The Developing Human Connectome Project: A fast deep learning-based pipeline for neonatal cortical surface reconstruction.

Qiang Ma¹, Kaili Liang², Liu Li³, Saga Masui⁴, Yourong Guo⁴, Chiara Nosarti², Emma C Robinson⁴, Bernhard Kainz⁵, Daniel Rueckert⁶

¹Department of Computing, Imperial College London, UK. Electronic address: q.ma20@imperial.ac.uk.

²School of Biomedical Engineering and Imaging Sciences, King's College London, UK; Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.

³Department of Computing, Imperial College London, UK.

⁴School of Biomedical Engineering and Imaging Sciences, King's College London, UK.

⁵Department of Computing, Imperial College London, UK; FAU Erlangen-Nürnberg, Germany.

⁶Department of Computing, Imperial College London, UK; Chair for AI in Healthcare and Medicine, Klinikum rechts der Isar, Technical University of Munich, Germany.

PubMed DOI

Abstract

The Developing Human Connectome Project (dHCP) aims to explore developmental patterns of the human brain during the perinatal period. An automated processing pipeline has been developed to extract high-quality cortical surfaces from structural brain magnetic resonance (MR) images for the dHCP neonatal dataset. However, the current implementation of the pipeline requires more than 6.5 h to process…

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