Speaker: Mert Rory Sabuncu, Princeton University
Date: Thursday, October 6 2005
Information-theoretic techniques, such as mutual information (MI) [Viola 95, Collignon 97], have yielded robust and accurate automatic multi-modal image registration algorithms. Inspired by this approach, our research employs the theory of entropic spanning graphs [Hero 2001] and proposes a novel graph-theoretic image registration framework. In this talk, I will provide a theoretical and experimental analysis of this framework, while drawing a rigorous comparison to a popular implementation of the MI-based registration algorithm. I will also elaborate on our recent contribution of showing how to obtain a gradient-based descent direction for the graph-theoretic registration function with minimal computational overhead. This result is then used for the efficient optimization of the registration function. Within the proposed framework, issues such as practical methods to speed up the algorithm and increase the robustness against "bad initialization", extensions to nonlinear transformations ,i.e., local deformations, and incorporation of prior knowledge (from pre-aligned image pairs) on the cross-modality relationship to improve robustness & speed will also be addressed. Experimental evidence for all the discussed ideas will be provided.
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