> 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 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 0
intensity voxels?
thanks
Siemwin
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
>> map.
>> i.eddycorrect on the original DTI
>> ii.bet the eddycorrected data.nii.gz (or the 1st B0) to derive the
>> nodif_brain_mask.
>> iii.feed the nodif_brain_mask, data.nii.gz,bvecs and bvals into
>> DTIFIT.
>>
>> 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
>> output
>> 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
>> is
>> from the diffusion toolkit. I ran the data on another DTI software
>> and
>> 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
>> (normally
>> 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
>> notice
>> this is not the standard way to process (BET) DTI data.
>>
>> I am concern about this as I have significant positive results from
>> the
>> 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
>> analyse
>> the tbss using the FA maps from the standard processing pipeline due
>> to
>> 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.
>>
>> Siewmin
>>
>
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