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Inverse reconstruction method for segmented multishot diffusion‐weighted MRI with multiple coils
Author(s) -
Uecker Martin,
Karaus Alexander,
Frahm Jens
Publication year - 2009
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.22126
Subject(s) - diffusion mri , computer science , iterative reconstruction , electromagnetic coil , diffusion , inverse problem , computer vision , inverse , artificial intelligence , phase (matter) , algorithm , physics , magnetic resonance imaging , mathematics , mathematical analysis , geometry , radiology , medicine , quantum mechanics , thermodynamics
Each k ‐space segment in multishot diffusion‐weighted MRI is affected by a different spatially varying phase which is caused by unavoidable motions and amplified by the diffusion‐encoding gradients. A proper image reconstruction therefore requires phase maps for each segment. Such maps are commonly derived from two‐dimensional navigators at relatively low resolution but do not offer robust solutions. For example, phase variations in diffusion‐weighted MRI of the brain are often characterized by high spatial frequencies. To overcome this problem, an inverse reconstruction method for segmented multishot diffusion‐weighted MRI is described that takes advantage of the full k ‐space data acquired from multiple receiver coils. First, the individual coil sensitivities are determined from the non–diffusion‐weighted acquisitions by regularized nonlinear inversion. These coil sensitivities are then used to estimate accurate motion‐associated phase maps for each segment by iterative linear inversion. Finally, the coil sensitivities and phase maps serve to reconstruct artifact‐free images of the object by iterative linear inversion, taking advantage of the data of all segments. The efficiency of the new method is demonstrated for segmented diffusion‐weighted stimulated echo acquisition mode MRI of the human brain. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.