Motion robust magnetic susceptibility and field inhomogeneity estimation using regularized image restoration techniques for fMRI

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Abstract

In functional MRI, head motion may cause dynamic nonlinear field-inhomogeneity changes, especially with large out-of-plane rotations. This may lead to dynamic geometric distortion or blurring in the time series, which may reduce activation detection accuracy. The use of image registration to estimate dynamic field inhomogeneity maps from a static field map is not sufficient in the presence of such rotations. This paper introduces a retrospective approach to estimate magnetic susceptibility induced field maps of an object in motion, given a static susceptibility induced field map and the associated object motion parameters. It estimates a susceptibility map from a static field map using regularized image restoration techniques, and applies rigid body motion to the former. The dynamic field map is then computed using susceptibility voxel convolution. The method addresses field map changes due to out-of-plane rotations during time series acquisition and does not involve real time field map acquisitions. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Yeo, D. T. B., Fessler, J. A., & Kim, B. (2008). Motion robust magnetic susceptibility and field inhomogeneity estimation using regularized image restoration techniques for fMRI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5241 LNCS, pp. 991–998). Springer Verlag. https://doi.org/10.1007/978-3-540-85988-8_118

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