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Chunk #11 — Methods — Data Processing — NCANDA-Specific Pre-processing Pipeline

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Regional growth trajectories of cortical myelination in adolescents and young adults: longitudinal validation and functional correlates.
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For each NCANDA MRI baseline visit, preprocessing involved noise removal (Coupe et al. 2008), correcting field inhomogeneity via N4ITK (Version: 2.1.0) (Tustison et al. 2010), aligning T2-weighted to T1-weighted MRI using CMTK (Version: 3.2.3) (Rohlfing and Maurer 2003). A brain mask was defined through majority voting (Rohlfing et al. 2004) across the maps extracted from bias and non-bias corrected T1-weighted and T2-weighted MRIs via FSL BET (Version: 5.0.6) (Smith 2002), AFNI 3dSkullStrip (Version: AFNI_2011_12_21_1014) (Cox 1996), FreeSurfer’s mri_gcut (Version: 5.3.0) (Sadananthan et al. 2010), and ROBEX (Version: 1.2) (Iglesias et al. 2011). The mean curvature along cortical surface, white matter boundary, and pial surface of the resulting skull-stripped T1-weighted MRI was extracted by FreeSurfer (Version: 5.3.0) (Dale et al. 1999; Fischl et al. 1999; Fischl 2012). Skull-stripping was further refined by aligning the white matter boundary to the T2-weighted MRIs via FSL epi_reg (Version: 5.0.6) and removing voxels with low T2-weighted intensities near the pial surface.