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

Gabriel A. Giménez gabrielgimenez85 at gmail.com
Tue Mar 10 09:03:41 EDT 2015


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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