[MINC-users] computing similarity across images

[Alex Zijdenbos]

Hi Trisanna,

I assume you are talking about cases when the patient name/id may have been
removed or is unreliable?

I have done this in the past by performing a direct linear registration
between two scans, and then calculating a similarity metric (e.g., xcorr)
between them (using minccmp for example). Assuming there has not been too
much change in the individual's brain between the scans, this can get you
at least an indication that might be useful; but as Vladimir said, it's in
general not trivial - and a measure like this will likely give you false
positives.

-- A

On Mon, Mar 20, 2017 at 1:12 PM, Vladimir S. Fonov <vladimir.fonov at gmail.com
> wrote:

> Hello,
>
> in general this is not a trivial task.
>
> But from the practical point of view - did you try to use the contents of
> "patient:full_name" field of the image header?
>
>
>
> On 2017-03-20 11:53 AM, Trisanna Sprung-Much wrote:
>
>> Hi there
>>
>> Is there a tool that can be used to confirm that 2 images are in fact
>> images of the same patient's brain? For instance computing some sort of
>> similarity index based on 2 T1 images or outputing a probability for them
>> being images of the same brain?
>>
>> Thanks!
>>
>> Trisanna
>>
>> --
>> Ph.D. Candidate
>> McGill University
>> Integrated Program in Neuroscience
>> Psychology
>> _______________________________________________
>> MINC-users at bic.mni.mcgill.ca
>> http://www.bic.mni.mcgill.ca/mailman/listinfo/minc-users
>>
>>
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