Dear Elisa,
On 9 Nov 2016, at 12:21, Elisa Marchetta wrote:
> Dear Christian,
> thank you for your quick reply.
>
> Here the details you asked for:
>
> - I'm trying both on healthy subjects and on a population
> characterized by a disease, in this case when necessary we alreday
> masked alterations to avoid segmentation problems.
> In both cases we have a wide age range, from 7 months to 14-17 years
> and we're using TPM different by TOMs to cover also the youngest ages
> not included in TOM.
The TOM toolbox only supports ages from 5-18 years and these data should
also work with CAT12 without any larger issues. However, children data
younger than 2 years will be difficult or impossible to process with
CAT12 even if you have customized TPMs or templates. The changes due to
development and the differences to adult brains are simply too large and
registration and segmentation will usually fail. If you have even
younger subjects the intensities in the T1 image are also affected
(inverse) and only customized software can deal with these data.
Moreover, it will be difficult at all to process and more important to
analyze data in that large age range because the changes due to
development will be huge. This will be a general issue if you include
subjects younger than 2-5 years (difficult to define a cutoff) because
it will be difficult or not meaningful to create a template that fits to
all data. If you use different templates you will have a bias due the
template selection and cannot analyze the data together.
However, if you don’t want to analyze all data together this will be
easier to handle and you can use the same customized template for a
certain age range. Again, you have to think about excluding the subjects
which are too young because of processing issues.
Maybe Marko Wilke can also comment because he has more experience with
children data and has maybe already tried to process data < 2 years of
age.
Best,
Christian
>
> - I've already reset the origin in AC both in TPMs and our images to
> minimize realignment errors.
> I was wondering if using different options of affine regularization as
> the "average size template" instead of the default "ICBM space
> template", may influence the results about surface.
>
> Otherwise, since my aim is to obtain values in some specific areas, is
> it possible to bypass the default internal atlas, generate surfaces
> for the whole brain without separating the two hemispheres and then
> use ad hoc templates, in the same space of TPMs, to separate the two
> hemispheres and to extract values only from the regions of interest?
>
> Thank you
> Elisa
>
> On Wed, 9 Nov 2016 09:45:56 +0000, Christian Gaser
> <[log in to unmask]> wrote:
>
>> Dear Elisa,
>>
>> On Tue, 8 Nov 2016 10:27:33 +0000, Elisa Marchetta
>> <[log in to unmask]> wrote:
>>
>>> Dear CAT experts,
>>>
>>> I started using CAT12 to calculate cortical thickness and sulcal
>>> depth.
>>>
>>> After some tests on adults' T1 images, I've started using it on
>>> pediatric population. To have a more accurate segmentation I changed
>>> the default TPM with specific pediatric TPM of corresponding age.
>>
>> Here I need more information: What type of pediatric population (age,
>> any diseases?) and what kind of specific TPM have you used (using TOM
>> toolbox, or any other TPM)?
>>
>>> The segmentation works perfectly and in many cases the surface
>>> calculation too.
>>>
>>> Unfortunately in many other cases, during the surface calculation,
>>> something goes wrong and in the results the two hemispheres are
>>> badly recognized, with the left hemisphere taking into account also
>>> a great portion of the right one and the right hemisphere cut in a
>>> bad way.
>>
>> CAT12 uses an internal atlas to divide the hemispheres and to fill
>> subcortical structures and ventricles. If your pediatric data deviate
>> too much this internal atlas might not fit very well. However, the
>> issues could be also caused by realignment errors. Please can you try
>> to set the AC first and run the preprocessing again for a few
>> selected subjects, where these issue occured.
>>
>> Best,
>>
>> Christian
>>
>>>
>>> I guess the problem is related with age, but sometimes subjects with
>>> the same age and similar images have very different results.
>>>
>>> Do you have an idea on how can I solve this problem?
>>>
>>> I thank you in advance for any advice about it
>>> Best regards
>>> Elisa
>
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