Bayesian analysis of neuroimaging data in FSL

By Mark William Woolrich, Saâd Jbabdi, Brian Patenaude, Michael A. Chappell, Salima Makni, Timothy Edward John Behrens, Christian F. Beckmann, Mark Jenkinson, Stephen M. Smith. NeuroImage, 2009

2,686 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/8e0892fa44f6e873263343d3c9de1f695df2ca90

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Precuneus Is a Functional Core of the Default-Mode Network (2014, neutral): “uk/fsl/) package (Smith et al., 2004; Woolrich et al., 2009).”
Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI (2015, neutral): “0, available at http://www.fmrib.ox.ac.uk/fsl; Smith et al. (2004), Woolrich et al. (2009), Jenkinson et al. (2012)).”
Visual inspection of independent components: Defining a procedure for artifact removal from fMRI data (2010, methodology): “uk/fsl) (Smith et al., 2004; Woolrich et al., 2009), involving non-brain removal using BET (Smith, 2002); motion correction with MCFLIRT (Jenkinson et al.”
A Deep Learning Approach for Automated Diagnosis and Multi-Class Classification of Alzheimer’s Disease Stages Using Resting-State fMRI and Residual Neural Networks (2019, methodology): “Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) [44, 45] is used for preprocessing the data.”
Diffusion tensor imaging shows white matter tracts between human auditory and visual cortex (2011, positive): “DTI pre-processing DTI pre-processing and fibre tracking was conducted with the FDT toolbox of FSL (Centre for Functional Magnetic Resonance Imaging of the Brain, University of Oxford, Oxford, UK) (Smith et al. 2004; Woolrich et al. 2009).”
Mechanical characterization of human brain tissue. (2017, methodology): “2) [54,55] and the DWI measurements from 12 directions were used to pixelwise calculate the DTI tensor model by using FSL.”
Informatic parcellation of the network involved in the computation of subjective value. (2014, methodology): “We evaluated the significance of the IBMA using the standard familywise error correction implemented in FSL (Woolrich et al., 2009).”
ICA-based artifact removal diminishes scan site differences in multi-center resting-state fMRI (2015, methodology): “FSL (http://www.fmrib.ox.ac.uk/fsl) tools were used for all data analyses (Smith et al., 2004;Woolrich et al., 2009; Jenkinson et al., 2012).”
Life-span changes of the human brain white matter: diffusion tensor imaging (DTI) and volumetry. (2010, methodology): “Image analyses and tensor calculations were done using FSL (Smith et al. 2004; Woolrich et al. 2009).”
Automated brain extraction of multisequence MRI using artificial neural networks (2019, methodology): “State-of-the-art brain extraction algorithms Commonly available techniques such as the Brain Extraction Tool (BET(Jenkinson and Smith, 2001; Smith, 2002)) implemented in FSL (Jenkinson, et al., 2012; Woolrich, et al., 2009) and 3dSkullStrip (part of the AFNI package (Cox, 1996)) are based on a defor”
The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated (2013, methodology): “The anatomical scan was then skull stripped and segmented into white matter (WM) and cerebrospinal fluid (CSF) masks using FSL's FAST routine (Smith et al., 2004; Woolrich et al., 2009; Zhang et al., 2001).”
Bayesian model reduction and empirical Bayes for group (DCM) studies (2016, methodology): “…and then either harvest subjectwise parameter estimates from a selected model (identified as optimal at the group level) or use Bayesian model averaging to summarise each subject in terms of expected model parameters (Trujillo-Barreto et al., 2004; Penny et al., 2006;Woolrich et al., 2009).”
Exploring the role of the posterior middle temporal gyrus in semantic cognition: Integration of anterior temporal lobe with executive processes (2016, positive): “…echo planar imaging (EPI) with a flip angle = 90°, matrix size = 64 × 64, and field of view ( Data pre-processing and analysis Task-based fMRI Analyses were conducted at the first and higher level using FSL-FEAT version 4.1.9 (Smith et al., 2004; Woolrich et al., 2009; Jenkinson et al., 2012 ).”
Task-Based Core-Periphery Organization of Human Brain Dynamics (2012, methodology): “Table S3 Brain regions in the Harvard-Oxford (HO) cortical and subcortical parcellation scheme provided by FSL [83,84] and their affiliation to the temporal core (C; cyan), bulk (B; gold), and periphery (P; maroon) for both left (L) and right (R) hemispheres.”