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Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank


Fidel Alfaro-Almagro

Mark Jenkinson

Neal K. Bangerter

Jesper L.R. Andersson

Ludovica Griffanti


Saad Jbabdi

Moises Hernandez-Fernandez

Emmanuel Vallee

Diego Vidaurre

Matthew Webster

Paul McCarthy

Christopher Rorden

Alessandro Daducci

Daniel C. Alexander

Hui Zhang

Iulius Dragonu

Paul M. Matthews

Karla L. Miller

Stephen M. Smith


UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.


Alfaro-Almagro, F., Jenkinson, M., Bangerter, N. K., Andersson, J. L., Griffanti, L., Douaud, G., …Smith, S. M. (2018). Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank. NeuroImage, 166,

Journal Article Type Article
Acceptance Date Oct 16, 2017
Online Publication Date Oct 24, 2017
Publication Date Feb 1, 2018
Deposit Date Oct 25, 2017
Publicly Available Date Oct 25, 2017
Journal NeuroImage
Print ISSN 1053-8119
Electronic ISSN 1095-9572
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 166
Keywords Epidemiological studies; Image analysis pipeline; Multi-modal data integration; Quality control; Big data imaging;
Machine learning
Public URL
Publisher URL


1-s2.0-S1053811917308613-main.pdf (8.6 Mb)

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