Journal article
Accelerated exponential parameterization of T2 relaxation with model-driven low rank and sparsity priors (MORASA)
Magnetic resonance in medicine, Vol.76(6), pp.1865-1878
12/2016
DOI: 10.1002/mrm.26083
PMID: 26762702
Abstract
This 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.
On 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.
Both 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.
This 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.
Details
- Title: Subtitle
- Accelerated exponential parameterization of T2 relaxation with model-driven low rank and sparsity priors (MORASA)
- Creators
- Xi Peng - Beijing Center for Mathematics and Information Interdisciplinary Sciences, Beijing, ChinaLeslie Ying - University at Buffalo, State University of New YorkYuanyuan Liu - Shenzhen Institutes of Advanced TechnologyJing Yuan - Hong Kong Sanatorium and HospitalXin Liu - Shenzhen Institutes of Advanced TechnologyDong Liang - National Center for Mathematics and Interdisciplinary Sciences
- Resource Type
- Journal article
- Publication Details
- Magnetic resonance in medicine, Vol.76(6), pp.1865-1878
- DOI
- 10.1002/mrm.26083
- PMID
- 26762702
- ISSN
- 0740-3194
- eISSN
- 1522-2594
- Grant note
- DOI: 10.13039/501100001809, name: the National Natural Science Foundation of China, award: 11301508, 81120108012, 81328013, 61471350; DOI: 10.13039/501100003453, name: the Natural Science Foundation of Guangdong, award: 2015A020214019, 2015A030310314, 2015A030313740; name: the Basic Research Program of Shenzhen, award: JCYJ20150630114942318, JCYJ20140610152828678, JCYJ20140610151856736; name: US National Science Foundation, award: CBET-1265612
- Language
- English
- Date published
- 12/2016
- Academic Unit
- Radiology
- Record Identifier
- 9984446400402771
Metrics
19 Record Views