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Iterative GRAPPA (iGRAPPA) for improved parallel imaging reconstruction
Author(s) -
Zhao Tiejun,
Hu Xiaoping
Publication year - 2008
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.21370
Subject(s) - imaging phantom , computer science , regularization (linguistics) , iterative reconstruction , image quality , artificial intelligence , iterative method , computer vision , algorithm , image (mathematics) , nuclear medicine , medicine
In this work an iterative reconstruction method based on generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstruction is introduced. In the new method the reconstructed lines are used to reestimate and refine the weights from all the acquired data by applying the GRAPPA procedure iteratively with regularization. Both phantom and in vivo MRI experiments demonstrated that, compared to GRAPPA, the iterative approach reduces parallel imaging artifacts and permits high‐quality image reconstruction with a relatively small number of calibration lines and slight changes of GRAPPA weights. Magn Reson Med 59:903–907, 2008. © 2008 Wiley‐Liss, Inc.