[Mristudio-users] questions about Fiber tracking

[Kotikalapudi Raviteja]

Dear Susumu,

Thank you for the advice. I have extracted the ROIs from the JHU
parcellation atlas. Now, I am using MRICro in order to extract FA values
for all the patient data for the ROIs where I would note the min,mean and
max values of FA for all ROIs. But is there are way where I could
automatically get my FA values for all the subjects for a specific ROI into
a .txt file.

Please let me know at your convenience.
Thank you for your time and consideration.
Thanks and regards,
Ravi


On Sat, Aug 17, 2013 at 5:36 PM, Susumu Mori <smoriw at gmail.com> wrote:

> To make our parcellation map overlapped well on your data, you need to use
> our LDDMM-based non-linear image alignment. If this cannot align the
> parcellation map, then, you need to improve the LDDMM results.
>
> Usually, following steps help;
> > use both FA and MD (or trace) map to drive the LDDMM
> > segment the ventricles and use them for the third channel of LDDMM
>
>
> On Sat, Aug 17, 2013 at 4:00 AM, Kotikalapudi Raviteja <
> raviteja.kotikalapudi at gmail.com> wrote:
>
>> Dear Susumu,
>>
>> I have been using JHU-Parcellation atlas for DTI analysis. I want to
>> extract the FA maps from corticospinal tract for which I made an ROI from
>> the JHU-Parcellation atlas. But it is not overlapping well with the FA
>> images. I need to know if there is a way to shift the ROI on the FA image?
>>
>> Your suggestions would be appreciated.
>>
>> Many thanks,
>> Ravi
>>
>>
>> On Fri, Aug 16, 2013 at 11:03 PM, Susumu Mori <smoriw at gmail.com> wrote:
>>
>>> Hi Ying,
>>>
>>> Here is my view of "registration".
>>>
>>> > Imaging is all about what is where.
>>> > When you quantify images, you have to make sure that you are measuring
>>> the same structures or locations across subjects. This act of identifying
>>> the same thing is "registration".
>>> > For example, you can manually define the hippocampus across subjects.
>>> By doing so, you identify a group of voxels that belong to the hippo and
>>> you "register" the hippo locations across subjects. You defined
>>> corresponding voxels across subjects. In this sense, manual ROI delineation
>>> is one of the registration methods.
>>> > Because the manual delineation is time consuming, people don't want to
>>> do it. Then what we do is to align all images and assume all voxels are
>>> registered automatically. This means, if I pick up an arbitrary location
>>> (like a single voxel), I can immediately locate the corresponding location
>>> (voxel) in each subject by using the same x, y, z coordinates.
>>> > Tractography can also be considered as a registration tool because,
>>> for example, we can identify a group of voxels that belong to the
>>> corticospinal tract across subjects. Therefore, there is nothing wrong with
>>> defining the cst in each subject without image-alignment.
>>> > However, there could be several reasons why you may want to do image
>>> alignment (thus voxel-by-voxel registration) first and then additional
>>> registration by tractography. First, tractography requires manually (or
>>> automatically) defined  ROIs for seed and destination. This could be done
>>> more reproducibly if all images are aligned. Second, after tracts are
>>> defined, you can easily create population-averaged probabilistic maps by
>>> simply adding the 3D masking files that define the tract locations. On the
>>> other hand, if you are just interested in voxel count (size of the tract)
>>> and FA values, image alignment may not be necessary.
>>>
>>> Susumu
>>>
>>>
>>> On Fri, Aug 16, 2013 at 2:25 AM, <wyzyf at mail.ustc.edu.cn> wrote:
>>>
>>>>
>>>>
>>>>
>>>>   Hello professor:
>>>>
>>>>     As I understood, fiber tracking analysis with DTI studio should be
>>>> a group analysis and image registration is
>>>>   necessary. Am I right?
>>>>
>>>>     I have finished the image registration with DiffeoMap through
>>>> linear and nonlinear(b0+FA) registration but I don`t
>>>>   know how to achieve group analysis and the registrated FA doesn`t
>>>> match the origin vector.
>>>>
>>>>     Thank you very much~!
>>>>
>>>>                                                     Ying Wang
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>>>
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