[Insight-users] Optimization problem

[Fischer, Sven]

Hi all,

 

I'm doing a 2D 3D registration between fluoroscopic images and CT
images, creating a DRR. Since I have several local optima I use a multi
resolution approach. I scale the images by a factor of two and do
Gaussian blurring. So I scale in 4 steps. First I register the images
with one eighth of the original size, than with one fourth, with the
half size and finally with the original size. But I have local optima in
the first step. So it leads me to misregistration when my starting point
is too far away from the final point when my images are correct
registered. I can avoid this problem with using a different step size
for the Powell optimizer. But when I find a good step size for one
starting point it often is useless for other starting points. 

My images are cardiac images, where the aorta and the spine can be seen
very clearly. I use the Gradient Difference Metric ( not exactly the
ITK-Implementation, I changed it a bit, and it worked very well in
several tests ). 

Do you have an idea how I could find good starting points or how to
choose the step size for the Optimizer, depending on the information the
image gives me? Or should I use another Optimizer? What is your
experience? I'm looking forward to your answers.

 

Regards

Sven

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