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. 2017 Aug 14;5:159. doi: 10.3389/fped.2017.00159

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Copyright © 2017 Mongerson, Jennings, Borsook, Becerra and Bajic.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Structural magnetic resonance imaging (MRI) data preprocessing pipeline. Figure illustrates structural MRI data preprocessing pipeline, using a representative ex-33 week premature infant scanned at 4-weeks corrected age (2.75 months postnatal age). Panel (A) shows conversion of original T1-weighted image (T1file, in sagittal view) to a standardized brain orientation (T1file_std). Note, anterior (A) and posterior (P) are flipped in reoriented file. Panel (B) illustrates process of brain extraction. Manually edited binary mask (T1file_bet_mask; red) is shown superimposed on T1 image (grayscale), as well as finalized extracted brain (T1file_brain). Panel (C) illustrates the process of bias field correction. FMRIB’s Automated Segmentation Tool tissue-type segmentation (_seg) and estimated bias field (_bias) output files are shown. The latter image reflects gradient of tissue-specific signal inhomogeneity, showing hypo- (black) and hyper-intense (white) regions across entire T1 image. Hyperintense subcortical regions present in original T1 image are attenuated following intensity normalization, creating finalized structural Reference image (T1file_ref).