Convert standard TORTOISE DTs (diagonal-first format) to standard AFNI (lower triangular, row-wise) format. NB: Starting from TORTOISE v2.0.1, there is an ‘AFNI output’ format as well, which would not need to be converted.
Part of FATCAT (Taylor & Saad, 2013) in AFNI.
- COMMAND: 3dTORTOISEtoHere -dt_tort DTFILE {-scale_fac X }
{-flip_x | -flip_y | -flip_z} -prefix PREFIX
Dxx,Dxy,Dyy,Dxz,Dyz,Dzz.
In case it is useful, one can apply ‘flips’ to the eventual (or underlying, depending how you look at it) eigenvector directions, as well as rescale the associated eigenvalues.
RUNNING: -dt_tort DTFILE :diffusion tensor file, which should have six bricks
of DT components ordered in the TORTOISE manner, i.e., diagonals first: Dxx,Dyy,Dzz,Dxy,Dxz,Dyz.
GRADFILE has N rows of gradients.
-flip_x | :change sign of first element of (inner) eigenvectors. |
-flip_y | :change sign of second element of (inner) eigenvectors. |
- -flip_z :change sign of third element of (inner) eigenvectors.
- -> Only a single flip would ever be necessary; the combination
- of any two flips is mathematically equivalent to the sole application of the remaining one. Normally, it is the gradients that are flipped, not the DT, but if, for example, necessary files are missing, then one can apply the requisite changes here.
-scale_fac X :optional switch to rescale the DT elements, dividing by a number X>0.
3dTORTOISEtoHere -dt_tort DTI/DT_DT+orig -scale_fac 1000 -prefix AFNI_DT
If you use this program, please reference the introductory/description paper for the FATCAT toolbox:
Taylor PA, Saad ZS (2013). FATCAT: (An Efficient) Functional And Tractographic Connectivity Analysis Toolbox. Brain Connectivity 3(5):523-535.