Physical Sciences and Mathematics Commons^™

Removing Inter-Subject Technical Variability In Magnetic Resonance Imaging Studies, Jean-Philippe Fortin, Elizabeth M. Sweeney, John Muschelli, Ciprian M. Crainiceanu, Russell T. Shinohara, Alzheimer’S Disease Neuroimaging Initiative

UPenn Biostatistics Working Papers

Magnetic resonance imaging (MRI) intensities are acquired in arbitrary units, making scans non-comparable across sites and between subjects. Intensity normalization is a first step for the improvement of comparability of the images across subjects. However, we show that unwanted inter-scan variability associated with imaging site, scanner effect and other technical artifacts is still present after standard intensity normalization in large multi-site neuroimaging studies. We propose RAVEL (Removal of Artificial Voxel Effect by Linear regression), a tool to remove residual technical variability after intensity normalization. As proposed by SVA and RUV [Leek and Storey, 2007, …