I am working on a model in which the primary orientation is described by the eigenvector corresponding to the smallest eigenvalue (basically the opposite case of CSD).
I find mrview a great tool to visualize rapidly gradient orientations and I would like to use the “vector plot tool” for this purpose with my model.
Can anyone please tell me how to make this modifications on the source code (or where to start) to adapt this tool (vector plot tool) to my purpose?
Many thanks in advance!
You don’t need to make any modifications to the source code. The vector plot tool will display any 4D image, interpreting the first 3 volumes as the [ X Y Z ] components of the vector. So assuming you were using the
dwi2tensor | tensor2metric combination, you could get the smallest eigenvector with a command like:
dwi2tensor dwi.mif - | tensor2metric - -num 3 -vector vec.mif
i.e. using the
-num 3 option to select the smallest eigenvalue/vector.
If you’re producing images from your own model, you’d just need to provide this type of 4D image (whether in
.mif or NIfTI format), and load it in the tool.
Thank you very much for your help and clear explanation. Exactly what I was looking for.