Multi-modal image registration using fuzzy kernel regression

Authors:
Edoardo Ardizzone;Roberto Gallea;Orazio Gambino;Roberto Pirrone
Affiliations:
Università degli studi di Palermo, DINFO, Dipartimento di Ingegneria Informatica, Palermo, Italy;Università degli studi di Palermo, DINFO, Dipartimento di Ingegneria Informatica, Palermo, Italy;Università degli studi di Palermo, DINFO, Dipartimento di Ingegneria Informatica, Palermo, Italy;Università degli studi di Palermo, DINFO, Dipartimento di Ingegneria Informatica, Palermo, Italy
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

This paper presents a study aimed to the realization of a novel multiresolution registration framework. The transformation function is computed iteratively as a composition of local deformations determined by the maximization of mutual information. At each iteration, local transformations are joint together using fuzzy kernel regression. This technique represents the core of the mothod and it's formally described from a probabilistic perspective. It avoids blocking artifacts and allows to keep the final deformation spatially congruent and smooth. Both qualitative and quantitative experimental results show that this approach is equally effective for registering datasets acquired from both single and multiple diagnostic modalities.