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Compressed sensing fMRI using gradient-recalled echo and EPI sequences

Cited 19 time in webofscience Cited 0 time in scopus
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Title
Compressed sensing fMRI using gradient-recalled echo and EPI sequences
Author(s)
Zong X.; Lee J.; John Poplawsky A.; Seong Gi Kim; Ye J.C.
Publication Date
2014-05
Journal
NEUROIMAGE, v.92, no., pp.312 - 321
Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
Abstract
Compressed sensing (CS)may be useful for accelerating data acquisitions in high-resolution fMRI. However, due to the inherent slow temporal dynamics of the hemodynamic signals and concerns of potential statistical power loss, the CS approach for fMRI (CS–fMRI) has not been extensively investigated. To evaluate the utility of CS in fMRI application, we systematically investigated the properties of CS–fMRI using computer simulations and in vivo experiments of rat forepaw sensory and odor stimulations with gradient-recalled echo (GRE) and echo planar imaging (EPI) sequences. Various undersampling patterns along the phase-encoding directionwere studied and k–t FOCUSSwas used as the CS reconstruction algorithm,which exploits the temporal redundancy of images. Functional sensitivity, specificity, and time courses were compared between fully-sampled and CS–fMRI with reduction factors of 2 and 4. CS–fMRI with GRE, but not with EPI, improves the statistical sensitivity for activation detection over the fully sampled data when the ratio of the fMRI signal change to noise is low. CS improves the temporal resolution and reduces temporal noise correlations. While CS reduces the functional response amplitudes, the noise variance is also reduced to make the overall activation detection more sensitive. Consequently, CS is a valuable fMRI acceleration approach, especially for GRE fMRI studies. © 2014 Elsevier Inc. All rights reserved.
URI
https://pr.ibs.re.kr/handle/8788114/1514
ISSN
1053-8119
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > Journal Papers (저널논문)
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