Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint

2007 | journal article; research paper. A publication of Göttingen

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​Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint​
Block, K. T.; Uecker, M.   & Frahm, J. ​ (2007) 
Magnetic Resonance in Medicine57(6) pp. 1086​-1098​.​ DOI: https://doi.org/10.1002/mrm.21236 

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Block, Kai Tobias; Uecker, Martin ; Frahm, Jens 
The reconstruction of artifact-free images from radially encoded MRI acquisitions poses a difficult task for undersampled data sets, that is for a much lower number of spokes in k-space than data samples per spoke. Here, we developed an iterative reconstruction method for undersampled radial MRI which (i) is based on a nonlinear optimization, (ii) allows for the incorporation of prior knowledge with use of penalty functions, and (iii) deals with data from multiple coils. The procedure arises as a two-step mechanism which first estimates the coil profiles and then renders a final image that complies with the actual observations. Prior knowledge is introduced by penalizing edges in coil profiles and by a total variation constraint for the final image. The latter condition leads to an effective suppression of undersampling (streaking) artifacts and further adds a certain degree of denoising. Apart from simulations, experimental results for a radial spin-echo MRI sequence are presented for phantoms and human brain in vivo at 2.9 T using 24,48, and 96 spokes with 256 data samples. In comparison to conventional reconstructions (regridding) the proposed method yielded visually improved image quality in all cases.
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John Wiley & Sons Inc
Magnetic Resonance in Medicine 



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