Difference between revisions of "Algorithm:MGH:TenorBasedGroupComparison"
From NAMIC Wiki
| (3 intermediate revisions by the same user not shown) | |||
| Line 1: | Line 1: | ||
| − | + | Back to [[NA-MIC_Collaborations|NA-MIC_Collaborations]], [[Algorithm:MGH|MGH Algorithms]] | |
| − | + | = DTI Analysis: Tensor-based Group Comparison = | |
| − | = | + | Our objective is to boost statistical sensitivity for group comparisons in comparison to 'traditional' univariate tests. |
| + | |||
| + | = Description = | ||
The figure shows an example of the potential gain in sensitivity using a multivariate tensor test in comparison to the univariate FA test: | The figure shows an example of the potential gain in sensitivity using a multivariate tensor test in comparison to the univariate FA test: | ||
| Line 11: | Line 13: | ||
[[Image:GrpCmpGrph.jpg|thumb|182px|right|]] | [[Image:GrpCmpGrph.jpg|thumb|182px|right|]] | ||
| − | + | ''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''<nowiki>: 'Compare DTI images between groups using the full tensor information.' </nowiki> |
* Difficulty: Medium | * Difficulty: Medium | ||
* Impact: Medium-High | * Impact: Medium-High | ||
| Line 27: | Line 28: | ||
# Port FFT method from R to matlab (Whitcher): '''done''' | # Port FFT method from R to matlab (Whitcher): '''done''' | ||
# Implement FFT method in diffusion development environment (Tuch): '''done''' | # Implement FFT method in diffusion development environment (Tuch): '''done''' | ||
| + | |||
| + | = Key Investigators = | ||
| + | |||
| + | = Publications = | ||
| + | |||
| + | = Links = | ||
Latest revision as of 17:55, 22 September 2007
Home < Algorithm:MGH:TenorBasedGroupComparisonBack to NA-MIC_Collaborations, MGH Algorithms
Contents
DTI Analysis: Tensor-based Group Comparison
Our objective is to boost statistical sensitivity for group comparisons in comparison to 'traditional' univariate tests.
Description
The figure shows an example of the potential gain in sensitivity using a multivariate tensor test in comparison to the univariate FA test:
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
- Implement in R (Whitcher/Tuch) : done
- Power analysis (Whitcher) : done
- Port to Matlab (Whitcher) : done
- Validate Matlab version against R (Whitcher) : done
- Test on group data : done
- Release bootstrap-only version to test group: done
- Port FFT method from R to matlab (Whitcher): done
- Implement FFT method in diffusion development environment (Tuch): done
