Using synthetic MR images for field map-less distortion correction
2021
Functional MRI (fMRI) data acquired using echo-planar imaging (EPI) is highly distorted by magnetic field inhomogeneity. Distortion combined with underlying differences in image contrast between EPI and T1-weighted and T2-weighted (T1w/T2w) structural images makes the alignment of functional and anatomical images a challenge. Typically, separately acquired field map data are used to correct fMRI distortions and a flexible cost function insensitive to cross-modal differences in image contrast and intensity is used for aligning fMRI and anatomical images. The quality of alignment achieved with this approach can vary greatly and depends on the availability and quality of field map data. To address this issue, we developed Synth, a software package for distortion correction and cross-modal image registration that does not require separately acquired field map data. Synth combines information from T1w/T2w anatomical images to construct an idealized undistorted synthetic image that has similar contrast and intensity properties to fMRI data. The undistorted synthetic image then serves as an effective reference for individual-specific nonlinear unwarping to correct fMRI distortions. We demonstrate that Synth reliably outperforms other standard registration and distortion correction approaches that utilize field maps in both pediatric (ABCD: Adolescent Brain Cognitive Development) and adult (MSC: Midnight Scan Club) data. Field map-less distortion correction with Synth allows accurate and precise registration of fMRI data with missing or corrupted field map information.
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