Mtnormalise: spurious FODs outside brain mask

Hi everyone,

I use the mtnormalise command for intensity normalisation. I get weird FODs around the nose area in some patients and I was wondering if anyone has experienced a similar issue.

Here is a picture of WM FODs from dwi2fod msmt_csd before normalisation. It seems fine.

After normalisation with mtnormalise, I get spurious FODs in a corner of the image:

This is the command I used to generate normalised WM FOD:

mtnormalise wmfod.mif wmfod_norm.mif gmfod.mif gmfod_norm.mif csffod.mif csffod_norm.mif -mask brain_mask.mif

The brain mask I provided is correct, as shown in this picture:

I get this issue in 4 out of my 7 patients.
Does anyone have a idea about what happened here?

Thank you,
Olga Trofimova

Hi Olga,

The issue here arises because the smoothly-varying bias field that is estimated within the processing mask is applied throughout the whole image. You can think of this as the “shape” of the bias field being projected beyond the outer extremities of the mask. Now this is actually a desirable feature - we specifically recommend not using the dwibiascorrect -fsl algorithm precisely because it doesn’t do this - but in some extreme cases that extrapolation of the bias field beyond the brain region can lead to extreme values.

What I would suggest doing in your case is using the mrcrop command to reduce the field of view of the DWI data to only encompass the brain region. The field estimated by mtnormalise will be exactly the same, but the extreme extrapolated values in the nose region won’t be applied because the image no longer extends that far spatially.


Hi @OlgaTrofimova,

If you’ve got a good brain mask (which is certainly the case in your screenshots) that positively includes all regions of the brain you’re interested in, you might as well provide that mask via -mask to the CSD step itself. This will not only reduce computation time quite drastically, but simply not compute FODs in non-brain regions. Depending on what subsequent processing you’re planning on doing, this might in fact be highly desirable to avoid accidentally making use of those non-brain FODs. Doing so will basically also avoid applying e.g. bias fields far beyond the brain mask from which they were estimated.

Just make sure you’re 100% happy with your brain mask and all regions it includes before proceeding. Even when you’ve got a good brain mask like the one you show, it will typically still not include e.g. parts of most cranial nerves. I’ve recently been involved in several works where we had the sensitivity to detect or observe effects in such nerves; but of course it always required these to be present in the mask.


Dear Rob and Thijs,

Thanks a lot for your answers. This clarifies many things, including why I always get some tiny little FODs all over the image even outside the patient’s head!

I suppose that doing mrcrop on the FOD file with the -mask option is equivalent to providing the same brain mask to the CSD, except the second option will save me some computational time beforehand. Is that correct?


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Hi Olga,

Yep, no worries. That’s exactly why! :wink:

Well yes, but not via mrcrop though! Use e.g. mrcalc with -mult to multiply the binary brain mask with the FOD image (or any other image, for that matter) to set all values outside of the binary brain mask to zero. mrcrop has a different purpose: that one is to crop the entire field of view of the image (i.e. the size in voxels of the “bounding box” of your image). The mask in mrcrop is used to determine the size/extent of the that bounding box. Also, it won’t “mask” your image actually, only change the field of view.

Absolutely. Not even “some”, but likely a lot: in a typical field of view, there’s a very large number of non-brain voxels compared to brain-voxels. Give it a shot, and see how much is impacts computation time for sure. :wink:


I did the test on one subject and it took 3’10’’ without -mask vs 55’’ with -mask.
Multiplied by hundreds of subjects, indeed it makes a huge difference!
Plus I like the clean result with the mask option, and no more extreme values outside the brain when I normalise :slight_smile:

Thanks for the help!

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Yep, that’s a solid factor 3. It’s quite surprising how many non-brain voxels are in a typical field of view! (this factor should quite directly relate to that ratio)

Absolutely; it’s a no-brainer. :rofl: (sorry, that pun came out of nowhere :wink:)

No worries at all! :+1: