Iterative self-consistent magnetic resonance inverse imaging
Date Issued
2012
Date
2012
Author(s)
Huang, Tsung-Min
Abstract
Magnetic resonance inverse imaging (InI) using multiple channel radio-frequency (RF) coil detection can achieve 100 ms temporal resolution with the whole brain coverage. InI reconstructions use the RF coil sensitivity information to reconstruct the omitted partition encoding data. Previously we proposed the k-space InI (K-InI) reconstruction to provide higher spatial resolution and higher sensitivity in detecting activated brain areas in BOLD fMRI experiment than the image domain minimum-norm estimate (MNE) InI reconstruction. Recently, the self-consistent property has been suggested as a useful property in k-space parallel MRI reconstruction because it improves the reconstruction image quality. Studying this study, we develop self-consistent K-InI and -self-consistent K-InI algorithms to use the self-consistent property to reconstruct highly accelerated InI acquisitions. Numerical simulations show that self-consistent K-InI and -self-consistent K-InI can provide higher spatial resolution than K-InI. Applying self-consistent K-InI and -self-consistent K-InI to BOLD contrast fMRI experiments, we found that all methods can reveal visual cortex activation at the 100 ms temporal resolution. Self-consistent K-InI has a comparable detection sensitivity to K-InI. -self-consistent K-InI the sensitivity of detecting brain activation is 50% higher than that of K-InI. Self-consistent K-InI and -self-consistent K-InI can be useful tools in fMRI data analysis to characterize brain activity with a high spatiotemporal resolution.
Subjects
fMRI
InI
visual
MRI
K-InI
self-consistency
Type
thesis
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