DBP2:UNC:Cortical Thickness Roadmap
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Roadmap
Group analysis of regional and local cortical thickness of the young brain (2 years old) is one goal of the UNC DBP. This page describes the technology roadmap for cortical thickness analysis in the NA-MIC Kit.
Ultimately, the NA-MIC Kit will provide a workflow for individual and group analysis of cortical thickness. This workflow will be implemented as a set of Slicer3 modules that can be used interactively within the Slicer3 application as well as in batch on a computing cluster using BatchMake. The main modules will include:
- A - White matter/gray matter segmentation
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- UNC has a segmentation technique implemented in an ITK framework for segmenting white matter and gray matter in the young brain. This technique will be converted into a Slicer3 command line module
- Since this segmentation technique exists in an ITK framework, the integration into Slicer3 is low risk and should be completed over the next couple of months (mid fall)
- UNC will also investigate adapting the Slicer3 EM Segment module to their young brain studies. Here, UNC will adapt the UNC atlas of the 2 year old brain to provide priors for the EM Segment module
- This will be a good test case for applying the Slicer3 EM Segment module to a slightly different application. UNC should work through the training material on the Slicer3 EM Segment module and then refer to Brad Davis and Kilian Pohl as needed.
- This also should be completed before the AHM.
- UNC has a segmentation technique implemented in an ITK framework for segmenting white matter and gray matter in the young brain. This technique will be converted into a Slicer3 command line module
- B - Local cortical thickness measurement
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- UNC has an algorithm to measure local cortical thickness given a labeling of white matter and gray matter. This technique will be converted into a Slicer3 command line module
- This technique is non-symmetric and sparse (only computing distances where they can be computed reliably).
- It is expected that this module should be available before the AHM.
- Marc Niethammer was developing a technique at a previous project week that would be symmetric. This could be an alternative used as a comparison.
- UNC has an algorithm to measure local cortical thickness given a labeling of white matter and gray matter. This technique will be converted into a Slicer3 command line module
- C - Subject comparison
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- Regional as well as local subject comparisons are needed
- Regional analysis will require precise deformable registration to a young brain atlas
- NA-MIC Kit tools can be applied here
- Local analysis requires techniques which are not currently in the NA-MIC Kit
- Freesurfer could be used for the local analysis (but it is not in the NA-MIC Kit)
- Ipek is developing local analysis tools and may have a tool available in Fall 2008.
- D - Performance characterization and validation
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- Characterize response based on signal noise, patient motion, etc.
- Comparison to other tools (FreeSurfer)
To do
- Assign owners to tasks
- Define schedule
Staffing Plan
- Clement is the DBP resource charged with adapting the tools in the NA-MIC Kit to the DBP needs
- Martin is the algorithm core contact
- Jim is the engineering core contact
Schedule
- xx/xx/2007 - White matter/gray matter segmentation of the young brain using UNC technique as a Slicer3 module
- xx/xx/2007 - White matter/gray matter segmentation of the young brain using the Slicer3 EM Segment module
- xx/xx/2007 - Cortical thickness measurement using UNC technique as a Slicer3 module
- xx/xx/2007 - Cortical thickness measurement using Marc Niethammer's approach as a Slicer3 module
- xx/xx/2007 - Deformable registration of young brain regional atlas
- xx/xx/2007 - Regional analysis of cortical thickness as a Slicer3 module
- xx/xx/2007 - BatchMake workflow
- xx/xx/2007 - Groupwise regional analysis of cortical thickness as a NA-MIC Workflow
- xx/xx/200x - Groupwise local analysis of cortical thickness as a NA-MIC Workflow
Team and Institute
- Co-PI: Heather Cody Hazlett, PhD, (heather_cody at med.unc.edu, Ph: 919-966-4099)
- Co-PI: Joseph Piven, MD
- NA-MIC Engineering Contact: Jim Miller, GE Research
- NA-MIC Algorithms Contact: Martin Styner, UNC