Format

Send to

Choose Destination
See comment in PubMed Commons below
Front Neuroinform. 2014 Jan 9;7:51. doi: 10.3389/fninf.2013.00051. eCollection 2014.

UNC-Utah NA-MIC framework for DTI fiber tract analysis.

Author information

1
Neuro Image Research and Analysis Laboratory, Department of Psychiatry, University of North Carolina Chapel Hill, NC, USA.
2
Neuro Image Research and Analysis Laboratory, Department of Psychiatry, University of North Carolina Chapel Hill, NC, USA ; Children's Hospital of Pittsburgh, University of Pittsburgh Pittsburgh, PA, USA.
3
Department of Biostatistics, University of North Carolina Chapel Hill, NC, USA.
4
Iowa Institute for Biomedical Imaging, University of Iowa Iowa City, IA, USA.
5
Scientific Computing and Imaging Institute, University of Utah Salt Lake City, UT, USA.
6
Kitware Inc. Clifton Park, NY, USA.
7
Neuro Image Research and Analysis Laboratory, Department of Psychiatry, University of North Carolina Chapel Hill, NC, USA ; Scientific Computing and Imaging Institute, University of Utah Salt Lake City, UT, USA.
8
Neuro Image Research and Analysis Laboratory, Department of Psychiatry, University of North Carolina Chapel Hill, NC, USA ; Department of Computer Science, University of North Carolina Chapel Hill, NC, USA.

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.

KEYWORDS:

DTI atlas building; diffusion imaging quality control; diffusion tensor imaging; magnetic resonance imaging; neonatal neuroimaging; white matter pathways

PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Frontiers Media SA Icon for PubMed Central
    Loading ...
    Support Center