2026/01/01 by Andrew N. Van, David F. Montez, Timothy O. Laumann +30 · 12 citations
Mathematics · Medicine · Neuroscience · #Advanced MRI Techniques and Applications #Advanced Neuroimaging Techniques and Applications #Artificial intelligence #Computer science #Computer vision #Distortion (music) #Echo (communications protocol) #Field (mathematics) #Frame (networking) #Functional Brain Connectivity Studies #Mathematics #Physics #Reference frame
paper · doi:10.1162/imag.a.1262
published in Imaging Neuroscience 4 (The MIT Press)
openalex created_date 2025/10/10 · openalex publication_date 2026/01/01 · openalex updated_date 2026/07/28
Functional MRI (fMRI) data are severely distorted by magnetic field (B0) inhomogeneities, which currently must be corrected using separately acquired field map data. However, changes in the head position of a participant across fMRI frames cause changes in the B0 field, preventing accurate correction of geometric distortions. Movement during field map acquisitions corrupts field maps, preventing distortion correction altogether. In this study, we use multi-echo (ME) fMRI data to dynamically sample and correct for magnetic field image distortions caused by head motion. Our distortion correction pipeline, MEDIC (Multi-Echo DIstortion Correction), leverages magnetic field inhomogeneity information found in the difference between echoes and uses it to correct for distortion on a frame-by-frame basis. Here, we demonstrate that MEDIC's frame-wise distortion correction decreases the impact of head motion on resting-state functional connectivity (RSFC) maps and improves alignment to anatomy when compared with the prior gold standard approach (i.e., FSL TOPUP). Enhanced frame-wise distortion correction with MEDIC, without the requirement for field map collection, furthers the benefit of cutting-edge multi-echo fMRI imaging over single-echo fMRI.