Citations¶
[Jenkinson2001] |
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[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. |
[Zhang2001] |
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[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. |
[Jenkinson2012] |
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[Jenkinson2001b] |
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[Jenkinson2003] |
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[Jenkinson2004] |
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[Smith2002] | S.M. Smith. Fast robust automated brain extraction. Human Brain Mapping, 17(3):143-155, November 2002. |
[Pechaud2005] |
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[Jenkinson2005] |
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[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. |
[Woolrich2008] |
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[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 |