CCB Global Shape Analysis Workflow
Overview - Global Shape Analysis (GSA) Workflow
This workflow takes raw un-skull-stripped volumes in 2 groups/populations, or a Study-Design, and generates a scene file containing the models of the ROIs where the 2 groups are different. It also reports the global 56 regional p-values.
Problem addressed by this workflow
Identifying the group differences between 2 populations in the
global shapes of 56 cortical and sub-cortical ROIs. This workflow also generates DX models of all 56 ROIs which can be viewed as a
scene in
ShapeViewer.
Detailed Workflow Usage & Specifications
- Input: Any volumetric file format can be used for the raw unskull-stripped imput images (e.g., DICOM, DIrectories, Analyze, MNC, Nifti, etc.)
- Pre-processing
- Image conversion to Analyze
- Converting to 8-bit
- Intensity Inhomogeneity correction
- Skull-stripping
- Affine Registration
- Auto Volume Parsing
- 56 Shape Modeling and Refinement
- Between-Group Statistical Analyses
- Compute various global shape measures for 56 ROIs (surface area, average mean curvature, shape-index, curevedness, fractal dimension)
- Shape Measure Tabulation
- Group comparisons per ROI
- Compute p-values
- Generate and display scene file
Pipeline Workflows
Footnotes
- Outputs and results: p-values tables and scene files illustrating the statistically significant between-group differences in the 56 ROIs using several global shape measures (see above).
- Expected times: about 3 hrs.
- Limitations: For some data/populations, the pre-processing steps (skull-stripping, tissue segmentation, etc.) may need to be improved/replaced by analogous processes (e.g., SSMA for Skull-stripping).
- Contact person/group: SIG-FLOW Team
- Pubs: Publications
- Grants: U54 RR021813, P41 RR013642
- Tools/packages used in this workflow: BrainSuite, FSL, ITK, CCB tools.
- Notes: Mature
.