[Insight-users] different interpolators

[Luis Ibanez]

Hi Yu,

When you use a BSpline interpolator, your Moving image is
implicitly smoothed by using a kernel of 4x4x4 pixels.

When you use a Linear interpolator, your Moving image is
implicitly smoothed by using a kernel of 2x2x2 pixels.

If your moving image is particularly noisy, it is to expect
that the BSpline interpolator will give better registration
results.



Easy way to verify/refute this guess:


    Run a Gaussian smoothing filter on the moving
    image, and then use this smoothed moving image
    as the new moving image in your registration.
    If you use a Gaussian sigma that is about 2 pixels
    wide, the result of the Linear interpolator should
    be closer to the Bspline.

    Note that the SmoothingRecursiveGaussianImageFilter
    expects Sigma to be specified in millimeters, not
    in pixels, so... take a look at your pixel size.



Just for the record,

You may want to be more careful when inferring generic
statments out of particular experiences.

The fact that *one* registration experiment is performing
poorly with a particular interpolator y by far not enough
for concluding that that interpolator cannot produce good
results. Every registration problem has between 10 and 30
parameters that must be fine-tunned. Different sets of
parameters will produce different results.

An Algorithm without its parameters
is an incomplete entitiy.




   Universal statements are almost always false.




  Regards,


      Luis




---------------------------------------------------------------
Yu Qi wrote:

> I use linear interpolater and BSpline(3rd order) interpolator 
> separately in my application of registration.
>  
> The result of using BSpline interpolator is very good, I can see it from 
> the resampled image.
>  
> But the result from Linear interpolator is not good. it has a larger 
> versor value and 10mm different along Z axis. The resampled image also 
> shows so.
>  
> I try to tune the parameters with linear interpolator, I got almost same 
> results.
> Does it means sometimes the linear interpolator can not get a good result?
> 
> 
> *Best Regards!*
> ** 
> *Yu Qi*
>  
>  
> 
> 
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