>> Hi, I have made a typo error in the previous email. Attach is the
edited question regarding BET.
Hi Jesper, many thanks for the prompt and very detailed explanation.
> Yeah, I've learned to ignore these values now.
> I have asked the next question before, but wonder if there is an answer to
> this question?
> If the pixels have 0 intesnity on the FA map, they would result in
> holes/blobs of "blackness" in the FA mask output from tbss_1_preproc.
> These "holes"/blobs comprise of the 0 intensity pixels and some
> surrounding pixels. Hence, the FA skeleton passing through these areas
> consequently have missing links.
> I have to run BET with -F function to remove this problem to generate FA
> maps with no 0 intensity voxels, which is not the standard way of doing
BET on DTI data. May I ask again why is it that if I run BET this way
instead of the standard way -f, the resulting FA map will no longer have
> intensity voxels?
> Dear Siew-Min,
>> and everyone else concerned with FA<0 or >1.
>> These values may seem disconcerting because we know that they are
>> "impossible", i.e. they come from voxels where the diffusion is
>> negative in some direction (indicating a black hole or some such thing
>> to which things can diffuse and disappear).
>> If instead you see it as having some set of data (your raw diffusion
>> data) affected by measurement error, and from these data you want to
>> estimate some parameters (let us say the diffusion in some direction).
>> The true value will be positive (though it can be quite small in the
>> case of hindered diffusion in white matter), and then our estimate
>> will have some finite precision that depends on the quality of the
>> data (SNR, # of directions etc). So, typically we will not calculate
>> the "true" value, but some value that is drawn from a distribution
>> around the true value (known as the "sampling distribution").
>> In some instances the true value is small (i.e. close to zero), and
>> then the sampling distribution (i.e. values that we may calculate)
>> will extend across zero. Then there is a chance/risk that we will
>> calculate/observe a negative diffusion value and subsequently an FA>1.
>> This might happen e.g. in highly anisotropic areas in the brain.
>> In other instances there isn't really a meaningful signal (e.g.
>> outside the brain) and the precision of our estimate will be very
>> poor, which again means that we may calculate/observe a diffusion < 0.
>> So, in short. We never get the "true" FA value. We get an estimate,
>> and that estimate can be more or less wrong (i.e. it can have better
>> or worse precision). Sometimes these "wrong" values are also
>> "impossible", but that doesn't really make them any more "wrong". It
>> just becomes a bit more obvious.
>> By increasing the quality of our data (higher SNR and/or more
>> directions) the errors become smaller and smaller, and the chance/risk
>> of calculating a negative diffusion becomes smaller. But it doesn't go
>> away. It just becomes so small that it is very unlikely that we
>> calculate/observe one given that we are only looking at a few tens of
>> thousands of voxels.
>> Therefore, I would suggest stop worrying about negative FA<0 or FA>1
>> and accept them for what they are. Noisy estimates of some unknown
>> value in the range 0-1.
>> Good luck Jesper
>> On 13 Mar 2009, at 15:11, Siew-Min Gan wrote:
>>> Hi all,
>>> I noticed my FA map output from DTIFIT has white matter brain
>>> voxels of 0 and >1. I ran the following procedures to get the FA
>>> i.eddycorrect on the original DTI
>>> ii.bet the eddycorrected data.nii.gz (or the 1st B0) to derive the
>>> iii.feed the nodif_brain_mask, data.nii.gz,bvecs and bvals into
>>> If the original data is ok, could a problem with the bvecs file result
>>> some brain voxels with 0 intensity (or intensity>1) in the FA map
>>> from the DTIFIT procedure?
>>> Initially, I thought it may be a problem with the original DTI data,
>>> however, it is a standard MGH 30 dir sequence, and the gradient file
>>> from the diffusion toolkit. I ran the data on another DTI software
>>> the FA map output doesnt seem to contain 0 intensity voxels, but it
>>> may be
>>> a scaling issue??
>>> The solution I tried with FSL is to do BET using the -F function
>>> used for 4D FMRI). The resulting FA map from DTIFIT only then will not
>>> contain 0 intensity voxels, but still have voxels of intensity>1. I
>>> this is not the standard way to process (BET) DTI data.
>>> I am concern about this as I have significant positive results from
>>> tbss FA voxel analysis. I wonder if these results would be
>>> independent of
>>> the fact that some voxels in the FA maps are >1. Also, I could not
>>> the tbss using the FA maps from the standard processing pipeline due
>>> some brain voxels having 0 intensity.
>>> May I ask if using BET with -F is ok? Has anyone has come across this
>>> problem before, and may explain why there may be voxel with 0
>>> intensity or
>>> intensity>1 in the FA maps output?
>>> Many Thanks for some kind advice.