Elsevier

NeuroImage

Volume 23, Supplement 1, 2004, Pages S208-S219
NeuroImage

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

https://doi.org/10.1016/j.neuroimage.2004.07.051Get rights and content

The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right.

In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).

Introduction

In recent years, magnetic resonance imaging and functional MRI have played an increasingly important role in the investigation of brain structure, function, development, and pathologies. The increasing flexibility and power of MRI and FMRI to answer scientifically interesting and clinically relevant questions have led to a demand for analysis techniques that allow investigators to interrogate their data in as flexible, scientifically informative, and convenient a manner as is possible. This paper presents an overview of research carried out with this aim in the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB).

The broadest distinction that can be drawn between MRI experiments in the brain is between structural experiments, which are sensitive to biophysical properties of local brain tissue, and functional experiments, which are sensitive to temporally changing neural activity. The two types of MRI data require very different analysis techniques and are grouped into separate sections in this paper, but the relationship between structure and function is fundamental to brain organization. The data analysis techniques and tools described in Functional MRI analysis research and Structural MRI analysis research allow investigators not only to learn from each source of information, but also to combine data from functional and structural experiments to better inform neuropsychological inference. FDT—diffusion and white matter connectivity analysis is an example of this interdependence between structure and function, investigating the influence of structural connectivity on brain function. Fundamental to the ability to draw inference from data is a thorough understanding of the processes involved in the data's creation. The research outlined in MR physics-related research gives examples of how to improve this understanding via direct modeling of the MR image acquisition process. Crucially, this allows investigators to increase the sensitivity of their MRI experiments through both improved experimental design and the reduction of acquisition-related image artefacts. Finally, FSL—FMRIB's software library describes briefly the freely available FSL software package, within which most of the research covered in this paper has been implemented.

Section snippets

Functional MRI analysis research

The fundamental challenge in the analysis of functional MRI experiments is to identify voxels that show signal changes varying with changing brain states. This is a difficult problem: firstly because the signal to noise ratio is generally poor, with the activation signal being often no larger than the noise level; secondly, the neurophysiology that couples the underlying brain activity to the measured response in FMRI is complex and generally poorly understood; and thirdly, the noise consists

Structural MRI analysis research

This section presents an overview of our research into the analysis of structural MRI data. The tools resulting from this research provide the means for making quantitative measurements of physiologically or clinically relevant parameters. For example, the combination in SIENA of brain extraction, tissue-type segmentation, and robust affine registration allows for the accurate measurement of temporal brain-volume change. However, these tools are also of crucial importance in the processing

FDT—diffusion and white matter connectivity analysis

The self-diffusion of water molecules in the brain is a sensitive probe of biological tissue microstructure and micro-biophysics. Among the tissue properties that contribute to the local diffusion characteristics is the local orientational structure of the tissue; most interestingly, diffusion is anisotropic in white matter, being greater in the direction of white matter tracts. By sensitizing the magnitude of the NMR spin-echo to local diffusion and by making assumptions about the structure of

PRELUDE and FUGUE—EPI distortion correction

Distortion of EPI-based functional images is a particular problem for high-field (3T and higher) MR scanners. The inhomogeneities in the magnetic field caused by susceptibility differences at air–tissue interfaces (predominantly near air-filled sinuses) result in both signal loss and geometric distortion of images. Such artefacts are particularly noticeable in the inferior temporal and frontal lobes, and restrict the use of standard FMRI or diffusion imaging techniques in these areas. In

FSL—FMRIB's software library

Most of the research carried out by the FMRIB Analysis Group has been made available to the wider community as a single integrated software package, FMRIB's Software Library (FSL). FSL is available as both source code and as self-contained binary distributions for Linux, MacOS X (Apple), Windows XP (under Cygwin), Solaris (Sun), and IRIX (Silicon Graphics). It is freely available for academic (noncommercial) use. Almost all tools can be run both from the command line and via GUIs. The FSL

Acknowledgments

We are grateful for financial support from the UK Medical Research Council, the UK Engineering and Physical Sciences Research Council, The Wellcome Trust, GlaxoSmithKline, and the Medical Images and Signals Inter-disciplinary Research Consortium (MIAS IRC). We also acknowledge vital collaborations with the many individuals listed at www.fmrib.ox.ac.uk/fsl/contributors.html.

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