Directed graph based image registration

Authors:
Hongjun Jia;Guorong Wu;Qian Wang;Yaping Wang;Minjeong Kim;Dinggang Shen
Affiliations:
Department of Radiology and BRIC, University of North Carolina at Chapel Hill;Department of Radiology and BRIC, University of North Carolina at Chapel Hill;Department of Radiology and BRIC, University of North Carolina at Chapel Hill and Department of Computer Science;Department of Radiology and BRIC, University of North Carolina at Chapel Hill and Department of Automation, Northwestern Polytechnical University, Xi'an, China;Department of Radiology and BRIC, University of North Carolina at Chapel Hill;Department of Radiology and BRIC, University of North Carolina at Chapel Hill
Venue:
MLMI'11 Proceedings of the Second international conference on Machine learning in medical imaging
Year:
2011

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Abstract

In this paper, a novel intermediate templates guided image registration algorithm is proposed to achieve accurate registration results with a more appropriate strategy for intermediate template selection. We first demonstrate that registration directions and paths play a key role in the intermediate template guided registration methods. In light of this, a directed graph is built based on the asymmetric distances defined on all ordered image-pairs in the dataset. The allocated directed path can be used to guide the pairwise registration by successively registering the underlying subject towards the template through all intermediate templates on the path. Moreover, for the groupwise registration, a minimum spanning arborescence (MSA) is built with both the template (the root) and the directed paths (from all images to the template) determined simultaneously. Experiments on synthetic and real datasets show that our method can achieve more accurate registration results than both the traditional pairwise registration and the undirected graph based registration methods.