[Insight-users] Parameter scales for registration (second try)

[Matt McCormick]

Hi Joel,

Can you get the same effect by tweaking the scales and/or increasing
the step size?

Thanks,
Matt=

On Thu, Apr 25, 2013 at 3:10 PM, Joël Schaerer <joel.schaerer at gmail.com> wrote:
> Hi all,
>
> Certain registration transforms have parameters with very different ranges
> of acceptable values. If uncorrected, this leads to serious problems with
> simple optimizers such as ITK's regular step gradient optimizer.
> Fortunately, ITK provides a parameter scale scheme to cope with this
> problem.
>
> Currently, this scheme is implemented by multiplying components of the
> parameter gradient by the parameter scales. The gradient vector is then
> uniformly scaled so that its norm is equal to the current step size.
>
> The problem with this is that it would make more sense to make larger steps
> in the directions along which the metric varies slowly (eg. the translations
> in the affine transform).
>
> My solution so far is to re-use the scale parameters to re-scale the
> resulting vector in the StepAlongGradient method of the
> itkRegularStepGradientOptimizer class:
>
>   for ( unsigned int j = 0; j < spaceDimension; j++ )
>     {
>     newPosition[j] = currentPosition[j] + transformedGradient[j] * factor /
> scales[j];
>     }
>
> I've made a little graph to explain the situation:
> http://i.imgur.com/DE6xqQ5.png
>
> Does this sound reasonable? I have good results on the particular
> (unfortunately confidential) transform I am currently using. However if
> there is interest I could test the effect on affine registration.
>
> Joel
>
> PS: I've looked briefly at the v4 optimizers. There is now a way to set the
> scales automatically, but the way they are used doesn't seem to have
> changed.
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