Real-time motion analytics during brain MRI improve data quality and reduce costs

• Published in: NeuroImage (Orlando, Fla.) Vol. 161; pp. 80 - 93
• Main Authors: Dosenbach, Nico U.F., Koller, Jonathan M., Earl, Eric A., Miranda-Dominguez, Oscar, Klein, Rachel L., Van, Andrew N., Snyder, Abraham Z., Nagel, Bonnie J., Nigg, Joel T., Nguyen, Annie L., Wesevich, Victoria, Greene, Deanna J., Fair, Damien A.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.11.2017; Elsevier Limited
• Subjects: Accuracy; Adolescent; Adult; Alcoholism - diagnostic imaging; Attention Deficit Disorder with Hyperactivity - diagnostic imaging; Autism Spectrum Disorder - diagnostic imaging; Brain - diagnostic imaging; Child; Cost control; Functional magnetic resonance imaging; Functional MRI; Functional Neuroimaging - methods; Functional Neuroimaging - standards; Head motion distortion; Head Movements - physiology; Humans; Image Processing, Computer-Assisted - methods; Image Processing, Computer-Assisted - standards; Magnetic Resonance Imaging - methods; Magnetic Resonance Imaging - standards; MRI acquisition; MRI methods; Neural networks; NMR; Nuclear magnetic resonance; Quality; Real-time quality control; Resting state functional connectivity MRI; Scanners; Structural MRI; Structure-function relationships; Young Adult; MRI acquisition; Head motion distortion; Real-time quality control; Resting state functional connectivity MRI; Structural MRI; Functional MRI; MRI methods

Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring c...