[Insight-users] itkCenteredRigid2DTransform registration optimization problems

Rupert Brooks rupe.brooks at gmail.com
Tue Jan 29 16:51:38 EST 2008


Hi Felix,

I think the problem you are having could be caused by two possibilities.



> Message: 6
> Date: Tue, 29 Jan 2008 15:38:39 +0100
> From: Felix Bollenbeck <bollen at ipk-gatersleben.de>
> Subject: Re: [Insight-users] itkCenteredRigid2DTransform        registration
>        optimization problems
> To: gabri <tartuz at gmail.com>, insight-users at itk.org
> Message-ID: <479F3A6F.2040404 at ipk-gatersleben.de>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Hi Gabriele,
>
> ok, that is some kind of random search, right? - I have to read the
> paper for understanding.
>
> Was it difficult to tune the parameters? I am not using mutual
> information metric, but I will try it out.
>
> I guess I will have to anneal 'epsilon' when going to finer scales. can
> you comment on your choice of parameters?
>
> Thanks for your time!
>
> FElix.
>
>
>
>
> gabri wrote:
> > Hi Felix,
> > I've had a lot of problems with the regularstepgrdient descent , finally
> > I switch all my code to use the OnePlusOneEvolutionaryOptimizer that is
> > relly well suited for the MattesMutulaInformationMetric .
> > Using that classes , after finding the correct parameters tuning for the
> > optimizer,all problems due to miallignement disappers in my case (MRI
> > AffineRegistration) .
> >
> > Best Reguards
> >
> > Gabriele
> >
> > Felix Bollenbeck ha scritto:
> >
> >> Hi ITKusers
> >>
> >> Im using the itkCenteredRigid2DTransform to register a stack of
> >> light-microscopy slice images containing sectionend objects in masked
> >> background within the image-pyramid framework of ITK.
> >>
> >> I have a question regarding the transformtype for registration of
> >> image pairs:
> >>
> >> objects in the images I use have a kind of symmetry axes, they are
> >> 'similar' on both sides but not the 'same'. The problem is, that
> >> sometimes the optimizer gets stuck in a local optimum representing the
> >> alignment of two images where the moving images is flipped along this
> >> axis-can I make myself clear?
> >>
> >> The problem is- that on broader scales, this 'similarity' turns out to
> >> be more less 'same', which causes the parameters to remain in this
> >> 'valley' in the subsequent fine optimization on smaller scales.
> >>
> >> starting with a finer resolution ends up in bad convergence, or bad
> >> overall results.
> >>
> >> I tried to tune stepwidths, optimizer scales etc. but i couldnt find
> >> any overall tendency, due to my little detailed knowledge on the
> >> optmizer (regularstepdescent).
> >>
> >> Can anybody suggest a method how to optimize the rotation angle more
> >> carefully?
> >>
> >> Regards&TIA,
> >>
> >> Felix.
> >>
> >>
> >>
> >>
> >
> >
> >
>
>
> --
> Felix Bollenbeck                Email: bollen at ipk-gatersleben.de
> Pattern Recognition Group       Phone: +49 (0)39482 5344
> Leibniz Institute of Plant      Fax  : +49 (0)39482 5137
> Genetics and Crop Plant Research
> Correnstr.3                     http://www.ipk-gatersleben.de
> 06466 Gatersleben,Germany
>

-- 
--------------------------------------------------------------
Rupert Brooks
McGill Centre for Intelligent Machines (www.cim.mcgill.ca)
Ph.D Student, Electrical and Computer Engineering
http://www.cyberus.ca/~rbrooks


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