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2016 | OriginalPaper | Buchkapitel

Inertial Demons: A Momentum-Based Diffeomorphic Registration Framework

verfasst von : Andre Santos-Ribeiro, David J. Nutt, John McGonigle

Erschienen in: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016

Verlag: Springer International Publishing

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Abstract

Non-linear registration is an essential part of modern neuroimaging analysis, from morphometrics to functional studies. To be practical, non-linear registration methods must be precise and computational efficient. Current algorithms based on Thirion’s demons achieve high accuracies while having desirable properties such as diffeomorphic deformation fields. However, the increased complexity of these methods lead to a decrease in their efficiency. Here we propose a modification of the demons algorithm that both improves the accuracy and convergence speed, while maintaining the characteristics of a diffeomorphic registration. Our method outperforms all the analysed demons approaches in terms of speed and accuracy. Furthermore, this improvement is not limited to the demons algorithm, but applicable in most typical deformable registration algorithms.

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Vorheriges Kapitel Memory Efficient LDDMM for Lung CT

Nächstes Kapitel Diffeomorphic Density Registration in Thoracic Computed Tomography

A value higher than 1 leads to instability of the registration process as the magnitude of the update field \(\left\| u(x) \right\| \) keeps increasing at each iteration.

The statistical comparison between each original and proposed methods was performed through a Mann-Whitney U test. Although not shown here a significant improvement is also seen if \(\left\| u(x) \right\| \le 0.4\) for all methods.

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Titel: Inertial Demons: A Momentum-Based Diffeomorphic Registration Framework
verfasst von: Andre Santos-Ribeiro
David J. Nutt
John McGonigle
Verlag: Springer International Publishing
Buch: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016
Print ISBN: 978-3-319-46725-2

Electronic ISBN: 978-3-319-46726-9

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-46726-9_5

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