[Insight-users] Vector Gradients and transform jacobians

[Luke Bloy]

Hi everyone,

I have 2 questions.

1) Id like to be able to compute the gradient of a vector image. The 
issue is that the gradient filters I've looked at all use convolution 
with a derivative operator, which I'm not positive how to modify to work 
with vector images. So my question is... Is there a gradient filter 
already written for vector images, if not is there a finite difference 
gradient filter for computing gradients?

2) As part of a registration problem I'd like to incorporate the 
smoothness of my deformation field into cost function to be minimized. 
The way I'd like to do this is to use the Jacobian of transformation in 
the metric. The problem is that the GetJacobian method returns the 
Jacobian of the transformation with respect to the parameters, not with 
respect to the image/spatial coordinates. I'm curious if anyone has done 
this or might suggest a good way for me to implement it.

Thanks,
Luke