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The developing Human Connectome Project automated functional processing framework for neonates  #24

@SeanFitzgibbon

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@SeanFitzgibbon

Presentor and Affiliation
Sean Fitzgibbon, WIN@FMRIB, University of Oxford
Eugene Duff, WIN@FMRIB, University of Oxford

Collaborators
Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford
Biomedical Image Analysis Group, Imperial College London
Centre for the Developing Brain, King's College London

Github Link (if applicable)
To be advised.

Abstract (max. 200 words):
Neonates present significant challenges to data processing due to rapid developmental changes, low and variable contrast, and high levels of head motion. The dHCP neonatal fMRI pre-processing pipeline has been designed specifically to address the challenges of neonatal data. The pipeline includes integrated dynamic distortion and slice-to-volume motion correction, a robust multimodal registration approach including custom neonatal templates, bespoke ICA-based denoising, and an automated QC framework. The pipeline currently has partial BIDS derivatives support with full support under development.

The pipeline has been evaluated on more than 500 neonatal subjects from the dHCP. With the impending open release of the pipeline and the pre-processed data by the consortium, now is the ideal time to demonstrate the capabilities of the pipeline to the community.

Preferred Session
3. Demo: New advances in open neuroimaging methods

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