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Design of k‐space channel combination kernels and integration with parallel imaging
Author(s) -
Beatty Philip J.,
Chang Shaorong,
Holmes James H.,
Wang Kang,
Brau Anja C. S.,
Reeder Scott B.,
Brittain Jean H.
Publication year - 2014
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.24883
Subject(s) - computer science , channel (broadcasting) , pipeline (software) , computation , calibration , k space , image quality , algorithm , arc (geometry) , image (mathematics) , artificial intelligence , computer vision , mathematics , telecommunications , geometry , fourier transform , mathematical analysis , statistics , programming language
Purpose In this work, a new method is described for producing local k‐space channel combination kernels using a small amount of low‐resolution multichannel calibration data. Additionally, this work describes how these channel combination kernels can be combined with local k‐space unaliasing kernels produced by the calibration phase of parallel imaging methods such as GRAPPA, PARS and ARC. Methods Experiments were conducted to evaluate both the image quality and computational efficiency of the proposed method compared to a channel‐by‐channel parallel imaging approach with image‐space sum‐of‐squares channel combination. Results Results indicate comparable image quality overall, with some very minor differences seen in reduced field‐of‐view imaging. It was demonstrated that this method enables a speed up in computation time on the order of 3–16X for 32‐channel data sets. Conclusion The proposed method enables high quality channel combination to occur earlier in the reconstruction pipeline, reducing computational and memory requirements for image reconstruction. Magn Reson Med 71:2139–2154, 2014. © 2013 Wiley Periodicals, Inc.