Difference between revisions of "Algorithm:MGH:TenorBasedGroupComparison"

From NAMIC Wiki
Jump to: navigation, search
Line 1: Line 1:
 
== DTI Analysis: Tensor-based Group Comparison ==
 
== DTI Analysis: Tensor-based Group Comparison ==
  
Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:MGH|MGH Algorithms]]
+
Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:MGH|MGH Algorithms]]
  
 
''Objective:'' To boost statistical sensitivity for group comparisons in comparison to 'traditional' univariate tests.
 
''Objective:'' To boost statistical sensitivity for group comparisons in comparison to 'traditional' univariate tests.

Revision as of 20:33, 20 September 2007

Home < Algorithm:MGH:TenorBasedGroupComparison

DTI Analysis: Tensor-based Group Comparison

Back to NA-MIC_Collaborations, MGH Algorithms

Objective: To boost statistical sensitivity for group comparisons in comparison to 'traditional' univariate tests.

Example

The figure shows an example of the potential gain in sensitivity using a multivariate tensor test in comparison to the univariate FA test:

Multivariate vs. Univariate Test Comparison
GrpCmpGrph.jpg

Status The tensor based group comparison method was released into the FreeDiffusion environment at MGH. Paper submitted: "Statistical Group Comparison of Diffusion Tensors via Multivariate Hypothesis Testing." The implementation is in Matlab. Results are able to be visualized in Slicer.


  • Use case: 'Compare DTI images between groups using the full tensor information.'
  • Difficulty: Medium
  • Impact: Medium-High
  1. Implement in R (Whitcher/Tuch) : done
  2. Power analysis (Whitcher) : done
  3. Port to Matlab (Whitcher) : done
  4. Validate Matlab version against R (Whitcher) : done
  5. Test on group data : done
  6. Release bootstrap-only version to test group: done
  7. Port FFT method from R to matlab (Whitcher): done
  8. Implement FFT method in diffusion development environment (Tuch): done