RT Journal Article
SR Electronic
T1 The Developing Human Connectome Project: a Minimal Processing Pipeline for Neonatal Cortical Surface Reconstruction
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 125526
DO 10.1101/125526
A1 Antonios Makropoulos
A1 Emma C. Robinson
A1 Andreas Schuh
A1 Robert Wright
A1 Sean Fitzgibbon
A1 Jelena Bozek
A1 Serena J. Counsell
A1 Johannes Steinweg
A1 Jonathan Passerat-Palmbach
A1 Gregor Lenz
A1 Filippo Mortari
A1 Tencho Tenev
A1 Eugene P. Duff
A1 Matteo Bastiani
A1 Lucilio Cordero-Grande
A1 Emer Hughes
A1 Nora Tusor
A1 Jacques-Donald Tournier
A1 Jana Hutter
A1 Anthony N. Price
A1 Maria Murgasova
A1 Christopher Kelly
A1 Mary A. Rutherford
A1 Stephen M. Smith
A1 A. David Edwards
A1 Joseph V. Hajnal
A1 Mark Jenkinson
A1 Daniel Rueckert
YR 2017
UL http://biorxiv.org/content/early/2017/04/07/125526.abstract
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.