DTI Processing - Software Tools
When starting out in a new imaging field like diffusion tensor imaging it is easy to be overwhelmed by different processing steps and tools.
A recent publication from Frontiers in Neuroscience tries to offer an answer to most of these questions in their appropriately named article: "A hitchhiker's guide to diffusion tensor imaging". You can find the full manuscript here.
The article discusses sources of artifacts during acquisition and how to reduce/correct them, they go into some detail on how to do quality control (see more on this here), what skull stripping methods are available, how you can use RESTORE for robust tensor estimation, etc.
Most importantly, they supply an exhaustive list of DTI software packages that I adapted into the below table.
DTI tools
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Pre-processing
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Tensor estimation
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Fiber tracking
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ROI-analysis
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Registration
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Pre-processing
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Tensor estimation
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Fiber tracking
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ROI-analysis
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Registration
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Reference: J.M. Soares, P. Marques, V. Alves, N. Sousa (2013). A hitchhiker's guide to diffusion tensor imaging, Frontiers in Neuroscience.
For my own research I use a combination of packages: FSL for preprocessing, Camino for tensor fitting and fiber tracking, DTI-TK for tensor based normalization and TrackVis for visualization and ROI- analysis.
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Reference this post as: Do Tromp, DTI Processing - Software Tools, The Winnower3:e146057.73165 (2016). DOI:10.15200/winn.146057.73165
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Reference this post as: Do Tromp, DTI Processing - Software Tools, The Winnower3:e146057.73165 (2016). DOI:10.15200/winn.146057.73165
