y1 - 2012

N2 - Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.

AB - Diffusion tensor imaging (DTI) has been widely used for nondestructive characterization of microstructures of myocardium or brain connectivity. It requires repeated acquisition with different diffusion gradients. The long acquisition time greatly limits the clinical application of DTI. In this paper, a novel method, named model-based method with joint sparsity constraint (MB-JSC), effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images in direct estimation of the diffusion tensor from highly undersampled k-space data. Experimental results demonstrate that the proposed method is able to estimate the diffusion tensors more accurately than the existing method when a high net reduction factor is used.

KW - Diffusion tensor imaging (DTI)

KW - distributed compressed sensing

KW - joint sparsity constraint

KW - modelbased (MB) method

UR - https://www.scopus.com/pages/publications/84864853865

U2 - 10.1109/ISBI.2012.6235597

DO - 10.1109/ISBI.2012.6235597

M3 - Conference contribution

AN - SCOPUS:84864853865

SN - 9781457718588

T3 - Proceedings - International Symposium on Biomedical Imaging

SP - 510

EP - 513

BT - 2012 9th IEEE International Symposium on Biomedical Imaging

T2 - 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012

Y2 - 2 May 2012 through 5 May 2012

ER -

A model-based method with joint sparsity constraint for direct diffusion tensor estimation

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this