Hi, I’m trying to run an FBA with some historical GRE dti images.
I have run basic preprocessing (motion, distortion, susceptibilty, and bias field (eddy) correction) with a local pipeline.
From there, I have run and QCed dwidenoise, mrdegibbs, dwi2response dhollander. I have used the -fslgrad option throughout.
Response functions and voxel assignment looked similar to BATMAN tutorial.
At this stage, as I have a patient group and control group, I wasn’t sure whether to create group specific response means or overall average. I have done both.
I then upsampled with mrgrid
I had some trouble with have holes in my masks, but got around this by using FSL bet for mask creation (as advised on some other threads here).
I have QCed at each of these steps and everything looked fine to me.
However, when running dwi2fod, my FODs came out looking very strange and not at all like the tutorial or anything else I’ve seen.
I have run basic preprocessing (motion, distortion, susceptibilty, and bias field (eddy) correction) with a local pipeline.
From there, I have run and QCed dwidenoise, mrdegibbs, …
As with the related thread, dwidenoise and mrdegibbs cannot be run after motion / susceptibility distortion / eddy current distortion correction.
At this stage, as I have a patient group and control group, I wasn’t sure whether to create group specific response means or overall average.
If you want it to be legitimate to compare AFD values between groups, you must use the same response function for all participants. If you were to use separate response functions for different groups, then the response functions themselves could embed and hide widespread group differences.
However, when running dwi2fod, my FODs came out looking very strange and not at all like the tutorial or anything else I’ve seen.
As previously, a higher resolution / more closely zoomed image clearly demonstrating the problem is required. Some difference to other data may be expected due to the data not being spin-echo, but if there are problems with e.g. incorrect diffusion gradient table, I can’t tell from that screenshot as the individual FOD shapes can’t be seen.
