[Insight-users] A Problem for MI Registration

Julien Jomier jjomier at cs.unc.edu
Sun Jan 2 15:13:40 EST 2005


Hi Weihua,

Registration often requires tuning the parameters depending on the 
optimizer, metric, and the nature of the images.

You need to play a little bit with the parameters of the registration.
Here a list of what you can do to adjust the ImageRegistration2 example.

1) Optimizer
   a) Increase the number of iterations so the registration doesn't stop 
        too quickly.
   b) Increase/Decrease the learning rate. The value of the gradient is 
multiplied by the learning rate.

2) Metric (MI)
   a) Adjust the ImageStandardDeviation for both the moving and the 
fixed images.
   b) Increase the number of Spatial Samples to achieve better convergence.

3) Pre-Processing
   In this example the preprocessing step blurs the input images. The 
problem you are having whith your binary images and the gradient 
optimizer is that if the initial translation is too far from the answer, 
the optimizer cannot follow the gradient, because the gradient is flat.

That said, using a learning rate of 20 and a number of Iterations of 
2000 and blurring the images by a factor of 3 (instead of 2) leads to a 
convergence of  Translation X = -10.4966, Translation Y = -2.33114. I'm 
confident you can adjust the translation in Y by increasing the number 
of spatial samples and/or adjust other parameters.

Hope this helps,

Julien

Weihua Xiong wrote:
> Hi:
> 
> 
> I made two images with only a WHITE PATCH in them. The White patch between
> them are 10 pixels along x direction. When I used the 'ImageRegistration2'
> to find the transfomation with MI, the result is 
> 
> 
> 
> Result =  
> 
>  Translation X = -2.42836 
> 
>  Translation Y = -0.352346 
> 
>  Iterations    = 200 
> 
>  Metric value  = 0.0369613 
> 
> 
> 
> Do you what is the reason? The fixed image and the moving image are
> attached.
> 
> 
> 
> Thanks
> 
> 
> 
> ---------------------------------------------
> 
> Weihua Xiong PH.D.
> 
> Computational Color Vision Lab
> 
> Simon Fraser University
> 
> 604-630-6060
> 
> www.cs.sfu.ca/~weihuax/personal
> 
> --------------------------------------------
> 
> 
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> 
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