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- Title
Iterative 3D projection reconstruction of <sup>23</sup>Na data with an <sup>1</sup>H MRI constraint.
- Authors
Gnahm, Christine; Bock, Michael; Bachert, Peter; Semmler, Wolfhard; Behl, Nicolas G. R.; Nagel, Armin M.
- Abstract
Purpose To increase the signal-to-noise ratio (SNR) and to reduce artifacts in non-proton magnetic resonance imaging (MRI) by incorporation of a priori information from 1H MR data in an iterative reconstruction. Methods An iterative reconstruction algorithm for 3D projection reconstruction (3DPR) is presented that combines prior anatomical knowledge and image sparsity under a total variation (TV) constraint. A binary mask (BM) is used as an anatomical constraint to penalize non-zero signal intensities outside the object. The BM&TV method is evaluated in simulations and in MR measurements in volunteers. Results In simulated BM&TV brain data, the artifact level was reduced by 20% while structures were well preserved compared to gridding. SNR maps showed a spatially dependent SNR gain over gridding reconstruction, which was up to 100% for simulated data. Undersampled 3DPR 23Na MRI of the human brain revealed an SNR increase of 29 ± 7%. Small anatomical structures were reproduced with a mean contrast loss of 14%, whereas in TV-regularized iterative reconstructions a loss of 66% was found. Conclusion The BM&TV algorithm allows reconstructing images with increased SNR and reduced artifact level compared to gridding and performs superior to an iterative reconstruction using an unspecific TV constraint only. Magn Reson Med 71:1720-1732, 2014. © 2013 Wiley Periodicals, Inc.
- Publication
Magnetic Resonance in Medicine, 2014, Vol 71, Issue 5, p1720
- ISSN
0740-3194
- Publication type
Article
- DOI
10.1002/mrm.24827