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Non‐iterative reconstruction with a prior for undersampled radial MRI data
Author(s) -
Zeng Gengsheng L.,
Li Ya,
DiBella Edward V. R.
Publication year - 2013
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22036
Subject(s) - undersampling , computer science , iterative method , compressed sensing , algorithm , iterative reconstruction , aliasing , bayesian probability , dimension (graph theory) , fourier transform , mathematical optimization , artificial intelligence , mathematics , mathematical analysis , pure mathematics
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 Fourier–Bayesian 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 Fourier–Bayesian technique over the iterative techniques is its fast computation time and its ability to reach the optimal solution. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 53–58, 2013.