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Diffeomorphic demons using normalized mutual information, evaluation on multimodal brain MR images

Modat, M.; Vercauteren, T.; Ridgway, G.R.; Hawkes, D.J.; Fox, N.C.; Ourselin, S.; (2010) Diffeomorphic demons using normalized mutual information, evaluation on multimodal brain MR images. In: Dawant, B.M. and Haynor, D.R., (eds.) Medical Imaging 2010: Image Processing. (pp. 76232K). International Society for Optical Engineering: Bellingham, US. Green open access

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Abstract

The demons algorithm is a fast non-parametric non-rigid registration method. In recent years great efforts have been made to improve the approach; the state of the art version yields symmetric inverse-consistent largedeformation diffeomorphisms. However, only limited work has explored inter-modal similarity metrics, with no practical evaluation on multi-modality data. We present a diffeomorphic demons implementation using the analytical gradient of Normalised Mutual Information (NMI) in a conjugate gradient optimiser. We report the first qualitative and quantitative assessment of the demons for inter-modal registration. Experiments to spatially normalise real MR images, and to recover simulated deformation fields, demonstrate (i) similar accuracy from NMI-demons and classical demons when the latter may be used, and (ii) similar accuracy for NMI-demons on T1w-T1w and T1w-T2w registration, demonstrating its potential in multi-modal scenarios.

Type: Proceedings paper
Title: Diffeomorphic demons using normalized mutual information, evaluation on multimodal brain MR images
Open access status: An open access version is available from UCL Discovery
DOI: 10.1117/12.843962
Publisher version: http://dx.doi.org/10.1117/12.843962
Language: English
Additional information: Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/19174
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