Similarity metrics for groupwise non-rigid registration

Authors:
Kanwal K. Bhatia;Jo Hajnal;Alexander Hammers;Daniel Rueckert
Affiliations:
Visual Information Processing, Department of Computing, Imperial College London;Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College London, Hammersmith Hospital;Imaging Sciences Department, MRC Clinical Sciences Centre, Imperial College London, Hammersmith Hospital and Division of Neuroscience, Faculty of Medicine, Imperial College London, Hammersmith Hos ...;Visual Information Processing, Department of Computing, Imperial College London
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Year:
2007

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Abstract

The use of groupwise registration techniques for average atlas construction has been a growing area of research in recent years. One particularly challenging component of groupwise registration is finding scalable and effective groupwise similarity metrics; these do not always extend easily from pairwise metrics. This paper investigates possible choices of similarity metrics and additionally proposes a novel metric based on Normalised Mutual Information. The described groupwise metrics are quantitatively evaluated on simulated and 3D MR datasets, and their performance compared to equivalent pairwise registration.