Modat, M; Vercauteren, T; Ridgway, GR; Hawkes, DJ; Fox, NC; Ourselin, S; (2010) Diffeomorphic Demons using Normalised Mutual Information, Evaluation on Multi-Modal Brain MR Images. In: Dawant, BM and Haynor, DR, (eds.) Proceedings of SPIE. (pp. 76232K/1-76232K/4). SPIE - The International Society for Optical Engineering: Bellingham, US.

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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 large-deformation 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.

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