Evidence map›Paper›PMID 29409960›Full record

ArticleNeuroImage2018

The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction.

Antonios Makropoulos, Emma C Robinson, Andreas Schuh, Robert Wright, Sean Fitzgibbon, Jelena Bozek, Serena J Counsell, Johannes Steinweg, Katy Vecchiato, Jonathan Passerat-Palmbach and 21 more

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 301 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
301citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

301 citing papers in PubMed, 4 syntheses or guidelines pooled it, 80 citations in OpenAlex.

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241 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

31 authors at 4 institutions in 2 countries.

Antonios MakropoulosBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
Emma C RobinsonBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom; Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom. Electronic address: emma.robinson@kcl.ac.uk.
Andreas SchuhBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
Robert WrightCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Sean FitzgibbonWellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Jelena BozekFaculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia.
Serena J CounsellCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Johannes SteinwegCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Katy VecchiatoCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Jonathan Passerat-PalmbachBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
Gregor LenzBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
Filippo MortariBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
Tencho TenevBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
Eugene P DuffWellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Matteo BastianiWellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Lucilio Cordero-GrandeCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Emer HughesCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Nora TusorCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Jacques-Donald TournierCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Jana HutterCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Anthony N PriceCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Rui Pedro A G TeixeiraCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Maria MurgasovaCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Suresh VictorCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Christopher KellyCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Mary A RutherfordCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Stephen M SmithWellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
A David EdwardsCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Joseph V HajnalCentre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
Mark JenkinsonWellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.
Daniel RueckertBiomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom.
King's College London · GBInstitute of Group Analysis · GBUniversity of Oxford · GBUniversity of Zagreb · HR

Funding

European Research Council 319456Medical Research Council MR/N026063/1
6 · The paper itself

Abstract

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 WU-MINN Human Connectome Project (HCP), and pioneered by FreeSurfer, the project utilises cortical surface-based processing pipelines. In this paper, we propose a fully automated processing 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, 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 processed fully automatically; generating cortical surface models that are topologically correct, and correspond well with manual evaluations of tissue boundaries in 85% of cases. Results improve on state-of-the-art neonatal tissue segmentation models and significant errors were found in only 2% of cases, where these corresponded to subjects with high motion. Downstream, these surfaces will enhance comparisons of functional and diffusion MRI datasets, supporting the modelling of emerging patterns of brain connectivity.

Indexed as

BrainConnectomeFemaleHumansImage Processing, Computer-AssistedInfant, NewbornMagnetic Resonance ImagingMaleCortical surface reconstructionDeveloping human connectome projectdHCPNeonatal MRIPipelineSegmentation

Identifiers

PMID29409960
PMCPMC6783314
OpenAlexW2606940515

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.