[ITK] [ITK-users] Mattes Mutual Information Speed with 3D Images

[Bill Lorensen]

Are ITK and your app built Release?

On Tue, Mar 10, 2015 at 9:03 AM, Gabriel A. Giménez
<gabrielgimenez85 at gmail.com> wrote:
> Hi! thanks for your answer...
>
> I use images of RIRE BD (http://www.insight-journal.org/rire/), my initial
> tests I make with package training_001 (CT - MR_PD). Following
> recommendation here is my configuration:
>
>
>          metric->SetNumberOfHistogramBins( 50 );
>          double samplingPercentage = 0.002;
>          registration->SetMetricSamplingPercentage( samplingPercentage );
>          RegistrationType::MetricSamplingStrategyType  samplingStrategy  =
>
> RegistrationType::REGULAR;
>
> Unfortunately, the results were not good ... the average execution time
> remains the same (25 ~ 30 seconds). With a population size equal to 50, the
> execution time of an iteration is in the order of 25 minutes, very slow for
> me ...
>
> These are the image data:
>
> Fixed Image:
>
> ObjectType = Image
>
> NDims = 3
>
> BinaryDataByteOrderMSB = True
>
> AnatomicalOrientation = LPH
>
> ElementSpacing = 0.653595 0.653595 4.000000
>
> DimSize = 512 512 29
>
> ElementType = MET_SHORT
>
> ElementDataFile = image.bin
>
>
> Moving Image:
>
> ObjectType = Image
>
> NDims = 3
>
> BinaryDataByteOrderMSB = True
>
> AnatomicalOrientation = LPH
>
> ElementSpacing = 1.250000 1.250000 4.000000
>
> DimSize = 256 256 26
>
> ElementType = MET_SHORT
>
> ElementDataFile = image.bin
>
>
>
> Thanks and regards!
>
>
> 2015-03-10 9:59 GMT-03:00 Bradley Lowekamp <blowekamp at mail.nih.gov>:
>
>> Hello,
>>
>> Unfortunately, I can help much because of lack of information.
>>
>> I can tell you I just wrote SimpleITK registration code which uses Mattes
>> Mutual Information, Versor Rigid Transform, with a Regular Step Gradient
>> Descent optimizer . The sampling percentage for the metric is 0.2, and the
>> volumes are about 60^3 each. This is able to do the registration in about 8
>> iterations in 0.3 seconds.
>>
>> Brad
>>
>> On Mar 9, 2015, at 7:02 PM, Gabriel A. Giménez
>> <gabrielgimenez85 at gmail.com> wrote:
>>
>> > Hello everyone...
>> >
>> > I'm working on a genetic optimizer for Rigid 3D Registration.
>> >
>> > The fitness of each individual is calculated using Mattes Mutual
>> > Information, the execution time of the metric is high ... (30 seconds on
>> > average). This makes the registration too slow.
>> >
>> > Any recommendations? could improve the performance metrics? otherwise
>> > most
>> > appropriate metric?
>> >
>> > Regards!
>> >
>> >
>> >
>> > --
>> > View this message in context:
>> > http://itk-insight-users.2283740.n2.nabble.com/Mattes-Mutual-Information-Speed-with-3D-Images-tp7586971.html
>> > Sent from the ITK Insight Users mailing list archive at Nabble.com.
>> > _____________________________________
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>
>
>
> --
> Gabriel Alberto Giménez.
>
> _____________________________________
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