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

[Luis Ibanez]

Hi Kristina,

In general terms, the computation time of one GetValueAndDerivatives()
call of the MutualInformation metric, is proportional to he number of
Sampling points.

Note that, it has been shown both theoretically and experimentally
that the number of sampling points is almost irrelevant for the
results of registration based on Mutual Information.

So, in principle, you want to experiment by reducing the number of
sampling points in this metric.


Note that your choice of the KernelFunction is also critical for
the run-time performance of this metric. Did you found the BSpline
Kernel to be faster than the default GaussianKernel ??


Please let us know,


    Thanks


      Luis



-------------------------
Kristina Grunewald wrote:

> 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
> 
> 
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