Hi,
Voxelwise SIENA Statistics can also run all 3 pairings?
Sorry for stupid question...
bsjeong
--------------------------------------------------------------------
SIENA can only take in two images, but you can run all 3 pairings and
combine the results in a number of statistical ways.
You might look at Frost et al Statist. Med. 2004; 23:3275–3286
Cheers, Steve.
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Steve Smith wrote:
> Hi,
>
> On 1 Feb 2007, at 15:58, Bum Seok Jeong wrote:
>
>> Hi,
>>
>> In my case, neck area is always remained after BET during SIENA.
>> If I have segmented brain (WM, CSF, GM), is there any way to bypass
>> only the segmentation process of SIENA?
>
> Well, you could edit $FSLDIR/src/siena/siena_diff.cc and change
> if(1) // always done unless the above uncommented and used instead of
> this test
> to
> if(0)
>
> and it will use the pre-existing segmentations
>
>> In my knowledge, SIENA is a tool to compare between two time point in
>> same subject.
>> Is it possible to compare among three time point in same subjects
>> like repeated measure anova?
>
> SIENA can only take in two images, but you can run all 3 pairings and
> combine the results in a number of statistical ways.
>
> You might look at Frost et al Statist. Med. 2004; 23:3275–3286
>
> Cheers, Steve.
>
>
>
>
>>
>> Bests,
>>
>> bsjeong
>>
>>
>>
>> Steve Smith wrote:
>>> Hi,
>>>
>>> At this point SIENAX does not use betsurf to generate the skull
>>> outline, it uses the simpler skull output by bet itself. Hence the
>>> brain extraction and the skull estimation are both estimated at the
>>> same time by the same call to bet at the start of SIENAX. Hence
>>> whilst it is easy to change SIENAX to allow you to hand edit the
>>> brain extraction, it's not so easy to feed that hand editing into
>>> the skull estimation.
>>>
>>> However, I'd be surprised if this made much difference anyway - the
>>> bet skull estimation has always been quite rough, but that is fine
>>> for the purposes of fixing the scaling constraint in SIENAX. If you
>>> use the -d option in SIENAX you can check the intermediate stages,
>>> but it's probably working fine.
>>>
>>> Cheers, Steve.
>>>
>>>
>>> On 1 Feb 2007, at 00:23, Russell Chu wrote:
>>>
>>>> Hi All,
>>>> Currently, I'm using BET to generate a brain mask, which I
>>>> hand-edit and use
>>>> to extract the brain from T1-weighted MR images. Just by visual
>>>> inspection,
>>>> it seems that brain masks requiring significant hand-editing also
>>>> have less
>>>> accurate skull outlines generated with BETSURF. If this is the
>>>> case, then
>>>> less accurate inner skull outlines may adversely affect the inverse
>>>> v-scaling values from SIENAX. Would it be possible to somehow take
>>>> advantage of the hand-edited masks by inputting them into SIENAX to
>>>> improve
>>>> the inverse v-scaling value? Any input would be greatly appreciated.
>>>> Thanks in advance.
>>>>
>>>> Cheers,
>>>> Russell Chu
>>>
>>>
>>> ---------------------------------------------------------------------------
>>>
>>> Stephen M. Smith, Professor of Biomedical Engineering
>>> Associate Director, Oxford University FMRIB Centre
>>>
>>> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
>>> +44 (0) 1865 222726 (fax 222717)
>>> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
>>> ---------------------------------------------------------------------------
>>>
>
>
> ---------------------------------------------------------------------------
>
> Stephen M. Smith, Professor of Biomedical Engineering
> Associate Director, Oxford University FMRIB Centre
>
> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
> +44 (0) 1865 222726 (fax 222717)
> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
> ---------------------------------------------------------------------------
>
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