Quantifying the statistical impact of GRAPPA in fcMRI data with a real-valued isomorphism

IEEE Transactions on Medical Imaging
Iain P Bruce, Daniel B Rowe

Abstract

The interpolation of missing spatial frequencies through the generalized auto-calibrating partially parallel acquisitions (GRAPPA) parallel magnetic resonance imaging (MRI) model implies a correlation is induced between the acquired and reconstructed frequency measurements. As the parallel image reconstruction algorithms in many medical MRI scanners are based on the GRAPPA model, this study aims to quantify the statistical implications that the GRAPPA model has in functional connectivity studies. The linear mathematical framework derived in the work of Rowe , 2007, is adapted to represent the complex-valued GRAPPA image reconstruction operation in terms of a real-valued isomorphism, and a statistical analysis is performed on the effects that the GRAPPA operation has on reconstructed voxel means and correlations. The interpolation of missing spatial frequencies with the GRAPPA model is shown to result in an artificial correlation induced between voxels in the reconstructed images, and these artificial correlations are shown to reside in the low temporal frequency spectrum commonly associated with functional connectivity. Through a real-valued isomorphism, such as the one outlined in this manuscript, the exact artificial correlat...Continue Reading

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Sep 13, 2011·Magnetic Resonance Imaging·Iain P BruceDaniel B Rowe

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Citations

Mar 19, 2016·Magnetic Resonance Imaging·Mary C Kociuba, Daniel B Rowe

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