[Insight-users] What is best registration setting for binary image matching?

[Luis Ibanez]

Hi Quy,

You may want to try the:

     OnePlusOneEvolutionaryOptimizer

that, just as the AmoebaOptimizer, doen't require the Metric
to be able to compute derivatives.


      Regards,


             Luis


------------------------------------------------------
On Fri, Oct 16, 2009 at 4:43 AM, Quy Pham Sy <phamsyquybk at gmail.com> wrote:
> Thanks guys,
>
> I check out MatchCardinalityImageToImageMetric (use exmaple in the
> guide book), it's significantly faster than mean squares metric.
> According to ItkSoftwareGuide, MatchCardinalityImageToImageMetric does
> not require "analytical derivatives" of its cost function so they use
> AmoebaOptimizer. it is  fast though, but AmoebaOptimizer just apply to
> unimodal function. I try it and the result alway fall to a local
> optimum value (which is incorrect). So question is
>
> ---> Which type of Optimizer should be use with MatchCardinality?
>
> Sorry if bothering :)
>
> quyps,
>
> 2009/10/16 Dan Mueller <dan.muel at gmail.com>:
>> Hi Quyps,
>>
>> The following metrics are designed for binary/label images:
>>    itk::MatchCardinalityImageToImageMetric
>>    itk::KappaStatisticImageToImageMetric
>>
>> Computation of these metrics is relatively simple (ie. they should be
>> faster than mean squares).
>>
>> Also, for performance make sure you configure/compile your application
>> for optimized release mode.
>>
>> Hope this helps.
>>
>> Regards, Dan
>>
>> 2009/10/15 Kishore Mosaliganti <kishoreraom at gmail.com>:
>>> If its a binary image, you can downsample it quite a bit. It won't
>>> affect your registration transform.
>>>
>>> Kishore
>>>
>>> On Thu, Oct 15, 2009 at 11:13 AM, Quy Pham Sy <phamsyquybk at gmail.com> wrote:
>>>> hi all,
>>>>
>>>> I need to match two binary images. first image actually is a subset of
>>>> second one.
>>>> The corresponding transform  between two images is composition of
>>>> translation, isotropic scaling, and centered rotation.
>>>> I use CenteredSimilarity2DTransform for my transformation type.
>>>>
>>>> In my current setting, i use: RegularStepGradientDescentOptimizer,
>>>> MeanSquaresImageToImageMetric,
>>>> NearestNeighborInterpolateImageFunction.
>>>>
>>>> But it takes more 6 minutes to finish a registration process.i think
>>>> it is long for two binary images.
>>>>
>>>> Anyone know what type of setting (metric, optimizor...etc) i should
>>>> use in this case?
>>>>
>>>> Thanks.
>>>> Quyps
>>
>
>
>
> --
> Pham Sy Quy
> HCI Lab, Advanced Fusion Technology Department,
> Room 1211, New Millennium Building
> Konkuk University, Seoul, Korea
> Mobile: +82-10-9800-8104
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