Difference between revisions of "2008 Summer Project Week:RegionalCorticalThicknessTool"
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<h1>Progress</h1> | <h1>Progress</h1> | ||
Attended: | Attended: | ||
− | * Special topic breakout: Non-rigid registration | + | * Special topic breakout: Non-rigid registration (interested in RegisterImages module) |
* Special topic breakout: GWE | * Special topic breakout: GWE | ||
− | The regional cortical thickness workflow has been developped using the module chaining method | + | The regional cortical thickness workflow has been developped using the module chaining method (Help from Marco Ruiz). |
− | Help from Marco Ruiz | + | One part of the pipeline needs to be continued (skull stripping step) |
</div> | </div> |
Revision as of 13:47, 27 June 2008
Home < 2008 Summer Project Week:RegionalCorticalThicknessTool
Key Investigators
- UNC: Heather Cody Hazlett, Martin Styner, Clement Vachet
- GE: Jim Miller
Objective
We would like to create an end-to-end application within Slicer3 allowing individual and group analysis of regional and local cortical thickness.
Such a workflow applied to the young brain (2-4 years old) is our goal in order to start a longitudinal study of early brain development in autism (UNC DBP).
See our Roadmap for more details.
Approach, Plan
Our plan for the project week is to start the development of a work flow tool allowing regional cortical thickness analysis. Pipeline:
- Tissue segmentation: itkEMSCLP (UNC external Slicer3 module)
- Skull Stripping: ImageMath and SegPostProcess (UNC Slicer3 external modules) - in progress
- Lobar parcellation registration
- Atlas to case affine registration: AffineRegistration module
- Atlas to case BSPline registration: Deformable BSpline registration module
- Applying transformation to parcellation map: Resample Volume 2 module
- Cortical Thickness: CortthickCLP (UNC Slicer3 external module)
Progress
Attended:
- Special topic breakout: Non-rigid registration (interested in RegisterImages module)
- Special topic breakout: GWE
The regional cortical thickness workflow has been developped using the module chaining method (Help from Marco Ruiz). One part of the pipeline needs to be continued (skull stripping step)