[Insight-users] Helo with bspline/mutual information/gradient descent

[J.X.J.]

Hi everyone,

I'm current using itk::BSplineDeformableTransform,
itk::MutualInformationImageToImageMetric and itk::GradientDescentOptimizer
to register 2D MRI images. My problem is that when running 2 phantom images
the output image is almost exactly the same as the original moving image
(nothing like the fixed image).

I have normalized and smoothed the 2 input images using
itk::NormalizeImageFilter and itk::DiscreteGaussianImageFilter with
SetVariance(2.0). For mutual information the standard deviation is 0.4.
Optimizer learning rate is 10.0, 200 iteration and with maximum on. This set
up is kind of a mixture of a number of deformableregistration examples on
default (as in I copied and pasted all parameter settings etc directly).

Does anyone know what the problem could be? The code runs all 200 iterations
is thats an indication, also the metric value of each iteration is around
0.2 - 0.4 if that's any help.

J.X.J.
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