Image Processing and Quality Control for the first 10,000 Brain Imaging Datasets from UK Biobank
Author:
Alfaro-Almagro FidelORCID, Jenkinson MarkORCID, Bangerter Neal K., Andersson Jesper L. R.ORCID, Griffanti LudovicaORCID, Douaud GwenaëlleORCID, Sotiropoulos Stamatios N.ORCID, Jbabdi SaadORCID, Hernandez-Fernandez MoisesORCID, Vallee EmmanuelORCID, Vidaurre DiegoORCID, Webster Matthew, McCarthy PaulORCID, Rorden Christopher, Daducci AlessandroORCID, Alexander Daniel C.ORCID, Zhang Hui, Dragonu Iulius, Matthews Paul M., Miller Karla L.ORCID, Smith Stephen M.
Abstract
AbstractUK 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.
Publisher
Cold Spring Harbor Laboratory
Reference101 articles.
1. Abe, S. , Irimia, A. , Van Horn, J. D. , 2015. Quality Control Considerations for the E_ective Integration of Neuroimaging Data. In: Data Integration in the Life Sciences. Springer, pp. 195–201. 2. Afyouni, S. , Nichols, T. E. , 2017. Insight and inference for DVARS. bioRxiv, 125021. 3. Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images 4. Andersson, J. L. , Jenkinson, M. , Smith, S. , 2007a. Non-linear registration aka Spatial normalisation. Internal Technical Report TR07JA2, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, Department of Clinical Neurology, Oxford University, Oxford, UK, available at www.fmrib.ox.ac.uk/analysis/techrep for downloading. 5. Andersson, J. L. , Skare, S. , 2010. Image distortion and its correction in diffusion MRI. In: Jones, D. (Ed.), Diffusion MRI: theory, methods, and applications. Oxford University Press, Oxford, pp. 285–302.
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|