[Insight-developers] Problems with Affine Registration

[Lydia Ng]

I don't think the dilating gaussian problem can be solved using
mutual information. As you have stated in a previous posting,
due to the symmetry, mutual information can only distinguish between
different gaussians up to an isotropic scale factor.

On the real data front, what kind of results are you 
getting with the MR brain data?

Lydia

> -----Original Message-----
> From: insight-developers-admin@public.kitware.com
> [mailto:insight-developers-admin@public.kitware.com]On Behalf Of Paul
> Hughett
> Sent: Monday, July 09, 2001 12:30 PM
> To: lng@insightful.com
> Cc: insight-developers@public.kitware.com
> Subject: Re: [Insight-developers] Problems with Affine Registration
> 
> 
> 
> > What kind of results are you getting?  Is it doing nothing at all or
> > is it converging to an unexpected solution?
> 
> I've been working most recently with the
> ImageToImageAffineMutualInformationGradientDescentRegistrationTest
> program, modified to add a scale factor within the reference gaussian,
> e.g.
> 
>     ri.Set( 200.0 * exp( - 1.1*( x*x + y*y )/(s*s) ) );
>                            ^^^^
> This corresponds to roughly a 5% isotropic scaling, and should yield
> coefficients of [0.95, 0.95] (or maybe [1.05, 1.05]) on the diagonal
> of the affine transform matrix.  What actually happens is that the
> diagonal stays within 0.001 or 0.0001 of unity.
> 
> > What happens when you fiddle with the number of iterations 
> and/or the
> > learning rates?
> 
> Doesn't seem to make any difference within the range of values that
> I've tried: roughly up to 1000 on the number of iterations, and from
> 0.0001 to 0.1 on the learning rate.  The larger learning rates seem to
> cause divergence (the images do not overlap any more!).
> 
> 
> Paul Hughett
> 
> 
> _______________________________________________
> Insight-developers mailing list
> Insight-developers@public.kitware.com
> http://public.kitware.com/mailman/listinfo/insight-developers