Non-iterative reconstruction with a prior for undersampled radial MRI data

作者：Zeng Gengsheng L^*; Li Ya; DiBella Edward V R

来源：International Journal of Imaging Systems and Technology, 2013, 23(1): 53-58.

DOI：10.1002/ima.22036

• constrained image reconstruction
• analytical reconstruction algorithm
• tomography
• undersampled MRI
• radial sampled MRI

This paper develops an FBP-MAP (filtered backprojection, maximum a posteriori) algorithm to reconstruct MRI images from undersampled data. An objective function is first set up for the MRI reconstruction problem with a data fidelity term and a Bayesian term. The Bayesian term is a constraint in the temporal dimension. This objective function is minimized using the calculus of variations. The proposed algorithm is non-iterative. Undersampled dynamic myocardial perfusion MRI data were used to test the feasibility of the proposed technique. It is shown that the non-iterative FourierBayesian reconstruction method effectively incorporates the temporal constraint and significantly reduces the angular aliasing artifacts caused by undersampling. A significant advantage of the proposed non-iterative FourierBayesian technique over the iterative techniques is its fast computation time and its ability to reach the optimal solution.

• 出版日期2013-3