SCOPE: signal compensation for low-rank plus sparse matrix decomposition for fast parameter mapping.

SCOPE: signal compensation for low-rank plus sparse matrix decomposition for fast parameter mapping.
Phys Med Biol. 2018 Aug 17;:
Authors: Zhu Y, Liu Y, Ying L, Peng X, Wang YJ, Yuan J, Liu X, Liang D
Abstract
Magnetic resonance (MR) parameter mapping is useful for many clinical applications. However, its practical utility is limited by the long scan time. To address this problem, this paper developed a novel image reconstruction method for fast MR parameter mapping. The proposed method (SCOPE) used a low-rank plus sparse model to reconstruct the parameter-weighted images from highly undersampled acquisitions. A signal compensation strategy was introduced to promote low rankness along the parametric direction and thus improve the reconstruction accuracy. Specifically, compensation was performed by multiplying the original signal by the inversion of the mono-exponential decay at each voxel. The performance of SCOPE was evaluated via quantitative T1ρ mapping. The results of the simulation and in vivo experiments with acceleration factors from 3 to 5 are shown. The performance of SCOPE was verified via comparisons with several low-rank and sparsity-based methods. The experimental results showed that the T1ρ maps obtained using SCOPE were more accurate than those obtained using competing methods and were comparable to the reference, even when the acceleration factor reached 5. SCOPE can greatly reduce the scan time of parameter mapping...

Source: Physics in Medicine and Biology - August 17, 2018 Category: Physics Authors: Zhu Y, Liu Y, Ying L, Peng X, Wang YJ, Yuan J, Liu X, Liang D Tags: Phys Med Biol Source Type: research