Local Shape Analysis (LSA) Workflow

Created: 2011-04-06 00:40:19      Last updated: 2011-04-06 00:40:26

This workflow takes raw un-skull-stripped volumes in 2 groups/populations and an ROI index to generate a color-coded shape object using the per-vertex local p-values of some local shape-measure (e.g., displacement, atrophy, Jacobian, curvature, etc). It also outputs the p-values color-map superimposed on the mean shape.

Problem addressed by this workflow


Identifying local group differences between 2 populations in one specific ROI. This workflow also generates mean-shape DX model and a CCBBM *.m file with vertex-coloring using p-values, which can be viewed as a scene in ShapeViewer. The p-values color-map is:

  • Red: p<=0.05
  • Green: 0.05<p<=0.1
  • Blue: p>0.1.

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
  • Shape Modeling and Refinement
  • Computing the local Mean and Gaussian curvatures per vertex on the shape of choice for all subjects
  • Shape registration - mapping, shape-correspondences
  • Mean (atlas) shape generation
  • (Non-parametric) permutation test for statistical differences between the 2 groups locally computed on each vertex of the corresponding shapes
  • Color-coding (mapping) the p-values on the mean-shape (shape-atlas)

URL: http://www.loni.ucla.edu/twiki/bin/view/CCB/PipelineWorkflows_LSA

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