ActionPlan

Comparative analysis of tractography methods/approaches

1. General Taxonomy (based on ROI requirements)- use all those presented at this conference and FSL tool
2. Reproducibility of tractography approaches
3. Our same 5 ROIs + CC. Sonia and Randy to make first pass in 1 subject, validate with Marek's lab and then send around to be sure work with algorithms.

Need data sets, appropriate ROIs. Iterate beginning with n=1 for ROI generation.

Exploration of potential data sets (UNC n=1, 10 acquisitions with 6 directions; MIND n=10, 8 acquisitions, 2x at each of 3 sites with 6 directions and 2x at 1 site with 60 directions).

Sylvain volunteers to make nrrd headers for the 10 MIND subjects data from MGH test/retest with Jeremy, Vince, Randy.

Outcome metrics

1. User interface, hardware/software (processor speed, platform, RAM), operator time

Preprocessing stream:

1. DWI with NiFTY header + gradient directions
2. Field Map correction (NMN.Iowa.MGH) if we verify that this is helpful
3. Eddy Current Correction (affine registration) (BWH)
4. nrrd (BWH)
5. weighted least squares (FSL won't match on this step) tensor estimation using #TEEM library (BWH)
6. T1 white matter mask co-registered to Eddy current corrected DWI data (NA-MIC affine registration tool) (Freesurfer white matter + ? vs. EMSegmentation- Sonia/Sylvain)
7. ROIs in DWI/DTI space
8. Affine registration transformation to bring retest into test space (use this for mapping ROIs and outcome label maps only from test to retest for each subject)

Outcome metrics:

1. Space carved (Casey's DTIprocess tool that generates a volume label map measure from traceline). This will give volumes, overlap, mean and Std Dev of FA, trace, mode. Use these for test-retest metrics. Pass these label maps to Sonia she will generate these.
2. Casey's FiberCompare multiple traceline visualization tool
3. Staple method to find common agreement (specificity and sensitivity)
4. Further discussion of how best to parameterize tracts at January AHM