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Assessment of Non-Rigid Registration

``Nothing in life is to be feared. It is only to be understood.''
- Marie Currie.

The most valuable contribution of this thesis is the introduction of a framework wherein NRR can be assessed without the use of ground truth. The framework is valuable not only because NRR applications are routinely used but because it offers a solution to a problem where cumbersome annotation is otherwise needed [].

The new assessment method exploits the relationship between NRR and model building, transforming the problem of assessing the NRR of a set of images into that of assessing the quality of a model built from the registered images.



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Roy Schestowitz 2010-04-05