Hi Christina,

DKE has some preprocessing scripts that work from dicoms, but there are some other options as well.

I like working with MRIcron for generating gradient tables and nifti images, and I have some scripts that work from their dcm2nii output, which I am happy to share. The basic idea is just co-register b0 images using SPM then average things and then create a 4D nifti image volume for DKE.

Normalizing tractography to standard space is a little more tricky. The DKE Tractography module works in image space with the bottom of the image volume at (0,0,0) and the tract coordinates in LPS. This was done for compatibility with visualization software I was working with (eg TrackVis and DSI Studio).

After running DKE and the DKE Tractography module, the FT_struct.mat file contains some of the info you need.

Do something like:

    S = load('~/FT_struct.mat');
    vox_to_ras = S.hdr.mat([S.permute_img 4],:)*[diag(S.invert_img) double(S.invert_img==-1)'.*S.hdr.dim(S.permute_img)'+S.shift*[1;1;1];0 0 0 1];

vox_to_ras is the affine transformation from image space (in LPS) to whatever coordinate system is specified in the nifti header, which can be applied to each tract in the FT_DKI.mat file.

This gets you to whatever space SPM has the images in. Then you would have to do a normalization step using SPM (or something else) to get to whatever standard space you want, which will require a non-linear transformation. You then have to apply that deformation to each of the tracts as well. I know of one script to do this from the VISTA Lab (mrAnatXformCoords.m).

Although tempting, it is not advisable to do the non-linear step before estimating the tracts. This is because there is no way that I'm aware of to deform the gradient tables (or tensors) for each region of the image which would probably cause funny stuff to happen when estimating the fiber bundle orientations.

Hope that help,

Russell