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Comprehensive quantification of signal‐to‐noise ratio and g ‐factor for image‐based and k ‐space‐based parallel imaging reconstructions
Author(s) -
Robson Philip M.,
Grant Aaron K.,
Madhuranthakam Ananth J.,
Lattanzi Riccardo,
Sodickson Daniel K.,
McKenzie Charles A.
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.21728
Subject(s) - noise (video) , iterative reconstruction , signal to noise ratio (imaging) , computer science , monte carlo method , signal (programming language) , pixel , k space , algorithm , image resolution , artificial intelligence , computer vision , physics , optics , image (mathematics) , mathematics , statistics , fourier transform , quantum mechanics , programming language
Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g ‐factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal‐to‐noise ratio and g ‐factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple “prescan” measurement of noise amplitude and correlation in the phased‐array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal‐to‐noise ratio and g ‐factor. The “pseudo multiple replica” method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel‐by‐pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k ‐space trajectories, image reconstruction, or noise conditioning techniques. Magn Reson Med 60:895–907, 2008. © 2008 Wiley‐Liss, Inc.