Point Set Registration Using Havrda-Charvat-Tsallis
Nicholas J. Tustison, Suyash P. Awate, Gang Song, Tessa Sundaram Cook, James C. Gee · 2011
We introduce a labeled point set registration algo- rithm based on a family of novel information-theoretic measures derived as a generalization of the well-known Shannon entropy. This generalization, known as the Havrda-Charvat-Tsallis en- tropy, permits a fine-tuning between solution types of varying degrees of robustness of the divergence measure between multiple point sets. A variant of the traditional free-form deformation approach, known as directly manipulated free-form deformation ,i s used to model the transformation of the registration solution. We provide an overview of its open source implementation based on the Insight Toolkit of the National Institutes of Health. Charac- terization of the proposed framework includes comparison with other state of the art kernel-based methods and demonstration of its utility for lung registration via labeled point set representation of lung anatomy.