well the T1 map is not always there, this depends on the license on the siemens console
About mp2rage, the way we process it, is to compute the the brain mask with the second inversion time, and then we report the mask on the UNI volume and we run freesurfer on the masked image
Cheers
The best way to deal with the noise structure in MP2RAGE images is to get rid of it - see http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0099676
Sadly, the Siemens product recon does not include this. If you have the two inversion times as complex images (mag/phase or real/imaginary), then I’ve implemented the robust method here: https://github.com/spinicist/QUIT/blob/mt/Source/Relaxometry/qimp2rage.cpp
nipype interface coming soon…
I guess some of you are aware of this but…
I have not used it yet but I am fairly sure that the CBS tools (http://www.cbs.mpg.de/institute/software/cbs-tools) include a module to get rid of the noise in the MP2RAGE and the nighres implemetation of the toolbox also include the skull stripping module (https://nighres.readthedocs.io/en/latest/brain/mp2rage_skullstripping.html).
Maybe this could help.
Hi @anuyapatil
Could you update me with how you dealt with the MP2RAGE data?
Currently, I have a dataset with INV1, INV2,and UNI images, and I’m looking to use fMRI Prep v1.2.5.
Thank you for your help in advance 
Cheers!
This is still an unresolved issue: https://github.com/poldracklab/smriprep/issues/18. Any help would be more than welcomed.
Hi @TribikramT
I am no longer using mp2rage. But when I tried my hand at it as part of a pilot project, I was having trouble skull stripping. Nighres didn’t do a good job, and getting the brainmask from INV2 and applying it to UNI still left some noise around the meninges.
If you find a better way, please let us know!
Hi @anuyapatil, and @ChrisGorgolewski
Thank you for your replies.
I am currently collecting some pilot data, and will keep you posted if I figure out how to deal with mp2rage data.
Cheers!
Hi @ChrisGorgolewski and @emdupre
Just wondering about fMRIPrep handling MP2RAGE data.
Currently, we’re acquiring a T1_INV1, T1_INV2, and a T1_UNI image. Seeing that fMRI prep doesn’t handle MP2RAGE data, what we’ve done is:
i) Used N4BiasFieldCorrection on the T1_INV2 image
ii) Used BET to get a mask from the image from step (i)
iii) Applied the outskin_mask from step (ii) to the T1_UNI image
iv) And fed the image from step (iii) as the T1w.nii.gz to fMRIPrep.
When doing these steps, what we’ve noticed is that while fMRIPrep accepts the newly formed T1w.nii.gz image well, it struggles with skull-stripping i.e., the borders don’t get the full brain. Therefore, we were wondering whether it was possible to feed in a skull-stripped T1w.nii.gz image to fMRIprep instead, disable skull-strip in fMRIPrep, and run the rest of the preprocessing steps as normal.
Thank you.
Cheers,
Thapa
This is not possible ATM
What version of fMRIPrep you are using?
I’m using fMRIPrep v1.2.5
Could you give a quick go to fmriprep-1.4.0? We’ve improved brain extraction and it may work out for you now.
I wrote a Docker image for our lab that we use to preprocess MP2RAGE images in such a way that they look a bit more like traditional MPRAGE images that fmriprep can handle.
Might be of interest to some of you:
https://github.com/VU-Cog-Sci/mp2rage_preprocessing
In my experience, at submillimeter resolution, manual editing, especially the removal of the sagital sinus, is strictly necessary.
Hi @oesteban,
I had a go with fMRIPrep v1.4.0, and here are the results when compared to v1.2.5. It seems I’m getting the same error (see green arrows in the see images below).
Thank your for the link. I will give it a go and keep you posted.
Thank you.
Cheers,
Thapa
Not really, the only change since these messages were posted is that now fMRIPrep allows you to feed a skull-stripped T1w image (there’s an argument to indicate this, please check the usage documentation because I don’t remember it on top of my head). So, you potentially can skull-strip the MP2RAGE on your own and pass that into fMRIPrep. Please let us know if that worked out.
Hi @brai
Sorry, we’ve put this analysis on hold, and moved forward with other projects. Hopefully, what @oesteban’s suggested helps you 
Good luck!
@oesteban
Again checking for updated recommendations (MP2RAGE in 7T).
or the best way currently is to add --skull-strip-t1w skip?
Dear all,
I have not tried to use it as input for fMRIPrep yet, but a simple multiplication (e.g. with fslmaths) of inv2 and T1w from MP2RAGE already leads to images that look very similar to MPRAGE. Any thoughts why this could be a bad idea as long as the images are only used for spatial processing of fMRI data with tools not capable of directly using MP2RAGE (and not for tasks like actual morphometry)?
Hi I think this strategy is valid for both morphometry and spatial processing of fMRI data.
I recently came across this project that does exactly that: preparing mp2rage for freesurfer, doing so by multiplying UNI by INV2 image.
Otherwise, the more “traditional” way to deal with MP2RAGE UNI data is to use the Robust background removal method introduced by O’Brien et al (2014), that you can find in different flavors:
You can find other options, there is at least another one cited in this thread.
Hi all, I am encountering the same issues with MP2RAGE anatomical images and would like to use them in fMRIprep for surface reconstructions and all further processing. Is there any update on this issue with regard to an implementation of MP2RAGE processing in fMRIprep? Or do people still follow any of the suggestions above (presurfer, 3dMPRAGEise, O’Brien 2014, feeding skull-stripped images to fMRIprep) and see which works for their specific use-case? Thank you for any responses!
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