Directed Graph Based Image Registration

• Published in: Machine Learning in Medical Imaging Vol. 7009; pp. 175 - 183
• Main Authors: Jia, Hongjun, Wu, Guorong, Wang, Qian, Wang, Yaping, Kim, Minjeong, Shen, Dinggang
• Format: Book Chapter
• Language: English
• Published: Germany Springer Berlin / Heidelberg 2011; Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Directed Graph; Image Registration; Registration Method; Undirected Graph; Virtual Node
• ISBN: 3642243185; 9783642243189
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-24319-6_22

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.