Advances in functional and structural MR image analysis and implementation as FSL

  title={Advances in functional and structural MR image analysis and implementation as FSL},
  author={Stephen M. Smith and Mark Jenkinson and Mark W. Woolrich and Christian F. Beckmann and Timothy Edward John Behrens and Heidi Johansen-Berg and Peter R. Bannister and M. De Luca and Ivana Drobnjak and David Flitney and Rami K. Niazy and James Saunders and John Vickers and Yongyue Zhang and Nicola De Stefano and Joanne Brady and Paul M. Matthews},

LISA improves statistical analysis for fMRI

A new fMRI analysis tool, LISA, is introduced, which provides increased statistical power compared to existing techniques and allows to find small activation areas that have previously evaded detection.

Large-scale functional MRI study on a production grid

Improving the temporal accuracy of functional Magnetic Resonance Imaging

This work shows how the current volume creation method leads to whole-brain volumes that contain within-volume temporal distortions and that are available at a low temporal resolution, and proposes a new framework for fMRI data analysis that yields greatly improved temporal accuracy of fMRI signals.


This paper analyzes the effectiveness of commonly used image processing algorithms in fMRI studies by statistically analyzing their effectiveness in extracting ROI’s in various images and tries to project the efficiency of these systems in f MRI scanning.

Magnetic resonance brain image processing and arithmetic with FSL.

  • W. Crum
  • Computer Science
    Methods in molecular biology
  • 2011
A number of key image analysis tasks in brain imaging are presented with particular reference to the freely available FMRIB Software Library.

A brief introduction to functional MRI

  • J. Pekar
  • Biology
    IEEE Engineering in Medicine and Biology Magazine
  • 2006
The future appears to promise a more integrative approach to functional brain imaging, in which data from multiple modalities are entered into comprehensive analyses of brain function and connectivity.

A Framework for the Automation of Multimodalbrain Connectivity Analyses

This work presents a framework that incorporates some of this technical knowledge and enables the automation of most of the processing in the context of combined resting-state functional Magnetic Resonance Imaging (rs-fMRI) and Diffusion Tensor Imaging (DTI) data processing and analysis.

System for Integrated Neuroimaging Analysis and Processing of Structure

The cortical reconstruction using implicit surface evolution (CRUISE) methodology is extended to perform efficient, consistent, and topologically correct analyses in a natively multi-parametric manner.



TIGER - A New Model for Spatio-temporal Realignment of FMRI Data

A new model is described which is able to model accurately the characteristics of subject motion, a dominant artefact in Functional Magnetic Resonance Images, enabling a far more accurate analysis of the patterns of brain activation which these images seek to capture.

A Three-Dimensional Statistical Analysis for CBF Activation Studies in Human Brain

A simple method for determining an approximate p value for the global maximum based on the theory of Gaussian random fields is described, which focuses on the Euler characteristic of the set of voxels with a value larger than a given threshold.

Accurate, Robust, and Automated Longitudinal and Cross-Sectional Brain Change Analysis

Improvements to this method are described, and an extension of SIENA is extended to a new method for cross-sectional (single time point) analysis, which provides easy manual review of their output by the automatic production of summary images.

Mixture model mapping of brain activation in functional magnetic resonance images

A novel method of identifying brain regions activated by periodic experimental design in functional magnetic resonance imaging data by fitting a mixture distribution with two components to a test statistic estimated at each voxel in an image is reported.

Variability in fMRI: An Examination of Intersession Differences

The results are interpreted as demonstrating that correct inference about subject responses to activation tasks can be derived through the use of a statistical model which accounts for both within- and between-session variance, combined with an appropriately large session sample size.

Tensorial extensions of independent component analysis for multisubject FMRI analysis

Functional connectivity in the motor cortex of resting human brain using echo‐planar mri

It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.

Tracking neuronal fiber pathways in the living human brain.

This approach enhances the power of modern imaging by enabling study of fiber connections among anatomically and functionally defined brain regions in individual human subjects.

Fast robust automated brain extraction

An automated method for segmenting magnetic resonance head images into brain and non‐brain has been developed and described and examples of results and the results of extensive quantitative testing against “gold‐standard” hand segmentations, and two other popular automated methods.

Functional Mapping of the Human Brain

Evidence has been provided showing that visual attention to cued targets leads to enhanced activations with a retinotopic organization in the medial occipitotemporal cortex, and the advent of functional imaging and deep electrode record ings in nonhuman primates opens up a new avenue for understanding the electrophysiological processes under lying cerebral activations.