Incorporating reference in parallel imaging and compressed sensing.
OBJECTIVE
To develop a new compressed sensing parallel imaging technique called READ-PICS that can effectively incorporate prior information from a reference scan for MR image reconstruction from highly undersampled multichannel measurements.


METHODS
READ-PICS incorporates information from a high-spatial-resolution reference prior using the generalized series model, to achieve increased image sparsity and mitigated noise amplification simultaneously. To further improve the ill-conditioning of the parallel imaging system, an annular area in the central residual k-space is used for calibration. Additionally, the mixed L1-L2 norm of the coefficients from the prior component and residual component is used to enforce joint sparsity.


RESULTS
The evaluations on parametric imaging and multiscan experiment demonstrate superior performance of READ-PICS in terms of detail preservation and noise suppression compared to state-of-the-art technique, L1-Iterative self-consistent parallel imaging reconstruction, and prescan required method, correlation imaging.


CONCLUSIONS
The proposed method can significantly increase signal sparsity and improve the ill-conditioning of the parallel imaging system using reference adaptive regularization. This technique can be easily adapted to other imaging applications where multiple images need to be acquired sequentially and a reference prior is also available.
Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Shenzhen, Guangdong, 518055, China; Beijing Center for Mathematics and Information Interdisciplinary Sciences, Beijing, 100048, China; Shenzhen Key Laboratory for MRI, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China.
Xi
X
Peng
Leslie
L
Ying
Qiegen
Q
Liu
Yanjie
Y
Zhu
Yuanyuan
Y
Liu
Xiaobo
X
Qu
Xin
X
Liu
Hairong
H
Zheng
Dong
D
Liang
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
compressed sensing; generalized series; parallel imaging; reference adaptive regularization