1. Jenkinson and S.M. Smith. A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5(2):143-156, 2001.
[Jenkinson2002]Jenkinson, M., Bannister, P., Brady, J. M. and Smith, S. M. Improved Optimisation for the Robust and Accurate Linear Registration and Motion Correction of Brain Images. NeuroImage, 17(2), 825-841, 2002.
[Greve2009]Greve, D.N. (2009), Accurate and robust brain image alignment using boundary-based registration, NeuroImage, vol. 48, no. 1, pp. 63-72.
  1. Zhang, M. Brady, and S. Smith. Segmentation of brain MR images through a hidden Markov random field model and the expectation maximization algorithm. IEEE Trans. on Medical Imaging, 20(1):45-57, 2001.
[Smith2004]Smith. S.M. (2004), Advances in functional and structural MR image analysis and implementation as FSL , NeuroImage, vol. 23, no. S1, pp. 208-19.
  1. Jenkinson, C.F. Beckmann, T.E.J. Behrens, M.W. Woolrich, and S.M. Smith. FSL. NeuroImage, 62:782-790, 2012.
  1. Jenkinson. Improved Unwarping of EPI Volumes using Regularised B0 Maps. Seventh Int Conf on Functional Mapping of the Human Brain; 2001
  1. Jenkinson. A fast, automated, n-dimensional phase unwrapping algorithm. Magnetic Resonance in Medicine, 49(1):193-197, 2003.
  1. Jenkinson. Improving the Registration of B0-distorted EPI Images using Calculated Cost Function Weights. Tenth Int Conf on Functional Mapping of the Human Brain; 2004;
[Smith2002]S.M. Smith. Fast robust automated brain extraction. Human Brain Mapping, 17(3):143-155, November 2002.
  1. Pechaud, M. Jenkinson, S. Smith. BET2 - MRI-Based Estimation of Brain, Skull and Scalp Surfaces. FMRIB Technical Report TR06MP1
  1. Jenkinson, M. Pechaud, and S. Smith. BET2: MR-based estimation of brain, skull and scalp surfaces. In Eleventh Annual Meeting of the Organization for Human Brain Mapping, 2005.
[Woolrich2001]M.W. Woolrich, B.D. Ripley, J.M. Brady, and S.M. Smith. Temporal autocorrelation in univariate linear modelling of FMRI data. NeuroImage, 14(6):1370-1386, 2001.
[Beckmann2003]C.F. Beckmann, M. Jenkinson, and S.M. Smith. General multi-level linear modelling for group analysis in FMRI. NeuroImage, 20:1052-1063, 2003.
  1. Woolrich. Robust group analysis using outlier inference. NeuroImage, 41(2):286-301, 2008.
[Woolrich2004]M.W. Woolrich, T.E.J. Behrens, C.F. Beckmann, M. Jenkinson, and S.M. Smith. Multi-level linear modelling for FMRI group analysis using Bayesian inference. NeuroImage, 21(4):1732-1747, 2004.
[Beckmann2004]C.F. Beckmann and S.M. Smith. Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans. on Medical Imaging, 23(2):137-152, 2004.
[Beckmann2005a]C.F. Beckmann and S.M. Smith. Tensorial extensions of independent component analysis for multisubject FMRI analysis. NeuroImage, 25(1):294-311, 2005.
[Beckmann2005b]C.F. Beckmann, M. De Luca, J.T. Devlin, and S.M. Smith. Investigations into resting-state connectivity using independent component analysis. Philosophical Transactions of the Royal Society, 360(1457):1001-1013, 2005.
[Smith1997]S.M. Smith and J.M. Brady. SUSAN - a new approach to low level image processing. International Journal of Computer Vision, 23(1):45-78, May 1997.
[Avants2008]Avants, B.B. (2008), ‘Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain’, Medical Image Analysis, vol. 12, no. 1, pp. 26-41.
[Mumford2006]Mumford JA, Hernandez-Garcia LH, Lee GR, Nichols TE. Estimation efficiency and statistical power in arterial spin labeling fMRI. NeuroImage 2006;33:103-114.
[Smith2007]S.M. Smith, M. Jenkinson, C.F. Beckmann, K.L. Miller, and M. Woolrich. Meaningful design and contrast estimability in FMRI. NeuroImage, 34(1):127-136, 2007.
[Power2012]Power, J.D. (2012), ‘Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion’, NeuroImage, vol. 59, no. 3, pp. 2142-54.
[Rex2003]Rex, D.E. (2003), ‘The LONI Pipeline Processing Environment’, NeuroImage, vol. 19, no. 3, pp. 1033-48.
[Gorgolewski2011]Gorgolewski, K. (2011), ‘Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python’, Frontiers in Neuroinformatics, vol. 5, article 13.
[Schmithorst2014]Schmithorst, V.J. (2014), ‘Optimized simultaneous ASL and BOLD functional imaging of the whole brain’, Journal of Magnetic Resonance Imaging, In Press (doi: 10.1002/jmri.24273).
[CMIND_Contract]The Pediatric Functional Neuroimaging Research Network, NICHD HHSN275200900018C.
[Wang2002]Wang, JJ. et. al. (2002), Comparison of Quantitative Perfusion Imaging Using Arterial Spin Labeling at 1.5 and 4.0 Tesla. Magnetic Resonance in Medicine 48:242-254