Accelerated exponential parameterization of T2 relaxation with model‐driven low rank and sparsity priors (MORASA)

Xi Peng; Leslie Ying; Yuanyuan Liu; Jing Yuan; Xin Liu; Dong Liang

doi:10.1002/mrm.26083

journal article Jan 13, 2016

Accelerated exponential parameterization of T2 relaxation with model‐driven low rank and sparsity priors (MORASA)

Xi Peng

Leslie Ying Yuanyuan Liu

Jing Yuan

Xin Liu

Dong Liang

Magnetic Resonance in Medicine Vol. 76 No. 6 pp. 1865-1878 · Wiley

View at Publisher Save 10.1002/mrm.26083

Abstract

PurposeThis work is to develop a novel image reconstruction method from highly undersampled multichannel acquisition to reduce the scan time of exponential parameterization of T2 relaxation.Theory and MethodsOn top of the low‐rank and joint‐sparsity constraints, we propose to exploit the linear predictability of the T2 exponential decay to further improve the reconstruction of the T2‐weighted images from undersampled acquisitions. Specifically, the exact rank prior (i.e., number of non‐zero singular values) is adopted to enforce the spatiotemporal low rankness, while the mixed L2–L1 norm of the wavelet coefficients is used to promote joint sparsity, and the Hankel low‐rank approximation is used to impose linear predictability, which integrates the exponential behavior of the temporal signal into the reconstruction process. An efficient algorithm is adopted to solve the reconstruction problem, where corresponding nonlinear filtering operations are performed to enforce corresponding priors in an iterative manner.ResultsBoth simulated and in vivo datasets with multichannel acquisition were used to demonstrate the feasibility of the proposed method. Experimental results have shown that the newly introduced linear predictability prior improves the reconstruction quality of the T2‐weighted images and benefits the subsequent T2 mapping by achieving high‐speed, high‐quality T2 mapping compared with the existing fast T2 mapping methods.ConclusionThis work proposes a novel fast T2 mapping method integrating the linear predictable property of the exponential decay into the reconstruction process. The proposed technique can effectively improve the reconstruction quality of the state‐of‐the‐art fast imaging method exploiting image sparsity and spatiotemporal low rankness. Magn Reson Med 76:1865–1878, 2016. © 2016 International Society for Magnetic Resonance in Medicine

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Details

Published: Jan 13, 2016
Vol/Issue: 76(6)
Pages: 1865-1878
License: View

Authors

X

Xi Peng

Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Shenzhen Guangdong China; Beijing Center for Mathematics and Information Interdisciplinary Sciences Beijing China

L

Leslie Ying

Department of Biomedical Engineering and Department of Electrical Engineering University at Buffalo, The State University of New York Buffalo New York USA

Y

Yuanyuan Liu

Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Shenzhen Guangdong China

J

Jing Yuan

Hong Kong Sanatorium and Hospital Hong Kong China

X

Xin Liu

Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Shenzhen Guangdong China; Beijing Center for Mathematics and Information Interdisciplinary Sciences Beijing China

D

Dong Liang

Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology Shenzhen Guangdong China; Beijing Center for Mathematics and Information Interdisciplinary Sciences Beijing China

Funding

US National Science Foundation Award: CBET-1265612

the National Natural Science Foundation of China Award: 11301508, 81120108012, 81328013, 61471350

the Basic Research Program of Shenzhen Award: JCYJ20150630114942318, JCYJ20140610152828678, JCYJ20140610151856736

Cite This Article

Xi Peng, Leslie Ying, Yuanyuan Liu, et al. (2016). Accelerated exponential parameterization of T2 relaxation with model‐driven low rank and sparsity priors (MORASA). Magnetic Resonance in Medicine, 76(6), 1865-1878. https://doi.org/10.1002/mrm.26083

Accelerated exponential parameterization of T2 relaxation with model‐driven low rank and sparsity priors (MORASA)

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