[Insight-users] Changing the size of the parameters array during registration?

motes motes mort.motes at gmail.com
Mon Dec 7 11:10:23 EST 2009


Yes that is also what I am doing now but I was more thinking of how
this affects the optimizer space.


On Sun, Dec 6, 2009 at 10:31 PM, Luis Ibanez <luis.ibanez at kitware.com> wrote:
> Hi Motes
>
> This type of run-time change is done in the Example:
>
>          Insight/Examples/DeformableRegistration15.cxx
>
> Note that the key actions that you have to take care of,
> every time that you change the size of the parameters
> array are:
>
> 1) registration->SetInitialTransformParameters( resizedArray );
> 2) optimizer->SetScales( resizedOptimizerScales );
>
> That is, the array of optimizer scales must be resized
> to the same size of the resized parameters array.
>
> Then, when you call StartRegistration() the metric and
> the registration class will initialize their internal arrays
> accordingly.
>
>
>
>      Regards,
>
>
>             Luis
>
>
> ----------------------------------------------------------------------------
> On Fri, Dec 4, 2009 at 4:50 PM, motes motes <mort.motes at gmail.com> wrote:
>> I have made a deformable image registration process that after a
>> number of iterations pauses the optimizer and based on some criterion
>> resizes the parameters array (always to a smaller size).
>>
>> The the new parameters array is thrown into the image registration
>> process and the optimization is continued (the remaining parameters
>> are copied to the new parameters array and the optimizer is updated -
>> number of optimizer scales).  The jacobian is resized accordingly in
>> the transform and so are the number of deformable nodes.
>>
>> Now I am trying to analyse the effect of resizing the parameters array
>> from the optimizer's point of view.  When the optimizer continues to
>> work on the new and smaller parameters array (which is initialized
>> with the  "surviving" coefficients from the previous parameters array)
>> the optimizer search space is actually reduced and the convergence
>> should in theory be speed up. But maybe someone has some thought on
>> this kind of "dynamic" search space reduction and its consequences?
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