[Insight-users] Cost function value over a region
Luis Ibanez
luis.ibanez at kitware.com
Mon Dec 20 18:45:09 EST 2004
Hi Martin,
Some questions:
A) What "GetNumberOfPixels()" method are you exactly calling ?
I don't think there is a method with this name on the
Image metrics...
B) The number of samples used shouldn't be the full number
of pixels in the image. That will be a killer for the
performance of the metric. The number of samples should
be in the range of 2%-10% of the total number of pixels.
C) What specific implementation of Mutual Information are you using ?
There are 4 of them in ITK:
- Viola & Wells
- Mattes
- KullbackLiebler
- NormalizedMutualInformation
http://www.itk.org/Insight/Doxygen/html/group__RegistrationMetrics.html
Please let us know,
Thanks
Luis
----------------------------
kavec at messi.uku.fi wrote:
> Hi Luis.
>
> thanks for your message.
>
> Quoting Luis Ibanez <luis.ibanez at kitware.com>:
>
>
>>Hi Martin,
>>
>>Your code seems to be ok.
>
>
> Wow. This really makes me happy.
> :)
>
>
>>How small is the region in your mask ?
>
>
> It is maybe a 1/4 to 1/3 of moving image. I used metric's function
> "GetNumberOfPixels" to find out how many pixels were considered for metric
> calculation and no matter if I use the mask or not, I always get the same number
> equaled to total number of pixels in the image. Is this correct.
>
>
>>Note that Mutual Information is actually computed by
>>selecting a small number of pixel samples from your
>>image. That number is typically as low as 50. In your
>>case it may be happening that the 50 samples are still
>>falling inside the region of your mask, and therefore
>>there is no difference between using the mask or not.
>>
>>
>>If you only want to compute the Mutual Information
>>between two images, you should rather use the example
>>in the Statistics directory:
>>
>> Insight/Examples/Statistics/
>> ImageMutualInformation1.cxx
>>
>
>
> Great! I didn't know about this one. I'll give it a try.
>
>
>>In this example, Mutual Information is computed from the
>>full joint histogram without attemting to do estimation
>>from a subset of samples. This approach is not efficient
>>for registration because the computational time is too
>>long. However, for your application, time doesn't seem
>>to be a critical factor.
>>
>>
>>Please let us know if you have further questions,
>>
>>
>>
>> Thanks
>>
>>
>> Luis
>
>
> Thanks,
>
> Martin
>
>
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