Journal article
UNC-Utah NA-MIC DTI framework: Atlas Based Fiber Tract Analysis with Application to a Study of Nicotine Smoking Addiction
Proceedings of SPIE, the international society for optical engineering, Vol.8669, pp.86692D-86692D-8
03/13/2013
DOI: 10.1117/12.2007093
PMCID: PMC3877245
PMID: 24386543
Abstract
The UNC-Utah NA-MIC DTI framework represents a coherent, open source, atlas fiber tract based DTI analysis framework that addresses the lack of a standardized fiber tract based DTI analysis workflow in the field. 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 54 directional DWI neuroimaging study contrasting 15 Smokers and 14 Controls.
At the heart of the framework is a set of tools anchored around the multi-purpose image analysis platform 3D-Slicer. Several workflow steps are handled via external modules called from Slicer in order to provide an integrated approach. Our workflow starts with conversion from DICOM, followed by thorough automatic and interactive quality control (QC), which is a must for a good DTI study. Our framework is centered around a DTI atlas that is either provided as a template or computed directly as an unbiased average atlas from the study data via deformable atlas building. Fiber tracts are defined via interactive tractography and clustering on that atlas. DTI fiber profiles are extracted automatically using the atlas mapping information. These tract parameter profiles are then analyzed using our statistics toolbox (FADTTS). The statistical results are then mapped back on to the fiber bundles and visualized with 3D Slicer.
This framework provides a coherent set of tools for DTI quality control and analysis.
This framework will provide the field with a uniform process for DTI quality control and analysis.
Details
- Title: Subtitle
- UNC-Utah NA-MIC DTI framework: Atlas Based Fiber Tract Analysis with Application to a Study of Nicotine Smoking Addiction
- Creators
- Audrey R Verde - Psychiatry, University of North Carolina, Chapel HillJean-Baptiste Berger - Psychiatry, University of North Carolina, Chapel HillAditya Gupta - Psychiatry, University of North Carolina, Chapel Hill ; Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PennsylvaniaMahshid Farzinfar - Psychiatry, University of North Carolina, Chapel HillAdrien Kaiser - Psychiatry, University of North Carolina, Chapel HillVicki W Chanon - Psychology, University of North Carolina, Chapel HillCharlotte Boettiger - Psychology, University of North Carolina, Chapel HillHans Johnson - Electrical and Computer EngineeringJoy Matsui - University of IowaAnuja SharmaCasey Goodlett - Kitware Inc, Clifton Park, NYYundi Shi - Psychiatry, University of North Carolina, Chapel HillHongtu Zhu - Biostatistics, University of North Carolina, Chapel HillGuido Gerig - Scientific Computing and Imaging Institute, University of Utah, Salt Lake CitySylvain Gouttard - Scientific Computing and Imaging Institute, University of Utah, Salt Lake CityClement Vachet - Psychiatry, University of North Carolina, Chapel Hill ; Scientific Computing and Imaging Institute, University of Utah, Salt Lake CityMartin Styner - Psychiatry, University of North Carolina, Chapel Hill ; Comp. Science, University of North Carolina, Chapel Hill
- Resource Type
- Journal article
- Publication Details
- Proceedings of SPIE, the international society for optical engineering, Vol.8669, pp.86692D-86692D-8
- DOI
- 10.1117/12.2007093
- PMID
- 24386543
- PMCID
- PMC3877245
- NLM abbreviation
- Proc SPIE Int Soc Opt Eng
- ISSN
- 0277-786X
- eISSN
- 0277-786X
- Grant note
- U54 EB005149 / NIBIB NIH HHS R01 HD055741 / NICHD NIH HHS P50 MH064065 / NIMH NIH HHS R01 MH091645 / NIMH NIH HHS P30 HD003110 / NICHD NIH HHS
- Language
- English
- Date published
- 03/13/2013
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Psychiatry; The Iowa Institute for Biomedical Imaging; The Iowa Initiative for Artificial Intelligence; Iowa Informatics Initiative
- Record Identifier
- 9984221629502771
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