[Insight-users] Levenberg-Marquardt and intensity based image registration

[Alex Taylor]

Hello,

In A Pyramid Approach to Subpixel Registration Based on Intensity (Thevenaz, UE Ruttimann, Unser) http://www.ncbi.nlm.nih.gov/pubmed/18267377, they recommend using a pyramid based approach with a modified version of Levenberg-Marquardt with a sum of square differences objective function.

This makes me think I should use Levenberg-Marquardt with my intensity-based image registration tasks in ITK.

The SetOptimizer methods of the itkImageRegistrationMethod and in itkMultiResolutionImageRegistrationMethod classes enforce that the specified optimizer is a itk::SingleValuedNonLinearOptimizer<http://www.itk.org/Doxygen/html/classitk_1_1SingleValuedNonLinearOptimizer.html>. The only implementation of Levenberg-Marquardt in ITK is an itk::MultipleValuedNonLinearOptimizer<http://www.itk.org/Doxygen/html/classitk_1_1MultipleValuedNonLinearOptimizer.html>.

Why is it that the itkImageRegistrationMethod isn't built to easily support the use of Levenberg-Marquardt? Is there an easy way to implement Levenberg-Marquardt least squares registration in ITK?

Futhermore, I'm noticing that a lot of the ITK examples use itk::RegularStepGradientDescentOptimizer<http://www.itk.org/Doxygen/html/classitk_1_1RegularStepGradientDescentOptimizer.html>. Is this generally a good choice when solving optimization based registration problems with SSD objective functions? If so, is there literature to support this?


Thanks,

Alex Taylor