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

Luis Ibanez luis.ibanez at kitware.com
Mon Dec 7 13:08:08 EST 2009


Hi motes,

Well,
the change in the number (and meaning of parameters)
certainly changes the optimizer space.

I guess you may have to post a more specific and precise
question....


     Regards,


            Luis


-------------------------------------------------------------------------------------
On Mon, Dec 7, 2009 at 11:10 AM, motes motes <mort.motes at gmail.com> wrote:
> 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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>>
>


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