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

Audrey R. Verde, Francois Budin, Jean Baptiste Berger, Aditya Gupta, Mahshid Farzinfar, Adrien Kaiser, Mihye Ahn, Hans Johnson, Joy Matsui, Heather C. Hazlett, Anuja Sharma, Casey Goodlett, Yundi Shi, Sylvain Gouttard, Clement Vachet, Joseph Piven, Hongtu Zhu, Guido Gerig, Martin Styner

    Research output: Contribution to journalArticle

    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.

    Original languageEnglish (US)
    Article number51
    JournalFrontiers in Neuroinformatics
    Volume7
    Issue numberJAN
    DOIs
    StatePublished - Jan 9 2014

    Fingerprint

    Neuroimaging
    Fibers
    Atlases
    Research Personnel
    Diffusion Tensor Imaging
    Quality Control
    Diffusion tensor imaging
    Digital Imaging and Communications in Medicine (DICOM)
    Cross-Sectional Studies
    Graphical user interfaces
    Parameterization
    Quality control
    Brain
    Statistical methods
    Imaging techniques

    Keywords

    • Diffusion imaging quality control
    • Diffusion tensor imaging
    • DTI atlas building
    • Magnetic resonance imaging
    • Neonatal neuroimaging
    • White matter pathways

    ASJC Scopus subject areas

    • Neuroscience (miscellaneous)
    • Biomedical Engineering
    • Computer Science Applications

    Cite this

    Verde, A. R., Budin, F., Berger, J. B., Gupta, A., Farzinfar, M., Kaiser, A., ... Styner, M. (2014). UNC-Utah NA-MIC framework for DTI fiber tract analysis. Frontiers in Neuroinformatics, 7(JAN), [51]. https://doi.org/10.3389/fninf.2013.00051

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

    In: Frontiers in Neuroinformatics, Vol. 7, No. JAN, 51, 09.01.2014.

    Research output: Contribution to journalArticle

    Verde, AR, Budin, F, Berger, JB, Gupta, A, Farzinfar, M, Kaiser, A, Ahn, M, Johnson, H, Matsui, J, Hazlett, HC, Sharma, A, Goodlett, C, Shi, Y, Gouttard, S, Vachet, C, Piven, J, Zhu, H, Gerig, G & Styner, M 2014, 'UNC-Utah NA-MIC framework for DTI fiber tract analysis', Frontiers in Neuroinformatics, vol. 7, no. JAN, 51. https://doi.org/10.3389/fninf.2013.00051
    Verde AR, Budin F, Berger JB, Gupta A, Farzinfar M, Kaiser A et al. UNC-Utah NA-MIC framework for DTI fiber tract analysis. Frontiers in Neuroinformatics. 2014 Jan 9;7(JAN). 51. https://doi.org/10.3389/fninf.2013.00051
    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. / UNC-Utah NA-MIC framework for DTI fiber tract analysis. In: Frontiers in Neuroinformatics. 2014 ; Vol. 7, No. JAN.
    @article{2e539499d6954250b7c255fcd877dc05,
    title = "UNC-Utah NA-MIC framework for DTI fiber tract analysis",
    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 = "Diffusion imaging quality control, Diffusion tensor imaging, DTI atlas building, Magnetic resonance imaging, Neonatal neuroimaging, White matter pathways",
    author = "Verde, {Audrey R.} and Francois Budin and Berger, {Jean Baptiste} and Aditya Gupta and Mahshid Farzinfar and Adrien Kaiser and Mihye Ahn and Hans Johnson and Joy Matsui and Hazlett, {Heather C.} and Anuja Sharma and Casey Goodlett and Yundi Shi and Sylvain Gouttard and Clement Vachet and Joseph Piven and Hongtu Zhu and Guido Gerig and Martin Styner",
    year = "2014",
    month = "1",
    day = "9",
    doi = "10.3389/fninf.2013.00051",
    language = "English (US)",
    volume = "7",
    journal = "Frontiers in Neuroinformatics",
    issn = "1662-5196",
    publisher = "Frontiers Research Foundation",
    number = "JAN",

    }

    TY - JOUR

    T1 - UNC-Utah NA-MIC framework for DTI fiber tract analysis

    AU - Verde, Audrey R.

    AU - Budin, Francois

    AU - Berger, Jean Baptiste

    AU - Gupta, Aditya

    AU - Farzinfar, Mahshid

    AU - Kaiser, Adrien

    AU - Ahn, Mihye

    AU - Johnson, Hans

    AU - Matsui, Joy

    AU - Hazlett, Heather C.

    AU - Sharma, Anuja

    AU - Goodlett, Casey

    AU - Shi, Yundi

    AU - Gouttard, Sylvain

    AU - Vachet, Clement

    AU - Piven, Joseph

    AU - Zhu, Hongtu

    AU - Gerig, Guido

    AU - Styner, Martin

    PY - 2014/1/9

    Y1 - 2014/1/9

    N2 - 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.

    AB - 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.

    KW - Diffusion imaging quality control

    KW - Diffusion tensor imaging

    KW - DTI atlas building

    KW - Magnetic resonance imaging

    KW - Neonatal neuroimaging

    KW - White matter pathways

    UR - http://www.scopus.com/inward/record.url?scp=84892618395&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84892618395&partnerID=8YFLogxK

    U2 - 10.3389/fninf.2013.00051

    DO - 10.3389/fninf.2013.00051

    M3 - Article

    AN - SCOPUS:84892618395

    VL - 7

    JO - Frontiers in Neuroinformatics

    JF - Frontiers in Neuroinformatics

    SN - 1662-5196

    IS - JAN

    M1 - 51

    ER -