A Demons Algorithm for Image Registration with Locally Adaptive Regularization

Authors:
Nathan D. Cahill;J. Alison Noble;David J. Hawkes
Affiliations:
Institute of Biomedical Engineering, University of Oxford, Oxford, UK and Research and Innovation, Carestream Health, Inc., Rochester, USA;Institute of Biomedical Engineering, University of Oxford, Oxford, UK;Centre for Medical Image Computing, University College London, London, UK
Venue:
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Year:
2009

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Abstract

Thirion's Demons [1] is a popular algorithm for nonrigid image registration because of its linear computational complexity and ease of implementation. It approximately solves the diffusion registration problem [2] by successively estimating force vectors that drive the deformation toward alignment and smoothing the force vectors by Gaussian convolution. In this article, we show how the Demons algorithm can be generalized to allow image-driven locally adaptive regularization [3,4] in a manner that preserves both the linear complexity and ease of implementation of the original Demons algorithm. We show that the proposed algorithm exhibits lower target registration error and requires less computational effort than the original Demons algorithm on the registration of serial chest CT scans of patients with lung nodules.