PT - JOURNAL ARTICLE AU - Makropoulos, Antonios AU - Robinson, Emma C. AU - Schuh, Andreas AU - Wright, Robert AU - Fitzgibbon, Sean AU - Bozek, Jelena AU - Counsell, Serena J. AU - Steinweg, Johannes AU - Passerat-Palmbach, Jonathan AU - Lenz, Gregor AU - Mortari, Filippo AU - Tenev, Tencho AU - Duff, Eugene P. AU - Bastiani, Matteo AU - Cordero-Grande, Lucilio AU - Hughes, Emer AU - Tusor, Nora AU - Tournier, Jacques-Donald AU - Hutter, Jana AU - Price, Anthony N. AU - Murgasova, Maria AU - Kelly, Christopher AU - Rutherford, Mary A. AU - Smith, Stephen M. AU - Edwards, A. David AU - Hajnal, Joseph V. AU - Jenkinson, Mark AU - Rueckert, Daniel TI - The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction AID - 10.1101/125526 DP - 2017 Jan 01 TA - bioRxiv PG - 125526 4099 - http://biorxiv.org/content/early/2017/04/07/125526.short 4100 - http://biorxiv.org/content/early/2017/04/07/125526.full AB - The Developing Human Connectome Project (dHCP) seeks to create the first 4-dimensional connectome of early life. Understanding this connectome in detail may provide insights into normal as well as abnormal patterns of brain development. Following established best practices adopted by the WUMINN Human Connectome Project and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processingmechanisms, genetic pipeline for the structural Magnetic Resonance Imaging (MRI) of the developing neonatal brain. This proposed pipeline consists of a refined framework for cortical and sub-cortical volume segmentation, cortical surface extraction and cortical surface inflation of neonatal subjects, which has been specifically designed to address considerable differences between adult and neonatal brains, as imaged using MRI. Using the proposed pipeline our results demonstrate that images collected from 465 subjects ranging from 28 to 45 weeks post-menstrual age (PMA) can be fully automatically processed; generating cortical surface models that are topologically and anatomically correct. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, and support the modelling of emerging patterns of brain connectivity.