ITK/Release 4/Enhancing Image Registration Framework: Difference between revisions

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* Separate computation of derivative components via chain rule.
* Separate computation of derivative components via chain rule.
# e.g.  Maximize  MI(  I(x) , J(T(x)) )  by gradient methods:
#
#  \partial Metric /  \partial Image  \partial Image / \partial Transform \partial Transform / \partial x


* Add feature based registration techniques (SIFT (patented?), SURF, etc)
* Add feature based registration techniques (SIFT (patented?), SURF, etc)

Revision as of 17:28, 7 September 2010

Enhancing Image Registration Framework

Goals

  • Review v4 registration plans and progress.
  • Catalog target use cases.
  • Discuss design changes in core itk to support these enhancements.
  • Wishlist items beyond standard use cases, e.g. projective transform (itkPerspective3DTransform).

Discussion Items

  • Separate sampling (interpolation strategy) and metric computation
  • Separate computation of derivative components via chain rule.
  • Add feature based registration techniques (SIFT (patented?), SURF, etc)

Refactoring of optimization framework

Wish List for ITKv4

Tcons

(Add one page for every tcon).

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