Spatial Normalisation of 7T Data for PD calibration

[mfcallaghan]

There is no validated pipeline for spatial alignment of data in voxel space.

• What should be the segmentation input?
• What algorithm would have sufficient precision?
• How should voxels outside the brain, where the signal models don't apply, be handled?

[SiyaMRPhy]

1. Segmentation of Outer-supressed MT was not giving good results (Dataset used - 7T 0.6 mm iso travel head data)
   https://github.com/SherS2/hMRI-toolbox/blob/e0cf8a68b36cb2d667707179be628badbac5068b/hmri_create_MTProt.m#L835-L859

Solution : Used multimodal segmentation using the MTsat and T1 OLS/WLS.
https://github.com/SiyaMRPhy/hMRI-toolbox/blob/4ca24849652be03e86acb67bcd4b6501455a6511/hmri_create_MTProt.m#L962-L1057

[SiyaMRPhy]

2. Bias-field correction of masked A map. This step was also giving bad segmentation results.

https://github.com/SiyaMRPhy/hMRI-toolbox/blob/e0cf8a68b36cb2d667707179be628badbac5068b/hmri_create_MTProt.m#L1086

This was coming wrong TPM priors. Masked brain does not have eye (Eye in TMP is c3).
Defined a TPM for the masked Brain (4 tissues classes - c1, c2, c3 without Eyes, c4 = 1-(c1+c2+c3) ) and used that for the segmentation.

https://github.com/SiyaMRPhy/hMRI-toolbox/blob/4ca24849652be03e86acb67bcd4b6501455a6511/hmri_create_MTProt.m#L1344-L1401