UNC-Utah NA-MIC framework for DTI fiber tract analysis
Public Deposited- Creator
- Verde, Audrey R.
- Budin, Francois
- Berger, Jean-Baptiste
- Gupta, Aditya
- Farzinfar, Mahshid
- Kaiser, Adrien
- Ahn, Mihye
- Johnson, Hans
- Matsui, Joy
- Hazlett, Heather C.
- Sharma, Anuja
- Goodlett, Casey
- Shi, Yundi
- Gouttard, Sylvain
- Vachet, Clement
- Piven, Joseph
- Zhu, Hongtu
- Gerig, Guido
- Styner, Martin
- Abstract
- Diffusion tensor imaging has become an important modality in the field of neuroimaging to capture changes in micro-organization and to assess white matter integrity or development. While there exists a number of tractography toolsets, these usually lack tools for preprocessing or to analyze diffusion properties along the fiber tracts. Currently, the field is in critical need of a coherent end-to-end toolset for performing an along-fiber tract analysis, accessible to non-technical neuroimaging researchers. The UNC-Utah NA-MIC DTI framework represents a coherent, open source, end-to-end toolset for atlas fiber tract based DTI analysis encompassing DICOM data conversion, quality control, atlas building, fiber tractography, fiber parameterization, and statistical analysis of diffusion properties. Most steps utilize graphical user interfaces (GUI) to simplify interaction and provide an extensive DTI analysis framework for non-technical researchers/investigators. We illustrate the use of our framework on a small sample, cross sectional neuroimaging study of eight healthy 1-year-old children from the Infant Brain Imaging Study (IBIS) Network. In this limited test study, we illustrate the power of our method by quantifying the diffusion properties at 1 year of age on the genu and splenium fiber tracts.
- Date of publication
- 2014
- Keyword
- DOI
- Identifier
- PMID: 24409141
- PMCID: PMC3885811
- Onescience id: cfa9809db476a8f8d4f7c21ec5b7448a8c74ebe6
- Publisher DOI: https://doi.org/10.3389/fninf.2013.00051
- Resource type
- Article
- Rights statement
- In Copyright
- Journal title
- Frontiers in Neuroinformatics
- Journal volume
- 7
- Language
- English
- ISSN
- 1662-5196
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