[Insight-developers] [Insight-users] PLoS ONE: How Many Scientists Fabricate and Falsify Research? A Systematic Review and Meta-Analysis of Survey Data

[Hua-mei Chen]

Dear ITK Users and Developers,

        In deformable image registration, it is very common to find the
image gradient at non-grid positions. For example, to obtain the driving
force by taking the derivative of SSD similarity measure. I am wondering how
this procedure is implemented in ITK. I used to construct a continuous image
based on Bspline model and then find the derivitive at non-grid positions.
However, I recently found a MATLAB code which resamples the image based on
the current deformation field and then find the gradient at the resampled
image. In this way, there is no need to find the gradient at non-grid
positions. Afterwards, the gradient information is used to construct the
update of the deformation field and the new deformation field is obtained by
ADDING the update to the original deformation field. Is this a common
practice to implement deformable image registration algorithms like demons,
fluid, and FFD in ITK? Any response is appreciated.

Chen
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