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the magnitude of the second derivative of the deformation. I see there are
gradient filters available and I guess for the second derivative, I can
pass the deformation field image to two gradient filters in succession and
then compute the magnitude. However, I would like to use a mask in my
computation. So areas under the mask should only be used and forward or
backward differences should only be used at the edges, as appropriate.

Is there a way to achieve this through existing filters?

Thank you for any help you can give me.


Cheers,

Anja

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<div dir=3D"ltr"><div><div><div><div>Hello all,<br><br></div>I am trying to=
 code some registration stuff from scratch using itk. So, I have a dense de=
formation field and I can compute various similarity measures and now I wan=
t to regularize the deformation to ensure smooth deformations.<br>
<br></div>From the literature, it seems one of the simple things to do is p=
enalize the magnitude of the second derivative of the deformation. I see th=
ere are gradient filters available and I guess for the second derivative, I=
 can pass the deformation field image to two gradient filters in succession=
 and then compute the magnitude. However, I would like to use a mask in my =
computation. So areas under the mask should only be used and forward or bac=
kward differences should only be used at the edges, as appropriate.<br>
<br></div>Is there a way to achieve this through existing filters?<br><br><=
/div>Thank you for any help you can give me.<br><br><div><div><div><div><di=
v><br>Cheers,<br><br>Anja
</div></div></div></div></div></div>

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