RIS ID

141693

Publication Details

S. Duong, S. Phung, A. Bouzerdoum, H. Taylor, A. Puckett & M. Schira, "Susceptibility artifact correction for sub-millimeter fMRI using inverse phase encoding registration and T1 weighted regularization," Journal of Neuroscience Methods, vol. 336, 2020.

Abstract

© 2020 Elsevier B.V. Background: Functional magnetic resonance imaging (fMRI) enables non-invasive examination of both the structure and the function of the human brain. The prevalence of high spatial-resolution (sub-millimeter) fMRI has triggered new research on the intra-cortex, such as cortical columns and cortical layers. At present, echo-planar imaging (EPI) is used exclusively to acquire fMRI data; however, susceptibility artifacts are unavoidable. These distortions are especially severe in high spatial-resolution images and can lead to misrepresentation of brain function in fMRI experiments. New method: This paper presents a new method for correcting susceptibility artifacts by combining a T1-weighted (T1w) image and inverse phase-encoding (PE) based registration. The latter uses two EPI images acquired using identical sequences but with inverse-PE directions. In the proposed method, the T1w image is used to regularize the registration, and to select the regularization parameters automatically. The motivation is that the T1w image is considered to reflect the anatomical structure of the brain. Results: Our proposed method is evaluated on two sub-millimeter EPI-fMRI datasets, acquired using 3T and 7T scanners. Experiments show that the proposed method provides improved corrections that are well-aligned to the T1w image. Comparison with existing methods: The proposed method provides more robust and sharper corrections and runs faster compared with two other state-of-the-art inverse-PE based correction methods, i.e. HySCO and TOPUP. Conclusions: The proposed correction method used the T1w image as a reference in the inverse-PE registration. Results show its promising performance. Our proposed method is timely, as sub-millimeter fMRI has become increasingly popular.

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Link to publisher version (DOI)

http://dx.doi.org/10.1016/j.jneumeth.2020.108625