The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants,NeuroImage

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The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants
NeuroImage ( IF 5.7 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.neuroimage.2020.117303
Sean P Fitzgibbon ₁ , Samuel J Harrison ₂ , Mark Jenkinson ₁ , Luke Baxter ₃ , Emma C Robinson ₄ , Matteo Bastiani ₅ , Jelena Bozek ₆ , Vyacheslav Karolis ₁ , Lucilio Cordero Grande ₄ , Anthony N Price ₄ , Emer Hughes ₄ , Antonios Makropoulos ₇ , Jonathan Passerat-Palmbach ₇ , Andreas Schuh ₇ , Jianliang Gao ₇ , Seyedeh-Rezvan Farahibozorg ₁ , Jonathan O'Muircheartaigh ₈ , Judit Ciarrusta ₄ , Camilla O'Keeffe ₄ , Jakki Brandon ₄ , Tomoki Arichi ₉ , Daniel Rueckert ₇ , Joseph V Hajnal ₄ , A David Edwards ₄ , Stephen M Smith ₁ , Eugene Duff ₁ , Jesper Andersson ₁

Affiliation

Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Translational Neuromodeling Unit, University of Zurich & ETH Zurich, Switzerland.
Paediatric Neuroimaging Group, Department of Paediatrics, University of Oxford, UK.
Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, UK; NIHR Biomedical Research Centre, University of Nottingham, UK.
Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia.
Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, UK.
Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK; Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK; MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
Centre for the Developing Brain, Division of Imaging Sciences and Biomedical Engineering, King's College London, London, UK; Department of Bioengineering, Imperial College London, UK; Children's Neurosciences, Evelina London Children's Hospital, King's Health Partners, London, UK.

Highlights • An automated and robust pipeline to minimally pre-process highly confounded neonatal fMRI data.• Includes integrated dynamic distortion and slice-to-volume motion correction.• A robust multimodal registration approach which includes custom neonatal templates.• Incorporates an automated and self-reporting QC framework to quantify data quality and identify issues for further inspection.• Data analysis of 538 infants imaged at 26–45 weeks post-menstrual age.

中文翻译：

正在开发的人类连接组计划 (dHCP) 新生儿自动静息状态功能处理框架

亮点 • 一个自动化且强大的管道，可对高度混淆的新生儿 fMRI 数据进行最低限度的预处理。• 包括集成的动态失真和切片到体积运动校正。• 一种强大的多模式配准方法，包括自定义新生儿模板。• 结合了自动化和自我- 报告 QC 框架以量化数据质量并确定进一步检查的问题。• 对 538 名在月经后 26-45 周成像的婴儿进行数据分析。

更新日期：2020-12-01

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