[Insight-users] Geospatial registration

[Garrett Potts]

Hello Luis:


Yes, I have been playing with some of those.  In your opinion which  
would be the best optimizer to use when using the mutual information  
metric?


Take care

Garrett

> Hi Garrett,
>
> You probably already know this,
> but just in case...
>
> ITK optimizers offer a mechanism for adjusting the scale
> of cost-function parameters. You pass an array of doubles
> to the optimizer and each one of them correspond to a
> scaling factor to be used for normalizing the parameters.
>
> You will find examples on the use of the scaling array,
> in the ITK Software Guide.
>
>      http://www.itk.org/ItkSoftwareGuide.pdf
>
> in the Registration chapter.
>
>
>
>    Regards,
>
>
>       Luis
>
>
>
> ---------------------------------
> Garrett Potts wrote:
>> Hello Luis:
>> Thank you for the information.  I'll try the metric for mutual  
>> information.  I was currently using  
>> MutualInformationImageToImageMetric and out of the metrics I have  
>> tried it was giving better results and the only problem that I was  
>> having now was the derivative estimates.  For our adjustable  
>> parameter interface I think I'll add a scales factor in order to  
>> compute derivatives so the change is not so large with respect to  
>> each parameter.  For a temporary fix I was dividing the partials by  
>> the largest change in pixels and this sort of got the change down to  
>> a reasonable rate.
>> I'll keep playing.  Thank you again for all the suggestions
>> Take care
>> Garrett
>>> Hi Garrett,
>>>
>>> Thanks for the detailed description of your project.
>>>
>>>
>>>>> Any suggestions on good metrics and size of the image to analyze  
>>>>> let me know.
>>>
>>>
>>>
>>> If you are registering multimodality images, your best
>>> options for metrics are the variants of Mutual Information.
>>> There are about 4 different implementations of Mutual Information
>>> in ITK, you probably want to start with MattesMutualInformation,
>>> that is one of the smoothest.
>>>
>>> For a full list of the ImageMetrics available in ITK please look at
>>> http://www.itk.org/Insight/Doxygen/html/ 
>>> group__RegistrationMetrics.html
>>>
>>> Note that you can always write your own customized Image Metric and
>>> replace it in the registration framework as you just did with the
>>> transform.
>>>
>>>
>>> About the computation of derivatives, the size of the perturbations
>>> to be used for computing derivatives by finite differences is  
>>> something
>>> that must be customized based on the dynamic range of every  
>>> individual
>>> parameter, as well as the sensitivity of the transforms to those  
>>> particular values.  For example, in a similarity transform, the  
>>> scale
>>> and rotation parameters are very sensitive to small variations.
>>>
>>> This is one of those issues that can only be solved by experimenting
>>> with the values.
>>>
>>>
>>>
>> _______________________________________________
>> Insight-users mailing list
>> Insight-users at itk.org
>> http://www.itk.org/mailman/listinfo/insight-users
>
>
>
>