[Insight-users] Geospatial registration
Garrett Potts
potts at cfl.rr.com
Thu Oct 28 10:45:45 EDT 2004
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.
>>>
>>>
>>>
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>
>
>
>
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