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RT‐GROG: parallelized self‐calibrating GROG for real‐time MRI
Author(s) -
Saybasili Haris,
Derbyshire J. Andrew,
Kellman Peter,
Griswold Mark A.,
Ozturk Cengizhan,
Lederman Robert J.,
Seiberlich Nicole
Publication year - 2010
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.22351
Subject(s) - computer science , operator (biology) , decoupling (probability) , algorithm , artificial intelligence , grid , weighting , computer vision , process (computing) , mathematics , acoustics , physics , repressor , control engineering , transcription factor , engineering , gene , operating system , biochemistry , chemistry , geometry
A real‐time implementation of self‐calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self‐calibrating GRAPPA operator gridding is a parallel‐imaging‐based, parameter‐free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self‐calibrating GRAPPA operator gridding's weight‐set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C++ and parallelized. This decoupling allows the weights to be updated adaptively in the background while image reconstruction threads use the most recent gridding weights to grid and reconstruct images. All possible combinations of two‐dimensional gridding weights G x m G y nare evaluated for m,n = {−0.5, −0.4, …, 0, 0.1, …, 0.5} and stored in a look‐up table. Consequently, the per‐sample two‐dimensional weights calculation during gridding is eliminated from the reconstruction process and replaced by a simple look‐up table access. In practice, up to 34× faster reconstruction than conventional (parallelized) self‐calibrating GRAPPA operator gridding is achieved. On a 32‐coil dataset of size 128 × 64, reconstruction performance is 14.5 frames per second (fps), while the data acquisition is 6.6 fps. Magn Reson Med 64:306–312, 2010. © 2010 Wiley‐Liss, Inc.