Hello all,
I was just curious to see if anyone has performed tractography on images obtained via MAP (mean apparent propogator) MRI. Is it even possible? If so, what’s the general workflow like. Any insight would be great! Thank yall in advance.
Cheers,
Ricardo
If you acquired your data as in the original MAP MRI paper then it is just a multi-shell sequence (with many b-values and a very high maximum b-value). So you should be able to follow our “standard” multi-shell approach: Multi-shell multi-tissue constrained spherical deconvolution — MRtrix 3.0 documentation
oh great! Thank you!
Hello, follow up on this from a year ago now that I have some participant data. So the original MAPMRI paper states that the model allows for the calculation of ODFs and SH’s from these ODFs. Is there any issue with using the ODFs/SH calculated using the dipy scripts (mapmri.py) as opposed to using the FODs/SH files calculated using the MRtrix line for tckgen? For tckgen I would be using the iFOD2 algorithm, where it used the FODs SH representation is used. Is there some processing within iFOD2 i should be aware of, for example if I provide an image file that is already in SH representation.
In summary, what I want to accomplish is implementing ACT Tractography on odfs/SHs derived from the MAPmri processing pipeline.
Any insight is much appreciated happy to clarify any points! Thank you for the time.
Please view the images of the resultant tractography below.
The mrtrix derived odfs produce more organized tract propagations compared to those odfs derived via the MAPmri.py processing pipeline. I thought this would help clarify what I was talking about in my previous reply. All parameters were kept the same, tractography was performed until 5m streamlines were obtained, sift (respective odf/fods were used for this as well) was applied to both to produce these tractograms of 1m streamlines. Any insight would be much appreciated.
