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A hitchhiker's guide to diffusion tensor imaging

Frontiers in Neuroscience · 2013 · Vol. 7 · pp. 31–31
José Miguel SoaresPaulo MarquesVictor AlvesNuno Sousa

Abstract

Diffusion Tensor Imaging (DTI) studies are increasingly popular among clinicians and researchers as they provide unique insights into brain network connectivity. However, in order to optimize the use of DTI, several technical and methodological aspects must be factored in. These include decisions on: acquisition protocol, artifact handling, data quality control, reconstruction algorithm, and visualization approaches, and quantitative analysis methodology. Furthermore, the researcher and/or clinician also needs to take into account and decide on the most suited software tool(s) for each stage of the DTI analysis pipeline. Herein, we provide a straightforward hitchhiker's guide, covering all of the workflow's major stages. Ultimately, this guide will help newcomers navigate the most critical roadblocks in the analysis and further encourage the use of DTI.

Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsDiffusion MRIComputer scienceWorkflowArtifact (error)Pipeline (software)VisualizationSoftwareData scienceProtocol (science)Artificial intelligence

Funding

  • FP7 Health
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