[Insight-users] parameters of viola & wells mutual information metric

[Kristina Grunewald]

Hello,

I am translating an image over another. I now want to compute the values 
of the MutualInformationImageToImageMetric at 16 different positions.
It is about 2 3d MR images.
FI:
  size:    192x256x32
  spacing: 1.875x1.875x5.0
MI:
  size:    256x256x30
  spacing: 1.5625x1.5625x6.0

I therefore normalised the 2 images, and then set the moving and the 
fixed image standard deviation to 0.4 as proposed.
As kernel function I use a BSplineKernelFunction of spline order 3.
Then I use 1% of the pixels of the larger of the 2 images.
This might of course not be enough but my question aims at sth. else.
I wonder about the computing time.
Computing these 16 values takes about 45 minutes.
I am not really translating the mi, i.e. I am not resampling it, I am 
just changing the parameters I pass the metric->GetValue() method.
Employing a gaussian kernel does't make a difference, it runs for ages.

Doing exactly the same with the mattes metric, it goes a lot faster. But 
there I have the possiblity to set histogram bins.
Computing 6400 values with 1% of the pixels and 10 histogram bins takes 
less than 10 minutes and gives me a reasonable result.

What could cause this huge difference in computing time?
Or am I applying the metric wrongly?

Thanks,
Kristina